ENCYCLOPEDIA OF ENERGY RESEARCH AND POLICY
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ENCYCLOPEDIA OF ENERGY RESEARCH AND POLICY
A. L. ZENFORA EDITOR
Nova Science Publishers, Inc. New York
Copyright © 2010 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS.
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ISBN 978-1-61324-544-6 (eBook)
Published by Nova Science Publishers, Inc. Ô New York
CONTENTS Preface
xi
Research and Review Studies
1
Chapter 1
Energy Markets United States Government Accountability Office
3
Chapter 2
Three-Dimensional Simulation of Base Carrier Transport Effects in Back Side Point Contact Silicon Solar Cells K. Kotsovos and K. Misiakos
53
Multiple Effect Distillation of Seawater Water Using Solar Energy – The Case of Abu Dhabi Solar Desalination Plant Ali M. El-Nashar
85
Solid State Organic Photoelectrochemical Solar Energy Conversion Based on Conjugated Substituted Polythiophenes Teketel Yohannes
159
Chapter 3
Chapter 4
Chapter 5
A New Approach to Hybrid Systems of Renewable Energy Utilization Yu.V. Vorobiev, J. Gonzalez-Hernandez, P. Gorley, P. Horley and L. Bulat
201
Chapter 6
Dye-Sensitized Nano SnO2:TiO2 Solar Cells Weon-Pil Tai
Chapter 7
Strategies for Reducing Carbon Dioxide Emissions - The Case of Botswana Rural Communities C. Ketlogetswe and T.H. Mothudi
231
The Applying of Coatings and Surface Thermal Treatment of Materials in Solar Furnaces: Theory and Experiments V.V. Pasichny and B.A. Uryukov
245
Chapter 8
219
vi Chapter 9
Chapter 10
Contents Transparent Conductive Layers of Tin, Indium, and Cadmium Oxides for Solar Cells Yu.V. Vorobiev, J. Gonzalez-Hernandez, P. Gorley, V. Khomyak, S. Bilichuk, V. Grechko and P. Horley Dynamic Impedance Characterization of Solar Cells and PV Modules Based on Frequency and Time Domain Analyses D. Chenvidhya, K. Kirtikara and C. Jivacate
Chapter 11
Wind Energy Technology Overview United States Department of the Interior, Bureau of Land Management
Chapter 12
Federal and State Regulatory Requirements Potentially Applicable to Wind Energy Projects United States Department of the Interior, Bureau of Land Management
277
301 327
367
Chapter 13
Commercial Wind Energy Projects United States Department of the Interior, Bureau of Land Management
Chapter 14
Biomass And Bioenergy Research In Tropical Africa: State Of The Art, Challenges And Future Directions Jonathan C. Onyekwelu and Shadrach O. Akindele
385
Poplar Biomass of Short Rotation Plantations as Renewable Energy Raw Material Bojana Klasnja, Sasa Orlovic, Zoran Galic and Milan Drekic
419
Biobased Polymers by Chemical Valorization of Biomass Components B. Kamm, M. Kamm, I. Scherze, G. Muschiolik and U. Bindrich
449
Experimental Analysis of Small Combustion Thermal Systems Based on Pellets J.C. Morán, J.L. Míguez, E. Granada and J. Porteiro
481
Chapter 15
Chapter 16
Chapter 17
Chapter 18
Chapter 19
Chapter 20
Negative Emission Biomass Technologies in an Uncertain Climate Future Kenneth Möllersten, Zuzana Chladná, Miroslav Chladný and Michael Obersteiner A Review of the Socio-Economic and Environmental Benefits of Biomass Gasification Based Power Plant: Lessons from India Kakali Mukhopadhyay The Energy Balance and Fuel Properties of Biodiesel Mustafa Acaroglu and Mahmut Ünaldı
377
501
549 589
Contents Chapter 21
An Experimental Study on Performance and Exhaust Emissions of a Diesel Engine Fuelled with Various Biodiesels Nazim Usta
Chapter 22
New Materials from Lignin Carlo Bonini and Maurizio D’Auria
Chapter 23
Offgas Recycle for Increased Heat Production from Aerobic Thermophilic Treatment of Swine Waste: Pilot Studies and FullScale Design James W. Blackburn, Zhe Wang and Mahesh Mudragaddam
Chapter 24
Nuclear Dynamics Modelling by Recurrent Neural Networks F. Cadini, E. Zio and N. Pedroni 675
Chapter 25
Primary Cosmic Ray Studies Based on Atmospheric Cherenkov Light Technique at High-Mountain Altitude A.L. Mishev, S. Cht. Mavrodiev and J.N. Stamenov
Chapter 26
Development of Subchannel Analysis Code for CANDU-SCWR Yu Jiyang, Wang Songtao, Jia Baoshan
Chapter 27
Application of Best Estimate Computational Tools for Safety Accident Analysis in Nuclear Plants Anis Bousbia Salah, Tewfik Hamidouche and Francesco D’Auria
vii
603 625
653 675
731 779
811
Chapter 28
Advanced Fuel Fusion Reactors: Towards a Zero-waste Option Massimo Zucchetti
829
Chapter 29
Solar Thermal Power Generation on Mars Viorel Badescu
843
Chapter 30
Equilibrium Phases in Zirconium Alloys of Concern to the Nuclear Industry: Isothermal Sections of the Zr-Cr-Sn and Zr-Cr-Ti Systems S.F. Aricó, R.O. González and L.M. Gribaudo
893
Nuclear Nonproliferation: IAEA Safeguards and Other Measures to Halt the Spread of Nuclear Weapons and Material Gene Aloise
915
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners for Wall-Fired Boilers Zhengqi Li
939
Chapter 31
Chapter 32
Chapter 33
Chapter 34
Fuel Cell Combined Cycle Power Generation System Installed into Micro-Grid Shin’ya Obara
1061
Electricity from Renewable Energy Sources: A Multi-Criteria Evaluation Framework of Technologies Fausto Cavallaro
1107
viii
Contents
Chapter 35
Gas Turbines and Electric Distribution System Francisco Jurado
1139
Chapter 36
Micro CCHP: Future Residential Energy Center R. Z. Wang and D. W. Wu
1173
Chapter 37
Sensitivity Calculation in Real Time Transmission Network and Energy Markets Jizhong Zhu
1199
Wide-Area Monitoring and Analysis of Inter-Area Oscillations Using the Hilbert-Huang Transform A. R. Messina, M. A. Andrade and E. Barocio
1219
Chapter 38
Chapter 39
Unconventional Problems in Power Systems Protection Mahmoud Gilany and Mohamed A. Mahmoud
Chapter 40
BME-Generated Temperature Maps of the Nea Kessani Geothermal Field Konstantinos Modis, Hwa-Lung Yu, George Christakos, Robert Stewart and George Papantonopoulos
Chapter 41
Chapter 42
Chapter 43
Chapter 44
Chapter 45
1251
1265
Advances in Studies of Thermal-Fluid Geochemistry and Hydrothermal Resources in China Jianguo Du, Youlian Zhang and Heping Li
1281
A Comparative Analysis of the Geothermal Fields of Larderello and MT Amiata, Italy Giovanni Gianelli
1321
Sedimentary Characteristics of Coal Beds in Intramontane Basins (Massif Central, France) Wang Hua and Xiao Jun
1349
Coupling of Thermal and Chemical Simulations in a 3-D Integrated Magma Chamber-Reservoir Model: A New Geothermal Energy Research Frontier Surendra P. Verma and Jorge Andaverde Determination of the Damage Effect in Geothermal Wells Using Inflow Type Curves A. A. Aragón, S. L. Moya and A. M. C. Suárez
1361
1403
Expert Commentaries
1443
Commentary A Innovative Techniques for the Simulation and Control of Nuclear Power Plants Antonio Cammi and Lelio Luzzi
1445
Contents
ix
Commentary B Analysis and Characterization of Complex Inter-Area Oscillations from Measured Data: A Time-Frequency Perspective A. R. Messina, E. Barocio and M. A. Andrade
1449
Index
1453
PREFACE Chapter 1 - To better understand how changes in domestic and international petroleum products markets have affected prices, this book evaluates trends in (1) the international trade of petroleum products, (2) refining capacity and intensity of refining capacity use internationally and in the United States, (3) international and domestic crude oil and petroleum product inventories, and (4) domestic petroleum supply infrastructure. This is an excerpted and indexed version. Chapter 2 – This work presents a theoretical investigation of rear junction point contact silicon solar cells through three-dimensional numerical simulation based on the solution of minority and majority carrier transport equations in the base of the cell. The device series resistance is evaluated through the simulated current-voltage (IV) curves under AM1.5 illumination conditions and its dependence on back contact geometry is examined. Results are presented which show the influence of the majority carrier transport in the base to the solar cell performance. A comparison is also performed with two other similar types of point contact solar cells, one with the emitter located on the front surface and the other on both surfaces, as well as with a conventional solar cell structure. Chapter 3 - This report describes the solar desalination test plant in Abu Dhabi, UAE and gives a summary of its first year performance and economics. The plant has been operating successfully for 18 years supplying fresh water to the City of Abu Dhabi. The plant was commissioned in September 1984 and was running until the year 2002 when it was dismantled after fulfilling its objectives. The aim of the plant is to investigate the technical and economic feasibility of using solar desalination of seawater in providing fresh water to remote communities in the Middle East and to obtain long-term performance and reliability data on the operation of the plant. The plant has proved its technical feasibility and proved to be reliable in operation with few minor maintenance problems that required slight plant modification. Maintenance routines were established to maintain high plant performance. The economic feasibility of the plant was established by comparing the cost of water from a solar MED plant with a conventional MED plant using fossil fuel for plant capacity ranging from 100 m3/day to 1000 m3/day. It was found that the cost of water from solar MED plants is competitive with that from a conventional MED plant if the cost fuel continues to rise. Chapter 4 - The utilization of organic materials for photovoltaic devices has been investigated intensely during the last couple of decades. Earlier studies concentrated on molecules that had high optical absorption in the visible region of the electromagnetic spectrum. Recent discovery of conjugated polymers having semiconductor-like behavior has
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started to stir excitement because such materials are not only able to function in a similar manner to the inorganic semiconductors but also have important advantages such as: low cost, light weight, ease of fabrication and the possibility of large area coatings. Their use as photoactive electrodes is of increasing interest, as the processing possibilities of conjugated polymer materials have become more developed. Furthermore, the high absorption coefficients of these materials and the possibility of varying the band gap by molecular engineering have opened up new options for solar energy conversion. Among the conjugated conducting polymers, neutral, substituted polythiophenes exhibit interesting properties as semiconducting photoactive materials and are used for conversion of optical energy into electrical energy. Investigation of the photoelectrochemistry of conducting polymers was mainly focused on their use as protective films against photocorrosion and as photoactive electrodes in liquid junction photoelectrochemical cells (PECs). Photocorrosion and side reactions involving the electrolyte solution and the difficulty of packaging limit the working life of liquid electrolyte PECs. Solid-state PECs with the use of solid polymer electrolytes provide a means to eliminate this problem since they can easily be processed into thin films over large areas and are easier to encapsulate. The solvent-free ion conducting polymer electrolytes eliminated handling, portability, and packaging problems encountered in liquid junction photoelectrochemical cells. Basically, the photoelectrochemical properties occurring in these systems are the same as those occurring in systems based on semiconductor photoelectrodes in contact with liquid electrolytes. In this chapter an overview of the studies made on solid-state photoelectrochemical solar energy conversion devices using standard photoelectrochemical and photoelectrical characterization techniques is presented. The photoelectrochemical cells contain a thin film of semiconducting conjugated substituted polythiophenes as a light-harvesting unit, a redox couple complexed with an ion conducting polymer electrolyte, and a counter electrode. Chapter 5 - A general analysis is given of hybrid systems consisting of different combinations of 4 devices frequently employed for renewable energy utilization: Photovoltaic Solar Panel (PV), Solar Thermal Plane Collector (ST), Wind Generator (WG) and Heat-toElectric/Mechanic Energy Convertor (HE); some of the combinations include radiation energy flux concentrators of different degrees. The main result of the consideration made is that the hybrid systems are more efficient than the sum of the constituents and more stable in relation to spontaneous variations of the renewable energy source potential (like wind velocity, insolation, etc.). However, to realize the possibilities mentioned, all the elements of a given hybrid system have to be especially designed and made for this specific system. For example, the PV panel for the hybrid PV/Thermal system ought to have a substrate with high thermal conductivity, to allow for heat extraction from the panel by the adjacent Solar Thermal Plane Collector, and practically no commercial panels with these characteristics are available. Besides, the PV panel as a part of the hybrid system will demand a special choice of semiconductor material and surface treatment which could be different from those for conventional panels. The limiting efficencies for some hybrid systems are estimated; these efficiencies exceed the efficiencies of separate use of the devices discussed. The most promising hybrid system is the PV panel made as spectrum splitter in combination with HE converter, of which total efficency could be around 50 %. Chapter 6 – The nanostructured SnO2:TiO2 bilayered and composite solar cells sensitized by eosin Y and RuL2(NCS)2 dyes are prepared and the photoelectrochemical
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properties of the cells are investigated. The semiconductor films possess the grain size of nanometer order and have nanoporous structure. The bilayered cell shows higher IPCE (incident photon- to-current conversion efficiency) value than the single and composite cells. A maximum IPCE value of 88.1% was reached at 540 nm wavelength in the bilayered cell with 3.5μm-thick SnO2 and 7μm-thick TiO2 sensitized by RuL2(NCS)2 dye. The higher IPCE value in the bilayered cell is attributed to the promotion of the charge separation by fast electron transfer process from the excited dye to SnO2 in the SnO2/TiO2/dye system with different conduction band edge energy positions. Chapter 7 - The International Community’s pre-occupation with the ever-escalating dangers posed by gaseous pollutants need not be overemphasized. Suffice to mention, however that the magnitude of the dire negativity of pollutants is reflected in the numerous international charters that were promulgated with a common objective to sensitise the world about the need to move toward setting up minimum permissible levels of emission for activities whose execution result in atmospheric pollution. In addition, authorities have also gone so far as to offer incentives / motivation as a means of assuaging nations towards implementing various strategies for minimising atmospheric pollutions. This paper explicates efforts taken by. The government of Botswana in an effort to strive for compliance with international protocols and standards to safeguard against deterioration of the planet. Focus will specifically be paid to examining any concrete measures taken with the view to curb the negative impacts of carbon dioxide gas. The suitability and sustenance or, otherwise, of government projects envisaged for reducing carbon dioxide emission levels generated during the combustion of fuelwood and other related energy sources used by rural communities in Botswana will also be discussed. Chapter 8 - Solar furnaces make it possible to obtain a temperature of heating equivalent to 3500 K and above it an oxidizing air medium and without any outside contamination. They are used for investigation of materials in the Institute for Problems of Materials Science (IPMS) of theNational Academy of Science of Ukraine (NASU) for the past 40 years. The created experimental base consists of 14 different solar installations of power from 0.1 up to 10 kW. They are included in the two laboratories located in Kyiv and on the Black Sea coast. Some optical furnaces on Xe arc lamps which are the simulators of solar furnaces are added to the experimental base. In the given chapter the works of the last few years are concentrated. They are dedicated to surface heating of materials intended for obtaining coatings and improving their protective, decorative and other operational characteristics. The specialists of various fields of engineering and production are engaged in the development of these energy-intensive processes with the use of traditional energy sources. Their substitution for renewable solar radiation if it is possible can cause not only saving on utilities saving but in some cases the improvement of coatings quality due to chemical purity of the heating source. Some theoretical and experimental results of the investigation in the given field fulfilled in the IPMS are represented in the proposed work. Using an approximate integral method for solving heat conduction equation the problem is solved for the determination of the rate of thermal treatment of a surface by partial melting in a solar furnace when the sample is stationary and moves relative to the focal spot depending upon the given thickness of fused layer. Taking into account the absence hitherto of industrial (commercial) production of solar furnaces the theoretical and practical foundations have been developed in the IPMS for the creation of solar radiation concentrators on the basis of metallic antennae with plane mirror facets. As it is described in the given work the energy characteristics of these
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concentrators fully come up to the standards which are necessary for the realization of the greatest part of the investigated processes. Chapter 9 - Transparent conductive oxides SnO2, In2O3-SnO2 (ITO) and CdO are widely used for different optoelectronic devices, including photovoltaic applications. Depending on technological conditions, oxide films can be either high- or low-resistive. This paper presents the results of complex investigation of technological parameters influence (such as chamber pressure, substrate temperature, magnetron cathode power, and duration of isothermal annealing in the air) on specific resistance and transmission coefficient of oxide thin films, grown by reactive magnetron sputtering. Ar-O2 mixture was used as a carrier gas for direct current sputtering; high-frequency sputtering was performed in pure Ar atmosphere. Substrates for the films were made of quartz glass and silicon. Significant attention was paid to the transformation of defect subsystems after isothermal annealing in the air. The authors determined optimal technological regimes allowing to obtain reproducible high-quality thin films of tin, indium and cadmium oxides with the following electrical and optical parameters: SnO2 – specific resistivity ρ = 6 – 15.10-4 Ω⋅cm, optical transmission T = 90 – 95% in transparency region; ITO – ρ = 4 – 6.10-4 Ω⋅cm, T = 90 – 95%; CdO – ρ = 5 – 20.10-4 Ω⋅cm, T = 80 – 90%. Chapter 10 - This article describes new methods to derive dynamic impedance of solar cells and PV modules from time and frequency domain analyses. Initially, the authors propose a new method, based on the frequency domain analysis, to measure dynamic impedance of x-Si solar cells and PV modules in the dark using basic instruments and FFT analysis. The dynamic parameters in the AC equivalent circuit, in addition to the DC model, consists of dynamic resistance, diffusion capacitance and transition capacitance. Loci of impedance in the complex plane can be obtained by inputting a small signal square wave, superimposing on either forward bias or reverse bias, to cells or modules. Such technique is compared with sinusoidal inputting. All of these parameters can be obtained from impedance loci in the complex plane. The impedance of a cell or a module can be derived in a closed form equation in terms of frequency dependent and voltage dependent resistance and capacitance under the dark condition with reverse bias. The relationship between the dynamic and static characteristics is compared for solar cell modules having low and high fill factors. Another new analytical method determining solar cell and module dynamic impedance is demonstrated using the same measuring techniques. Determination of dynamic parameters, previously outlined, and time constant of solar cells and modules, based on a time domain response, can be simultaneously obtained at each bias condition. The merits of this second characterization method using square wave inputs are reduction in measuring steps and yielding of dynamic parameters and time constants in a single measurement. Experiments on polycrystalline and amorphous silicon cells and modules are also conducted and their results will be separately revealed at a later date. Knowledge of dynamic impedance characterization of solar cells and modules will lead to better understanding of behaviors of PV grid-connected systems and improvement of power quality from such distributed power generation systems. Chapter 11 - Modern wind energy technologies rely heavily on the very complex scientific discipline of fluid dynamics (which includes the study of the atmosphere) and the equally complex engineering discipline of aerodynamics. A comprehensive treatment of either of these disciplines is well beyond the scope of this programmatic environmental
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impact statement (PEIS). The discussions that follow are intended only to establish a basic understanding of wind technology and the factors that control its evolution. References are provided for those who wish to have a more detailed understanding of wind technology. This appendix provides an overview of the fundamentals of wind energy and wind energy technologies, describes the major components of modern wind turbines, and introduces terms that are unique to the field of electric power generation using wind energy. Important site characteristics and critical engineering aspects of wind energy technologies are presented, and their respective influences on future development decisions are discussed.[1] An overview of the current state of wind energy technology and ongoing research and development (R&D) is provided. Descriptions of a typical wind energy project and the major actions associated with each phase of development — site monitoring and testing, construction, operation, and decommissioning — are presented in part 3 of this PEIS. Chapter 12 - The tables that follow list the major federal and state laws, Executive Orders, and other compliance instruments that establish permits, approvals, or consultations that may apply to the construction and operation of a wind energy project on Bureau of Land Management (BLM)-administered lands. The general application of these federal and state authorities and other regulatory considerations associated with such construction and operation are discussed in Chapter 3. The tables are divided into general environmental impact categories. The citations in the tables are those of the general statutory authority that governs the indicated category of activities to be undertaken under the proposed action and alternatives. Under such statutory authority, the lead federal or state agency may have promulgated implementing regulations that set forth the detailed procedures for permitting and compliance. Definitions of abbreviations used in the tables are provided here. Chapter 13 - Data on commercial wind energy projects in the western states that are within the scope of this programmatic environmental impact statement (PEIS) are displayed in the tables below. The American Wind Energy Association (AWEA) compiles and maintains all of the data displayed below. All data presented are current as of January 14, 2004. All data are accessible electronically from the AWEA Web site at http://www.awea.org/projects/index.html. Data presented in the tables below are updated quarterly by the AWEA. The Bureau of Land Management (BLM) cannot guarantee the completeness or accuracy of these listings. Submission by wind farm developers or operators of project information to AWEA for inclusion in these listings is voluntary. Chapter 14 - Forest biomass and bioenergy production currently play a very important role in energy generation in tropical African countries, especially in the rural areas where between 75 and 95% of the populace depend on fuelwood as the primary energy source. Given the current high population growth, the low rates of switching to non-carboniferous household energy sources as well as the inefficiency of other energy sources, the importance of biomass and bioenergy in household energy generation in tropical African countries is expected to increase in the future. This paper examines the sources and extent of biomass production in tropical African countries as well as their current contribution to bioenergy supply and possible future trend. The current status and prospects of bioenergy technologies, the state of biomass and bioenergy research in the sub-region as well as the methodologies used in obtaining local and national biomass estimates were reviewed. The paper also discussed the challenges facing biomass and bioenergy research in tropical Africa, and
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stressed the need for more collaboration with the developed countries to be able to tackle the challenges. The paper finally examines the likely future research directions and makes recommendations towards a more efficient and environmental-friendly utilization of biomass and bioenergy in the sub-region. Chapter 15 - Fast-growing broadleaf species (poplars, willows and black locust), raised in dense, short-rotation plantations, very often on the soils unsuitable for agricultural crops, produce a high yield of biomass. A significant amount of thermal energy can be obtained by direct combustion of young plant biomass (aged from one to three years) converted into chips by chipping the whole trees together with bark and branches. In this aim, the Institute carried out systematic multiannual research on the improvement of several poplar clones in order to increase the yield of biomass. Also for this purpose, the selection focused on the clones which are best adapted to the conditions of very dense planting, which is the main condition required from the foresters in the establishment of energy plantations. Based on the calorific value of wood and bark of the study poplar clones, it is assessed the quantity of energy which could be produced by the combustion of the chipped biomass of one-year, i.e. two-year-old plants. The higher heating value of wood and bark was determined for several poplar clones (Populus spp.) of different ages and plants, as well as the trees from mature plantings (aged from 8 to 14 years). By FVI (Fuel Value Index) which takes into account ash content, wood basic density, as well as moisture content, it was determined that poplar wood can be significant energy raw material, primarily because of its short production cycle and very high volume increment. The plantations are established in two variants, by planting the cuttings of the selected poplar clones, with two planting spaces, i.e. with 38,461 plant/ha, and 83,333 plant/ha, on the previously selected and prepared soil. To define the produced biomass of individual clones, the increment elements were measured after the cycles of one and two years. Average dry matter biomass yield reached 21 t ha-1 year-1 (38,461 plant/ha), and 12 t ha1 year-1 (83,333 plant/ha). Based on calorific values of oven dry wood and bark of each clone, average energy potential of researched poplar clones was estimated up to 395 GJ ha-1 year-1, and for denser plantations up to 222 GJ ha-1 year-1. Chapter 16 - Plants represent a natural chemical and polymer factory and food plant. Biorefineries combines necessary technologies between biogenic raw material and intermediates and final products. The paper present two strategies for producing of polymeric materials, firstly the utilization of the pre-determined natural macromolecular structure and secondly the using of biogenic building blocks. The first step is the fractionation technology from green biomass for producing of fiber-rich press cake and a nutrient rich-green juice. The main focus is directed on products, such as proteins, polylactic acid, cellulose and levulinic acid- sequence products and their application as well as their market. Chapter 17 - In this chapter a set joint of experimental techniques for assessing biomass combustion devices is presented. Small scale energy converters such as chimneys, boilers, stoves, etc, producing heat and/or hot water by combustion of biomass (wood, pellets, briquettes, etc.) are especially suited to domestic purposes. However, in regular commercial combustion conditions, this kind of use still has some disadvantages: besides the fact that some emissions (volatile organic carbons, carbon monoxide or NOx) may still be high, it is difficult to compare the quality and performance of equipment working in very different combustion conditions.
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Due to their relatively low cost and the complexity of combustion in such devices, modelling by numerical analysis is seldom attempted. Controlling operational factors are usually designed and regulated based on the manufacturer’s experience or on handbook values. In order to protect customers, and to assure compliance with minimum requirements for energy performance and maximum limits on pollutant emissions, several national and international regulations have been developed in recent years. Experimental analysis of these devices is a key technique for control and improvement. Chapter 18 - Mitigation of and adaptation to climate change belong to the most pressing global challenges for the 21st century. Major mitigation options include improved energy efficiency, shifting towards less carbon-intensive fossil fuels, increased use of energy sources with near-zero emissions, such as renewables and nuclear, CO2 capture and permanent storage (CCS), and carbon sequestration by protection and enhancement of biological absorption capacity in forests and soils. Bioenergy is one of several energy sources which could provide society with energy services with near-zero emissions. Bioenergy has a unique feature, however, which distinguishes it from other low-emitting energy supply options, such as solar, wind, nuclear, and clean fossil energy technologies. Bioenergy conversion could be integrated with a process which separates carbon. If the biomass feedstock is sustainably produced and the separated carbon is subsequently isolated from the atmosphere for a very long time the entire process becomes a continuous carbon sink – in other words such technologies yield negative CO2 emissions. Negative emission biomass technologies can be centralised or distributed; Centralised negative emission biomass technologies, biomass energy with CO2 capture and storage (BECS), build on the conversion of biomass into energy carriers in centralised conversion plants integrated with CO2 capture. The captured CO2 is subsequently transported and stored in geological formations. Distributed negative emission biomass technologies are based on the production of long-term carbon-sequestering charcoal soil amendment, with or without co-production of biofuels. In this chapter a BECS implementation scenario study is presented. The study analyses investments in BECS in a pulp and paper mill environment. The investment analysis is carried out within a real options framework taking into account the potential revenue from trading generated emission allowances on a carbon market. Uncertainty is considered in the economic modelling through the use of stochastically correlated price processes of one input price (biomass) and two output prices (electricity and CO2 emission permits) that are consistent with shadow price trajectories of a large-scale global energy model. The results suggest that BECS can be economically feasible within approximately 40 years. The chapter also discusses Research and Development needs for better understanding of the future overall potential of negative emission biomass technology implementation. Chapter 19 - There is a steady and continuing interest in biomass gasification in both the developed countries and developing countries. While the advanced countries are interested primarily from considerations of reduced emissions and waste utilisation, the developing countries look at biomass gasification as a means to augment commercial energy like electricity, diesel, fuel oil etc. India, a tropical country with a vast geographical area is richly endowed with renewable energy sources like solar, wind, biomass which can play a crucial role in meeting end use energy needs in a decentralised manner. One of the major goals of the ninth and tenth five year plan is strengthening of infrastructure (energy, transport, communication, irrigation) in
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order to support the growth process on a sustainable basis. It is usually the tendency of the developing countries to equate development with economic growth and to further equate economic growth with energy consumption especially electricity. India being a developing country has also given due emphasis on strengthening its energy position accordingly. Moreover threat from Green House Gasses (GHG) also has caused worldwide concern. In India electric power generation is the largest source of GHG emissions. It accounts for 48% of carbon emitted. These concerns point towards more rational energy use strategies. The renewable and recycling process makes biomass possible to generate power without adding to air emissions. Biomass (firewood, agricultural residue, and dung) is one of the main fuels in India, particularly in the energy-starved rural sector. The biomass power potential in India was 16,000 MW (excluding co-generation), but the achievement in this respect is negligible (Installed capacity - 630 MW Project under implementation - 630 MW, as on March 2005). It brings out the fact that much of the potential of biomass gasification is still unexplored. Globally, India is in the fourth position in generating power through biomass and with a huge potential, is poised to become a world leader in utilization of biomass. According to the Planning Commission of India, in its Tenth Five Year Plan, announced that 26.10 per cent of the Indian populations are below the poverty line and mostly belongs to rural areas. The inequitable distribution has been evident from the fact that although 70% of India’s population lives in the rural areas, only 29% of rural households have electricity supply as against 92% of urban households. Of the half a million or so villages in India, about 3, 10,000 villages have been declared to be electrified and 80,000 more villages remain completely un-electrified. There are a number of constraints to supply power to remote rural area such as small human settlements, geographically dispersed villages, seasonally of loads etc. In the absence of adequate network and hence supply of power to remote rural areas the household depend largely on primary energy sources like kerosene and diesel for lighting. No commercial investments in micro enterprises can therefore be made by either individuals or companies without installing diesel generators which have a very high generating cost. Biomass gasifier is a leading option in that respect. Besides, the supply of power to remote rural areas from the centralised grid is not competitive than a modern biomass gasification based decentralised power plant. Estimate from an Indian village shows that modest 50 kW of installed capacity per village will lead to total saving of 52000 million Rs (Rs 5200 Crore / 1100 million US $) in power plant investments. In energy terms, the saving in TandD losses will release a generation capacity of 800 MW for profitable sale. Reduced pollution and reduction of CO2 emissions will be the other advantages of a decentralised renewable energy based system for the rural areas. The purpose of the present paper is to evaluate the rural electrification programme in India undertaken by the Ministry of Non Conventional Energy Sources (MNES), Government of India, through biomass gasifier power plant. It explores the eradication of poverty that has been made possible by introducing biomass gasification based power plant in remote rural areas in India. Creation of jobs in the power stations, small-scale business, commerce and industries and also improvement in the quality of life is assessed. The paper concludes with policy options relevance for the other developing countries. Chapter 20 - In this study energy balance and fuel properties of biodiesel has been calculated. Accordingly, the cost of 1 liter of oil is calculated 0.32 € after the income from the seed meal is deduced. Finally, the cost of per unit of biodiesel (1 liter) was calculated as 0.55
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€, after deduction of the income provided by the sales of glycerin for use in soap and cosmetic industry. The energy equivalent of total output was calculated 147605.50 MJ per hectare. The net energy gain (refined oil) was found as 15105.63 MJ per hectare (The net energy ratio 11.031) according to yield and inputs values. The viscosity values of vegetable oils vary between 27.2 and 53.6 mm2/s whereas those of vegetable oil methyl esters between 3.59 and 4.63 mm2/s. The flash point values of vegetable oil methyl esters are highly lower than those of vegetable oils. The flash point values of vegetable oil methyl esters are highly lower than those of vegetable oils. An increase in density from 860 to 885 kg/m3 for vegetable oil methyl esters or biodiesel increases the viscosity from 3.59 to 4.63 mm2/s and the increases are highly regular. There is high regression between density and viscosity values vegetable oil methyl esters. The relationships between viscosity and flash point for vegetable oil methyl esters are irregular. An increase in density from 860 to 885 kg/m3 for vegetable oil methyl esters increases the flash point from 401 to 453 K and the increases are slightly regular. The LHV values of vegetable oils methyl ester vary between 35.74 and 39.16 MJ/kg. Chapter 21 - Instability and increases in prices of petroleum-based fuels, gradual depletion of world petroleum reserves and increases in environmental pollution caused by exhaust emissions speed up research on renewable alternative fuels. Vegetable oils have been considered as renewable alternative fuels in compression ignition engines for a long time. However, they have not been widely used as fuels in the engines due to some technical and economical drawbacks. Some properties of vegetable oils such as high viscosity, lower volatility and lower heat content result in technical problems in direct using of vegetable oils in short and long term applications. From economical point of view, the main problem is that vegetable oils have been more expensive than petroleum Diesel fuel. There are various ongoing studies on solving these problems to be able to use vegetable oils in Diesel engines. Different methods such as preheating oils, blending or dilution with other fuels, thermal cracking/pyrolysis and transesterification have been developed. Among these techniques, transesterification appears to be the most promising one. It is a chemical process converting vegetable oils to alcohol ester of oil named as biodiesel. In general, biodiesel-Diesel fuel No.2 blend can be used as a fuel in Diesel engines without modification. Specifications of biodiesel mainly depend on oil, transesterification process, type and amount of alcohol, type and amount of catalysis, reaction time and temperature. Biodiesel can be produced from different kinds of vegetable oils. Since prices of edible vegetable oils are higher than that of Diesel fuel No. 2, waste vegetable oils and non-edible crude vegetable oils are mostly preferred as potential low priced biodiesel sources. It is also possible to use soapstock, a by-product of edible oil production, for cheap biodiesel production. In this study, various biodiesels were produced from raw vegetable oils (rapeseed oil, soybean oil, cotton seed oil, palm oil and tobacco seed oil), waste sunflower vegetable oils and hazelnut oil soap stock-waste sunflower vegetable oil, and their specifications were compared with each other. The biodiesel (20% in volume) - Diesel fuel No.2 (80% in volume) blends were tested in a four cycle, four cylinder turbocharged indirect injection Diesel engine. The effects of biodiesel addition to Diesel fuel No.2 on the performance and emissions of the engine were investigated at full load. Experimental results showed that the
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biodiesels can be partially substituted for Diesel fuel No.2 at most operating conditions in terms of performance parameters and emissions without any engine modification and preheating of the blends. Chapter 22 - Lignin, obtained through steam explosion from straw, was completely characterized via elemental analysis, gel permeation chromatography, ultraviolet and infrared spectroscopy, 13C and 1H nuclear magnetic resonance spectrometry. Lignin powder was used for the preparation of blends with low-density polyethylene (LDPE), linear low-density polyethylene (LLDPE), high-density polyethylene (HDPE) and atactic polystyrene (PS). The obtained blends are processable through the conventional techniques used for thermoplastics; the modulus slightly increases for most lignin-polymer blends, while the tensile stress and elongation reduce. Moreover, lignin acts as a stabilizer against the UV radiation for PS, LDPE and LLDPE. Polyurethanes were obtained treating steam exploded lignin from straw with 4,4’methylenebis(phenylisocyanate), 4,4’-methylenebis(phenylisocyanate) – ethandiol, and poly(1,4-butandiol)tolylene-2,4-diisocyanate terminated. The obtained materials were characterized by using gel permeation chromatography, infrared spectroscopy and scanning electron microscopy. Differential scanning calorimetry analysis showed a Tg at -6 °C, assigned to the glass transition of the poly(1,4-butandiol) chains. The presence of ethylene glycol reduced the yields of the polyurethanes. The use of the prepolymer gave the best results in polyurethanes formation. Steam exploded lignin was used as starting material in the synthesis of polyesters. Lignin was treated with dodecanoyl dichloride. The products were characterized by using gel permeation chromatography, infrared spectroscopy, 13C and 1H nuclear magnetic resonance spectrometry, and scanning electron microscopy. Chapter 23 - Pilot plant experiments with both a 3.79 m3 batch and semi-continuous reactor have been performed with whole, fresh swine manure and the production of biochemical energy as heat has been both measured and calculated. The reactor operates at near atmospheric pressure and about 55˚ C. The systems were equipped with a patented offgas recycle process that may be shown to increase the amount of recoverable and useful energy from the reactor compared with a once-through aeration system. The batch study, a statistically-designed series of experiments, was held to investigate the relationships of initial or feed total solids concentration, fresh air fed, and offgas recycle rate to the total biochemical energy produced in the system. A linear model was developed to determine the importance of these factors in design. The model indicates optimism for improved operation over pilot plant work performed. The recycle concept is most useful when a reactor design is desired with a relatively shallow depth (e.g., 3 m aeration submergence), as may be found in in-ground concrete tanks. Good results may be achieved in deep aeration submergence reactors with no offgas recycle, owing to the higher oxygen transfer efficiencies in tall tanks. A combination of tall tanks and offgas recycle is synergistic with improved results. These results will be presented and discussed in the context of a full-scale farm application. When compared to once-through aeration systems, offgas recycle also leads to major reductions of emitted offgas, and aiding odor and pollutant reductions. Other potential applications will also be discussed. Chapter 24 - The design, operation and control of highly risky industrial systems, such as in the nuclear, chemical and aerospace, entail the capability of accurately modelling the
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nonlinear dynamics of the underlying processes. In this respect, Artificial Neural Networks (ANNs) have gained popularity as valid alternatives to the lengthy and burdensome analytical approaches to reconstructing complex nonlinear and multivariate dynamic mappings. In particular, Recurrent Neural Networks (RNNs) are attracting significant attention, because of their intrinsic potentials in temporal processing, e.g., time series prediction, system identification and control, temporal pattern recognition and classification, whereas classical feedforward neural networks are in general capable of representing only static input/output mappings. The aim of this chapter is to present two kinds of recurrent neural networks and show their capabilities of approximating the temporal evolution of complex dynamical systems. First, the Elman’s recurrent network is considered, in which external feedback connections feed the output of the hidden nodes back to a set of additional nodes placed in the input layer. The network’s modelling capabilities are demonstrated on a case study concerning the prediction of the behaviour of a steam generator in a nuclear power plant. A more advanced type of recurrent architecture is then presented: the Infinite Impulse Response-Locally Recurrent Neural Network (IIR-LRNN), characterized by nodes which contain local, internal feedback paths realized by means of IIR synaptic filters providing the network with the necessary system state memory. The effectiveness and criticalities of this type of recurrent neural network are tested on two highly nonlinear dynamic systems of literature, the discrete-time Back-Tsoi model and the continuous-time Chernick model describing the evolution of the neutron flux in a nuclear reactor. Chapter 25 - A new method for primary cosmic ray investigations based only on atmospheric Cherenkov light flux analysis is presented. The method is applied for the solution of two of the main problems in astroparticle physics: ground based gamma ray astronomy, selection of events initiated by primary gamma quanta and the energy and mass composition estimation of primary cosmic ray in the region around the “knee”. The lateral distribution of atmospheric Cherenkov light flux in extensive air showers initiated by primary proton, Helium, Oxygen and Iron nuclei with energies in the range from 1013 eV to 1017 eV were obtained with the help of the CORSIKA 5.62 code, using VENUS and GHEISHA hadronic interaction models for the Chacaltaya observation level of 536 g/sm2. The lateral distribution of Cherenkov light flux in extensive air showers is approximated using a nonlinear fit such as Breit-Wigner. A detailed study of the energy dependence of the proposed model function parameters is carried out and the fit of model parameters as a function of the energy is obtained as well. On the basis of the difference between the model parameters, precisely their behavior as a function of the energy, the strong nonlinearity of the model, the authors propose a method, which permits the making of the distinction between a primary gamma quanta from a primary nuclei. The efficiency of the method is estimated and studied. An additional analysis for primary nuclei is carried out, towards the development of a similar method for simultaneous energy and mass composition estimation of simplified cosmic ray spectra of protons, iron, helium and oxygen. Different detector displacements are analyzed using the simulation of simplified primary mass composition. The detector response is simulated taking into account the physical fluctuations of the processes, the statistical and possible systematic errors. The simulated and reconstructed events are compared and the accuracy in energy and primary mass estimations
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is obtained. Moreover, the accuracy in shower axis localization is studied and the corresponding criteria are proposed. On the basis of the obtained approximation of the lateral distribution of Cherenkov light, a fast Monte Carlo simulation of the response of a different detector displacement is carried out. The possible triggers for two different detector arrays are studied and the registration efficiency is estimated. Chapter 26 - The paper presents the development of a sub-channel thermal hydraulic analysis code named SUBCHAN. The code was originally developed to analyze a super critical CANDU type reactor which has such characteristics as horizontal fuel channels, heavy water moderated, super critical light cooled water, and any type of fuel bundle with or without thorium rods. Thermal-hydraulic model of SUBCHAN is based on four partial differential equations that describe the conservation of mass, energy and momentum vector in axial and lateral directions for the water liquid/vapor mixture. The heat transfer correlations and pressure drop correlations used in the SUBCHAN code are presented in this paper. The water properties package of the code is based on the Industrial Formulation 1997 for the Thermodynamic Properties of Water and Steam. The heat transfer correlation of super critical region is based on the experimental investigation of Xi'an Jiaotong University. By calculating the TACR case, which is operating at 12.5MPa pressure, compared with the results of ASSERT-PV code, the paper arrives at the conclusion that the development of the SUBCHAN code with super critical water property package is successful. Then the paper uses the SUBCHAN code to analyze CANDU-SCWR operating at 25.0 MPa pressure. The paper draws the conclusion that the SUBCHAN code can be used to analyze sub-channel thermal hydraulic analysis of CANDU-SCWR fuel channel. Chapter 27 - Computer codes are widely used for Nuclear Power Plants (NPP) safety analysis within a wide set of purposes including licensing issues, safety improvement programs of existing NPPs, better utilization of nuclear fuel, and higher operational flexibility, for justification of lifetime extensions, development of new emergency operating procedures, analysis of operational events, and development of accident management programmes. A safety key parameter of the evaluation and assessment of NPPs is closely related to the code ability in determining the time-space thermal-hydraulic conditions throughout the reactor coolant system and especially in the core region. In the beginning, the code development took place between the sixties and seventies during which sets of conservative models were used. Furthermore, the latter were also limited due mainly to the restricted computer memory, Central Process Unit (CPU) time, and performances. However, in light of the sustained development in computer technology and computational methods, the potential of computational features has been enlarged accordingly. Nowadays, it has become possible to switch to a new generation of computational tools consisting of coupling advanced computer codes and getting better realistic simulations of complex phenomena and transients that could occur in NPP. These packages include mainly a thermal-hydraulic system and reactor kinetics codes, as well as specific codes for the containment thermal-hydraulics, structural mechanics codes, and more sophisticated Computational Fluid Dynamics (CFD) codes. However, notwithstanding the complexity of these codes and the level of the present scientific knowledge, a computer code cannot be expected to accurately model phenomena that are not yet fully understood by the scientific community. In general, the results of code predictions, specifically when compared with experimental data, often reveal some
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discrepancies. These discrepancies could be attributed to several reasons as model deficiencies, approximations in the numerical solution, nodalization effects, imperfect knowledge of boundary and initial conditions. Therefore, it is necessary to investigate the uncertainty of the results and the sensitivity effect of the most effective parameters. The purpose of the present paper is to characterize the present situation as far as the code assessment and uncertainty predictions are concerned. This is achieved through a reevaluation of some typical activities carried out at the University of PISA. These examples concern mainly application of Best Estimate tools for PWR, BWR, VVER1000 and Research nuclear reactors accident analysis. On this basis, requirements and future needs in the field of Best Estimate tools are outlined. Chapter 28 - Most of the studies and experiments on nuclear fusion are currently devoted to the Deuterium-Tritium (DT) fuel cycle, the easiest way to reach ignition. Some of the main technological questions of future DT fusion reactors have been identified previously. Among those, in particular, the radioactive inventory in such reactors is due, besides tritium, to the neutron-induced radioactivity in the reactor structures. The recent stress on safety by the world community has stimulated research on fuel cycles other than the DT cycle, based on ‘advanced’ reactions, such as Deuterium-Helium-3 (DHe). Several studies have addressed the design of DHe reactors: concerning small-size near-term experiments, to begin to explore the possibilities of DHe plasmas, a DT burning plasma experiment at high magnetic field and high plasma densities is particularly compelling. Ignitor is a proposed compact high magnetic field tokamak, aimed at reaching ignition in DT plasmas and at studying them for periods of a few seconds. A design evolution of Ignitor in the direction of a reactor using a DHe fuel cycle has been proposed: a feasibility study of a high-field DHe experiment of larger dimensions and higher fusion power than Ignitor, still based on the core Ignitor technologies, has led to the proposal of the Candor fusion experiment. This paper deals with the radioactive waste issue for fusion reactors, proposing an innovative solution (the “zero-waste” option), which is a clear advantage of fusion power versus fission, in view of its ultimate safety and public acceptance. Even if feasible in theory, a zero-waste option for fusion reactors using the DT fuel cycle will be difficult to obtain. As a further step towards the zero-waste option, the features of fusion reactors based on alternative advanced fuel cycles have been examined, to assess whether that goal could be reached for such devices. Fusion reactors with advanced DHe fuel cycle turn out to have quite outstanding environmental advantages. Activation behaviour of materials after service in a DHe advanced fuel fusion experiment has been investigated. EUROFER, SiC/SiC and V-Cr-Ti materials have shown the possibility of being declassified to non-radioactive material (clearance) after their irradiation in the reactor plasma chamber wall, if a sufficient interim cooling time is allotted. AISI 316L, on the contrary, suffers the presence of Ni and N (alloying elements) and Nb and Mo (impurities). Chapter 29 - A "dynamic" solar power plant (which consists of a solar collector - thermal engine combination) is proposed as an alternative for the more usual photovoltaic cells. Upper bounds for the efficiency of solar thermal power plants operating in the Martian environment are first evaluated. A general thermodynamic approach, first presented here, clearly shows which of the three theories usually quoted in literature gives the exergy of thermal radiation. Recent works reporting accurate upper bounds for the efficiency of thermal radiation energy conversion into work are subsequently used in this chapter. The results refer to thermal
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engines powered by direct or diffuse solar radiation on Mars. Diffuse solar radiation is modeled as diluted or multiply scattered thermal radiation. A more elaborated model uses an endoreversible Carnot cycle to describe solar engine operation. Two strategies to collect solar radiation are analyzed: a solar horizontal collector and a solar collector whose tilt and orientation are continuously adjusted to keep the receiving surface perpendicular on Sun rays. Meteorological data measured at Viking Landers (VL) sites are used in computations. Results show that generally the influence of latitude on performance is important. In some situations the meteorological effects compensate the latitudinal effects and the output power is quite similar at both VL1 and VL2 sites. During a winter dust-storm day the maximum output power is much smaller than during autumn. High efficiency thermal engines should be used in combination with solar collectors kept perpendicular to the Sun’s rays. When a horizontal solar collector is considered, the dependence of the maximum output power on optimum solar efficiency seems to be quadratic at both VL1 and VL2 sites. When a collector perpendicular to the Sun’s rays is considered, this dependence is more complicated, but keeps the quadratic feature. No obvious difference exists between power plant performances in the two years of VL2 operation. A solar Stirling engine based on a horizontal selective flat-plate converter is analyzed in the last part of this chapter. All the computations were performed for a solar collection area similar in size with that of Mars Pathfinder’s Sojourner. The solar efficiency at noon is as high as 18 %. The power provided by the engine is as high as 16 W during autumn and winter. These results suggest that under the Martian environment the performance of properly designed solar Stirling engines is comparable with that of PV cell power systems. Chapter 30 - Zirconium has a low neutron capture cross-section and it is used in alloys for internal components of nuclear reactors, the currently named Zircaloy, Zr-Nb, ZIRLO, etc. In Zircaloy-2 and Zircaloy-4, chromium is an important component in order to assure good corrosion performance, and tin is one of the strengthening elements. On the other hand, titanium, in spite of its poor neutron transparency, has sometimes been considered an element, which could substitute zirconium in this kind of alloy. The present experimental study concerns two ternary systems Zr-Cr-X (being the X component Sn or Ti). Published data on phase equilibriums of these systems are very scarce and found only in Russian works. Many contributions to the knowledge of phase equilibriums in ternary and quaternary systems involving zirconium as the principal component were assessed by Ivanov O.S. et al. and published by the Metallurgical Institute of Moscow in the monograph Zirconium Alloys Structures in 1973. Stability domains of phases at different temperatures of those two ternaries were presented, especially as isothermal sections of the equilibrium diagram. The knowledge of transformations through equilibrium diagrams is essential in order to design or improve technological applications, especially in the temperature range where the Zr rich hcp/bcc solid solution reaction is possible. Alloys were prepared by melting the metal components in a non-consumable tungsten electrode arc furnace with a copper crucible under a high purity argon atmosphere. Phase characterizations and determination of their compositions were carried out by metallographic observations and electron microprobe analysis. X-ray diffraction was performed on some samples. The study of the Zr-Cr-Sn system involves alloys with compositions between 0 and 15 at. % Cr and 0 to 15 at. % Sn and heat treatments at temperatures of 860, 900, 960 and 980 ºC.
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Three alloys of the Zr-Cr-Ti system with 40 at. % Cr and different Zr/Ti ratios and one more, richer in Cr, were elaborated. Specimens were heat treated at 900 and 1100 ºC respectively. Results of equilibrium between the solid solutions and the intermetallic compounds are presented as tie lines and isothermal sections where the phase boundaries are also sketched. Chapter 31 - The International Atomic Energy Agency’s (IAEA) safeguards system has been a cornerstone of U.S. efforts to prevent nuclear weapons proliferation since the Treaty on the Non-Proliferation of Nuclear Weapons (NPT) was adopted in 1970. Safeguards allow IAEA to verify countries’ compliance with the NPT. Since the discovery in 1991 of a clandestine nuclear weapons program in Iraq, IAEA has strengthened its safeguards system. In addition to IAEA’s strengthened safeguards program, there are other U.S. and international efforts that have helped stem the spread of nuclear materials and technology that could be used for nuclear weapons programs. This testimony is based on the U.S. Government Accountability Office’s (GAO’s) report on IAEA safeguards issued in October 2005 (Nuclear Nonproliferation: IAEA Has Strengthened Its Safeguards and Nuclear Security Programs, but Weaknesses Need to Be Addressed, GAO-06-93 [Washington, D.C.: Oct. 7, 2005]). This testimony is also based on previous GAO work related to the Nuclear Suppliers Group—a group of more than 40 countries that have pledged to limit trade in nuclear materials, equipment, and technology to only countries that are engaged in peaceful nuclear activities— and U.S. assistance to Russia and other countries of the former Soviet Union for the destruction, protection, and detection of nuclear material and weapons. Chapter 32 - The kind of swirl coal burners is given. Radial-biased-combustion and centrally-fuel-rich swirl coal combustion technology was developed. In the air and the airparticle test facilities, the single sensor hot-film and the anemometers were used to measure air and air-particle flows in the near-burner region of different swirl burners. Both cold air flow and reacting flow experiments were performed in the industrial 50, 220, 410, 670 and 1025 ton per hour boilers. On an air-particle test facility, the characteristics of the pulverizedcoal concentrator with cone vanes were investigated. The influence of structure parameters, such as run parameters such as swirling vane angle and burner cone angle and length, and run parameters, such as non-swirl secondary air, central air and air supply, and primary air flow type on divergent angles, diameter and length of the central recirculation zone, mixing characteristic of the primary air and the secondary air, in-situ gas temperature and NOx formation near the burner zone, carbon in ash and NOx emission of boilers was determined with the radial-biased-combustion burner. The difference characteristics of gas/particle flow and coal combustion of the centrally-fuel-rich and dual register burners were obtained. The experimental results show that the two new burners simultaneously have the ability of high combustion efficiency, flame stability, low NOx emission and resistance to slagging and high temperature corrosion. The air-surrounding-fuel combustion theory was put forward. Chapter 33 - The introduction to urban areas of the micro-grid system has the following characteristics. (a) The distance between the heat-supply side and the heat-demand side is short, and effective utilization of exhaust heat is possible. (b) It is linked with the load leveling of the existing large-sized electric power facilities. (c) Since a facility suitable for the energy-demand characteristics of a region can be installed, energy efficiency may increase and facility costs may decrease. The micro-grid using a proton exchange membrane type fuel cell (PEM-FC) may greatly reduce environmental impact. However, when connecting an energy system to the micro-grid of a city area and operating, partial load operation occurs
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frequently and power generation efficiency falls. And, the electrode material (especially the catalyst material and the proton exchange membrane) of PEM-FC is expensive, and its system is complex. Consequently, it is necessary to connect two or more power generation systems to the micro-grid, and to design optimization of an operation plan for the purpose of maximization of power generation efficiency. Therefore, the methods of an improvement of the efficiency of the power generation system connected to the micro-grid installed into a city area are described. In this chapter, it consists of subjects of three studies on the micro grid. In these studies described in this chapter, the improvement of the subject of the micro grid is tried by combining fuel cell and other power equipment. Section 1 describes "Operation Plan of Micro Grid Using PEM-FC/Diesel Engine Generator Combined System." Section 2 describes "Carbon-Dioxide Emission Characteristic of Micro Grid Using PEMFC/Hydrogenation City gas-Engine Combined System." Section 3 describes "Dynamic Characteristics of Micro Grid Using PEM-FC/Woody Biomass Engine Combined System." Chapter 34 - The energy policy of many Western governments aims to diversify supply and reduce dependence on foreign sources and thus to maximise benefits from internal resources. Undoubtedly, the main strategy underlying this is one that seeks to optimise the use of renewable energy sources (RES). The development of these sources, as well as their market penetration, depends however not only on political will but also on sound management of energy demand in order to rationalise and stabilise energy consumption. In addition to fortifying the guaranteed energy supply, RES represent a potential that cannot be overlooked. This lies in their ability to reduce greenhouse gas emissions and thus to stem the growing trend of global warming, one which has accelerated particularly in recent years and which is due mainly to the use of fossil fuels for producing electricity. The use of RES for the production of electric power brings huge benefits both in terms of environmental protection as well as savings in non-renewable resources. Nevertheless, the very nature of RES raise technical and economic problems that create a considerable gap between their potential capacity and ways to feasibly exploit them. Their many different forms and the ways in which they may be used have to be carefully examined in order to evaluate the costs and other technical and environmental factors involved. The planning and appraisal of sustainable energy projects involve rather complex tasks. This is due to the fact that the decision making process is the closing link in the process of analysing and handling different types of information: environmental, technical, economic and social. Such information can play a strategic role in steering the decision maker towards one choice instead of another. Some of these variables (technical and economic) can be handled fairly easily by numerical models whilst others, particularly ones relating to environmental impacts, may only be adjudicated qualitatively. In many cases therefore, traditional evaluation methods and the chief economic and financial indicators are unable to deal with all the components involved in an environmentally valid energy project. Multicriteria methods provide a flexible tool that is able to handle and bring together a wide range of variables appraised in different ways and thus offer valid assistance to the decision maker in mapping out the problem. Chapter 35 - Lately, the use of gas turbines following the deregulation of the electricity supply industry has become greater quickly. The motivation for modeling the gas turbines and their controllers is determinant to the interpreting of their impacts on distribution systems. The model predictive control (MPC) is used to damp the oscillation when the power distribution system is subjected to a disturbance. MPC is selected because it can explicitly
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handle the nonlinearities, and constraints of many variables in a single control formulation. The IEEE 13 node power distribution system is employed to demonstrate the effectiveness of MPC to damp the oscillations of gas turbines. Among fossil fuels, gas is the most quickest, with a growth rate nearly double that of coal and oil. The electricity generation field is the leading market for gas. The natural gas business has a great interaction with the electricity market in terms of fuel consumption and energy conversion. On the other hand, the transmission and distribution activities are very similar with the natural gas transportation through pipelines. The power losses in gas and electric systems are compared. It is also demonstrated that the electricity system results more convenient for longer distances of gas wells from electricity consumption area. Chapter 36 - Combined cooling, heating and power (CCHP) system, as a distributed energy system, can work all the year and provide cooling/hot-water/power in summer, heating/hot-water/power in winter and hot-water/power in other seasons. In CCHP systems, the total energy efficiency increases to over 85%, while the average energy efficiency of conventional fossil fuel fired electricity generation systems is around 40%. The energy efficiency promotion of CCHP systems results in emission reduction compared to the conventional methods of generating heat and electricity separately. And as a distributed energy resource, CCHP systems also increase in the reliability of the energy supply. With the overall development of CCHP systems and related technologies, the utilization of micro CCHP systems in the residential sector is emerged as a growing potential. The article focuses on the micro CCHP systems for single-family applications (around 10 kW) and multi-family or residential district applications (under 200 kW). The status quo of micro CCHP systems is briefly presented and diverse combinations of technologies existing in applications or experimental units are listed through comprehensive literature review. Various technologies available or under development are introduced, such as reciprocating internal combustion engine, micro-turbine, fuel cell, Stirling engine, absorption chiller, adsorption chiller and so on. Afterward, the tendency and issues of micro CCHP systems are discussed. The review shows that micro-CCHP applications are entering into average families as a nextgeneration residential energy supply center. Chapter 37 - The calculations of the several sensitivities such as loss sensitivity, voltage sensitivity, generator constraint shift factor, and area based constraint shift factor become very important in energy management system (EMS) and energy markets. This chapter focuses on the analysis and implementation details of the above-mentioned sensitivities calculations in the practical transmission network and energy markets. The power operator uses them to study and monitor market and system behavior and detect possible problems in the operation. These sensitivities calculations are also used to determine whether the on-line capacity as indicated in the resource plan is located in the right place on the network to serve the forecasted demand. If the congestion or violation exists, the generation scheduling based on the sensitivities calculations can determine whether or not a different allocation of the available resources could resolve the congestion or violation problem. This chapter also comprehensively discusses how to compute and use the sensitivities under the different references such as the market-based reference, and the energy management system based reference. The calculation results of the several sensitivities are illustrated using the IEEE 14 bus system and AREVA T & D 60-bus system. Chapter 38 - Many transient processes in power systems involve phenomena that vary in time and space in complicated ways. Comprehensive monitoring of large-scale power systems
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by means of properly placed time-synchronized phasor measurement units (PMUs) provides the opportunity to analyze and characterize complex inter-area swing dynamics involving all or most of the power system. Wide-area real-time monitoring may prove invaluable in power system dynamic studies by giving a quick assessment of the damping and frequency content of dominant system modes after critical contingencies. Measured data, however, may exhibit quite different dynamics at each system location or exhibit abrupt changes, dynamic irregularities, or be complicated by nonlinear trends or noise. Traditional Fourier and Prony methods for system identification are unable to resolve the localized nature of these processes and hence provide little useful information concerning the nature of noisy, time-varying oscillatory processes. In this Chapter, a new method for analyzing the temporal dynamics of nonlinear and nonstationary inter-area oscillations using a local empirical mode decomposition (EMD) method and the Hilbert transform is presented. Two novel algorithms are developed to address nonlinear and non-stationary issues. The first method is a local implementation of the empirical mode decomposition technique. The second is an algorithm to compute the Hilbert transform using finite impulse response (FIR) filters. By combining these approaches, the method can be used to analyze complex signals for which the conventional assumptions of linearity and stationarity may not apply and can be implemented for on-line estimation of modal damping and frequency using synchronized wide-area measurement systems. The physical mechanism underlying nonlinear time-varying inter-area oscillations is investigated and methods to characterize the observed oscillatory phenomena in terms of physically meaningful modal components are proposed. Emphasis is placed on identifying modal content in the presence of noise and nonlinear trends. Issues concerning the implementation of the method and numerical considerations are also discussed. As specific applications, data obtained from PMU measurements from a real event in the northern systems of the Mexican interconnected system are used to examine the potential usefulness of nonlinear time series analysis techniques to characterize the spatio-temporal characteristics of the observed oscillations and to determine the nature and propagation of the system disturbance. The efficiency and accuracy of the method is demonstrated by comparison to other approaches. Chapter 39 - Of the numerous electric power faults an Electric Engineer comes across in a life time, only a few of these faults are memorable- the rest being routine ones. In this chapter, some of those unconventional faults, which are mainly related to power system protection, are presented. The chapter presents five case studies of actual field incidents rather than hypothetical scenarios. The objective of the chapter is to present a typical approach for analyzing the faults in power systems. Chapter 40 - Temperature profiles have been empirically investigated in the underground geological formations of the Nea Kessani (Greece) geothermal system by the Greek Institute of Geology and Mineral Exploration using measurements in a set of vertical drill holes. In this work, we used the BME method to derive spatial temperature estimates in the Nea Kessani region in a mathematically rigorous and scientifically meaningful manner. The proposed analysis involves the solution of a stochastic partial differential equation representing the geothermal field and is conditioned on site-specific information (random boundary conditions reflecting in-situ uncertainties etc.). Temperature probability distributions were generated at the nodes of a dense spatial grid, which can provide a detailed understanding of the geothermal situation by means of various temperature maps (most probable, error minimizing
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etc.), depending on the objectives of the study. The BME solutions are more informative than the direct (analytical and numerical) solutions of the geothermal model obtained in a formal mathematical sense. Chapter 41 - This chapter introduces briefly distribution of hydrothermal resources, potential of hydrothermal energy, geochemistry of geothermal fluids and correlation between geothermal areas and seismic zones in China. More than 3,200 hydrothermal manifestations have been found in China. About 2,240 drilled wells reveal that 275 high temperature sites of hydrothermal energy, which are expected to supply a need of electric generators with total annual output of 5,800 MW. More than 2,900 sites of low and intermediate temperature geothermal systems have been found, which can be utilized for heating, medicine treating, bathing, farming, etc. Most geothermal waters in China are (Na, Ca)-HCO3 type, and some are (Ca, Na)-SO4 and Na-Cl types. Stable isotopic compositions of oxygen and hydrogen indicate the geothermal waters are derived from meteoric water, with small amount of magmatic volatile. Reservoir temperatures calculated with chemical geothermometers range from about 100 °C to 350 °C. Geochemical variations of geothermal fluids with time are found, which are correlated to hydrothermal eruption, earthquakes and exploitation. Main gaseous components of geothermal systems in China are CO2, N2, O2, and trace amount of H2S, H2, CH4, NH3, CO, C2H6, C3H8 as well as noble gases (Rn, He, Ar, Ne, Kr, Xe). The gaseous concentrations of geothermal systems are correlated to the temperatures of geothermal systems and seismic faults. The gases have a multiple origins of crust, mantle and atmosphere. The chapter emphasizes on both the spatial correlation between the geothermal areas/zones and the seismic zones and the energetic relationship between geothermal-fluid geochemistry and seismic activity. The more amounts of mantle gases the geothermal systems contain, the higher temperature of geothermal systems and the more active the seismic zones. The deep earth fluids provide both matter and energy for geothermal fields and earthquake generation, and carry the messages of geothermal reservoir and earthquake. Chapter 42 - The Larderello and Mt Amiata geothermal fields in Tuscany are large active thermal systems. Both likely overlie young plutonic rocks that serve as the principal sources of heat. The features of the two geothermal systems are similar. 1 Structural setting. The geothermal fields of Larderello and Mt. Amiata are located in the inner part of the Northern Apennines, characterized asthenosphere uplift and delamination of the crustal lithosphere or underplating. 2 The heat source both at Larderello and Mt. Amiata can be ascribed to the presence of shallow igneous intrusions. 3 The heat flow data for the area surrounding both the Larderello and Mt. Amiata geothermal fields show a comparable areal extension and similar values (up to 200-300 mW/m2 ). 4 Cap rocks and reservoirs. Both the Larderello and the Mt. Amiata fields have shallow vapor-dominated sedimentary, and deep metamorphic reservoirs. At Larderello super-heated steam is present in both reservoirs, to depth of more than 3.5 km, whereas the deep reservoir of the Mt. Amiata geothermal fields is likely water-dominated. In both fields the upper reservoir is present below the flysch units forming the cap rocks. 5 Permeability is due to rock fracturing, even at depths of about 4 km and temperatures as high as 350°C. Pressure greater than hydrostatic and a supercritical fluid can occur in the deepest part of the geothermal fields. 6 Hydrothermal alteration and contact metamorphism. At Larderello and Mt. Amiata there is evidence of an early contact metamorphism related with
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the intrusion of the granites. 6 Recharge. The water stable isotope values of the steam discharged by the geothermal wells at Larderello indicate a meteoric origin. A geochemical regional study on the thermal waters and gases of the Mt. Amiata area indicates that the geothermal reservoirs originated from a meteoric fluid, mainly stored in a regional Mesozoic dolomite-anhydrite unit, and evolved in a Na-Cl, CO2 gas-reach reservoir by interaction with calcite-bearing metamorphic rocks. The high temperatures existing in correspondence of a deep seismic reflector suggest the occurrence of a deep-seated unconventional geothermal resource (UGR), which can be possibly exploited. The heat could be mined from silica-rich rocks close to a plastic state, but where fracturing can be induced by fluid overpressure and abrupt high strain rates. This geothermal resource is very important, requires a re-assessment of the geothermal resources in Italy, considering the possibility of the exploitation of the new reservoirs. Chapter 43 - High-temperature geothermal reservoir is under consideration, consisting of two high-permeability layers, which are separated by a low-permeability stratum. The thermodynamic conditions are assumed to imply that the upper and lower high-permeability layers are filled in by water or by vapor, respectively. The stable stationary regimes of vertical phase flow between water and vapor layers in the low-permeability stratum may exist. The authors give possible types of transition to instability of the vertical flows in such a system under the condition of smallness of the advective heat transfer in comparison with the conductive one. It is found that in the generic case there exist three different scenarios of the instability onset of the stationary vertical flows. They are accompanied by the bifurcations of solutions describing the destabilizing vertical flows. The possible scenarios of the evolution of the system over the threshold of instability are discussed. Chapter 44 - Abundant genetic and sedimentary indicators has been found in the thick coal beds from three fault-controlled coal basins on the Central Massif France. A new formation model for thick continental (intra-mountainous) lacustrine peat swap is proposed. In the new coal accumulation mechanism, thick coal beds were associated with various gravity-influenced breccia and sandstone interlayer sediments and the subaquatic gravitary current transported the organic (peat) and inorganic clasts formed in lakeshore swamp were formed in active clastic environment, and were associated with various gravity-influenced mudstone and sandstone interlayers. The presence of a great number of gravity-flow sediments such as detrital flow, diluted slurry flow or turbidity-current sediments in the coal seams, and that of the contemporaneous gravity slump and deformation structures in the coal seams both indicate that the accumulation of the thick coal beds was characterized by the relatively deep water environment and allochthonous sedimentation. This new model interprets reasonably the accumulation mechanism of the thick coal beds developed in the fault basins in the Central Massif (France) and provides a completely new idea with respect to the traditional coal formation models. Chapter 45 - As an innovation, the authors propose that a new frontier in geothermal research should be explored that involves the coupling of thermal and chemical simulations in an integrated “magma chamber-reservoir” model. To achieve this innovation in geothermal research, the authors have written a new computer program (in Fortran 90) in modular structure that runs on a PC under the dynamic memory concept and simulates heat transfer conductive and convective processes both in a magma chamber and the overlying geothermal reservoir as well as computes in-situ major element chemistry of magmas that evolved in the magma chamber as a result of processes of assimilation, crystallization (liquid line of
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descent), magma mixing, recharge, and eruption. This combined task is accomplished in three dimensions (3-D) – a substantial improvement as compared to the current practice of obtaining thermal solutions in 1-D or 2-D and of modeling chemical data obtained from the analysis of surface outcrops without reference to the actual location within the Earth where the magmas were stored prior to eruption. In fact, if temperature estimates in drill wells and chemical data for surface rocks were available, this information can be used to constraint the model the authors are proposing as a new research frontier. The practice of “direct” modeling can be replaced in the future by inverse modeling when greater computing and storage capacities of personal computers will be available. This chapter briefly reviews the current state of thermal modeling of geothermal areas and presents the salient features of our new research approach, including a brief description of our computer program. An application example of a Mexican geothermal field (Los Humeros, Puebla), currently under exploitation for electricity production, will highlight the use of our software. This particular geothermal field was chosen for illustration purposes because of the availability of required thermal and chemical data to test the 3-D simulation model. The authors have successfully reproduced some of the major element chemical characteristics for the most voluminous caldera-forming eruption at about 0.46 Ma and the present-day thermal regime inferred from static formation temperatures using a quadratic regression of the actually measured bottom hole temperature data. Expert Commentary A - In the last decade, nuclear energy has gained a widespread renewal of interest as an important contributor to energy security, supply and sustainability. A number of new designs of nuclear power plants (NPP) has emerged recently, in attempts to achieve advances in the following areas: sustainability, competitive economics, safety and reliability, proliferation-resistance and physical protection. Actually, in the framework of the Generation IV International Forum (GIF), a task force has announced in 2002 the selection of six reactor technologies, which would represent the future shape of nuclear fission energy: these reactors operate at higher temperatures than today's reactors, allowing new and attractive applications, such as the thermo-chemical production of hydrogen. In addition to these six concepts for deployment between 2010 and 2030, the GIF has recognised a number of International Near-Term Deployment advanced NPPs available before 2015. Moreover, several international research projects are ongoing, which concern subcritical AcceleratorDriven Systems for radioactive wastes incineration, in conjunction with Partitioning and Transmutation technologies. Expert Commentary B - Large sparse power systems form an extremely complex dynamical system which usually possess many degrees of freedom and poses a challenge for simulation and analysis. Forced complex oscillations triggered by the loss of major system resources may manifest highly complex spatial and temporal dynamics and involve a large number of machines and take place over a great range of time and time scales. Proper understanding of the underlying dynamics causing these oscillations requires investigation of the various types of temporal nonlinear interactions involving the fundamental modes of the system. Such features may be obscured or distorted in the normal spectral analysis approach. The analysis of spatio-temporal dynamic patterns is important for many reasons. Nonlinearity causes the fundamental waves or temporal modes to interact, leading to frequency and amplitude modulation and to a phase relationship known as quadratic phase coupling between the frequency components involved. Mounting evidence suggest that these interactions can have a significant impact on system performance such as the modal content
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of the observed oscillations and may the design of controllers. Further, it is also possible that nonlinearity contributes to non-stationary behavior in the record.
RESEARCH AND REVIEW STUDIES
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 3-51
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 1
ENERGY MARKETS* United States Government Accountability Office WHY GAO DID THIS STUDY To better understand how changes in domestic and international petroleum products markets have affected prices, GAO was asked to evaluate trends in (1) the international trade of petroleum products, (2) refining capacity and intensity of refining capacity use internationally and in the United States, (3) international and domestic crude oil and petroleum product inventories, and (4) domestic petroleum supply infrastructure. To address these objectives, we reviewed numerous studies, evaluated data, and spoke to many industry officials and experts and agency officials.
WHAT GAO RECOMMENDS GAO is making recommendations aimed at improving the functioning of petroleum product markets, including that the Secretaries of Transportation and Energy coordinate with other agencies to (1) encourage more uniform biofuel and petroleum product blending practices, (2) conduct a study of infrastructure system adequacy, and (3) evaluate the assignment of a lead agency to coordinate permitting of infrastructure construction. In commenting on the report, the Federal Energy Regulatory Commission generally agreed with the report’s findings and recommendations, while the Departments of Energy and Transportation neither fully agreed nor disagreed. To view the full product, including the scope and methodology, click on GAO-08-14. For more information, contact Mark Gaffigan at (202) 512-3841,
[email protected].
*
This is an edited, reformatted and augmented version of GAO Report GAO-08-14, dated December 2007 publication.
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WHAT GAO FOUND International trade in petroleum products has expanded over the past two decades, making markets for gasoline and other petroleum products increasingly global in nature. Recent plans and mandates in the United States and other countries to greatly expand the use of biofuels blended with petroleum products—for example, ethanol blended with gasoline and biodiesel blended with petroleum diesel—may have the unintended effect of reducing opportunities for trade because blending different levels of biofuels with petroleum blending stocks will require changes to these blending stocks and thereby reduce their fungibility. For most of the past 25 years, there has been excess refining capacity globally, but this excess has shrunk considerably in recent years as demand has increased faster than capacity growth, causing refineries to run closer to their production capacity, and contributing to recent increases in petroleum product prices, price volatility, and refining profits. However, experts say it is unclear whether or for how long the current market tightness will continue, in part because of uncertainties about how much additional refining capacity will actually be built in the face of rising construction costs and initiatives that may reduce future demand for petroleum products such as through the blending of large volumes of biofuels into the transportation fuels markets. When measured as average days of consumption, inventories of petroleum products and crude oil in the United States indicate a general decline over the past 20 years. A number of factors have contributed to this decrease in the United States, including reductions in crude oil production and the number of refineries as well as efforts to reduce inventory holding costs by applying advances in technology. Lower operating costs associated with lower inventories may have translated into lower consumer prices during normal periods. However, lower than normal inventories can lead to higher or more volatile prices in the event of supply disruptions or surges in demand. The nation’s petroleum product supply infrastructure is constrained in key areas and is likely to become increasingly constrained, unless timely investments are made. A constrained supply infrastructure can exacerbate price effects and price volatility due to a supply disruption. However, no central source of data tracks system bottlenecks. While there is widespread recognition that a study is needed to fully identify the extent of infrastructure inadequacy and the impact on prices, to date, no such analysis has been undertaken, though such a study was mandated by Congress in 2006 with a June 2008 deadline. Significant infrastructure expansion plans in the private sector could alleviate the stresses. However, a complex permitting and siting process involving as many as 11 federal agencies and numerous state and local stakeholders has slowed or impeded the expansion and construction of new pipelines. Unlike in the case of natural gas pipelines, no central federal agency acts to coordinate this permitting process.
ABBREVIATIONS BP DOE DOT EIA
British Petroleum Department of Energy Department of Transportation Energy Information Administration
Energy Markets EPA FERC FTC IEA MARAD NYMEX OECD SPR
5
Environmental Protection Agency Federal Energy Regulatory Commission Federal Trade Commission International Energy Agency U.S. Maritime Administration New York Mercantile Exchange Organisation for Economic Co-operation and Development U.S. Strategic Petroleum Reserve
December 20, 2007 The Honorable Daniel Inouye Chairman, Committee on Commerce, Science, and Transportation United States Senate The Honorable Maria Cantwell United States Senate In 2003, the price of West Texas Intermediate crude oil, a widely watched benchmark crude oil price, averaged about $31 per barrel. By 2006, the average was about $66 per barrel, and in mid-November, 2007 the price rose to over $90 per barrel. Wholesale and retail prices of petroleum products refined from crude oil, including gasoline, diesel, and jet fuel, which normally rise and fall with crude oil prices, also generally rose over the period. For example, U.S. retail regular gasoline prices—equivalent to wholesale prices plus taxes, marketing costs, and retail profit margins—averaged $1.52 per gallon in 2003, but by August 2006, they had almost doubled to $3.00 per gallon, and as of July 2007, remained relatively high at $2.85 per gallon. Such large and sustained increases in gasoline prices have not been seen in the United States since the late 1970s and early 1980s, when the start of the Iran-Iraq war pushed prices up—even higher than today’s prices when adjusted for inflation—causing severe economic hardship for many Americans and contributing to a global economic recession. While this more recent increase in petroleum product prices does not appear to have had such far-reaching economic effects, consumers want to know the reasons for the large and relatively sudden price increases. Figure 1 shows retail regular gasoline prices in the United States, in both nominal and inflation-adjusted terms during the past 30 years. In addition to crude oil prices, a number of factors affect the price of petroleum products. As we recently testified before Congress, these factors include domestic capacity to refine crude oil into petroleum products; inventories of these products; the proliferation of special blends of gasoline; the capacity and functioning of the crude oil and petroleum product supply infrastructure, which is composed of pipelines, barges, tanker vessels, marine terminals, rail, trucking and storage tanks; and mergers in the oil industry.[1] In addition, because the United States imports and exports petroleum products, events outside the United States can affect domestic petroleum product prices. Imports to or exports from the United States typically enter or leave through port facilities on tankers or across national borders via pipeline. Our imports of petroleum products come from all over the world into ports in the Gulf of Mexico and the east and west coasts, and by pipeline from Canada. Refineries process crude oil into petroleum products through a variety of complicated processes, and a single barrel of crude oil produces a varying amount of gasoline, diesel, jet fuel, and other products depending on the configuration––or complexity––of the refinery as well as the type of crude oil being refined. Refineries can be optimized—or “upgraded”––to
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process different grades of crude oil through the addition of specialized refining equipment. U.S. refineries are generally optimized to produce large proportions of gasoline to meet domestic transportation demand. Cleaner-burning fuels have proliferated in response to legislation including the Clean Air Act Amendments of 1990, leading to additional investments in the refining equipment needed to produce the new fuels.
Source: GAO analysis of EIA data. Figure 1. U.S. Retail Regular Unleaded Gasoline Prices, Annual Average, 1976 – 2006.
More recently, a number of European countries, the U.S. federal government, and a number of individual states and localities have proposed or mandated the use of biofuels— such as ethanol made from corn or biodiesel made from soybeans or other crops—partly in an effort to reduce greenhouse gas emissions and reduce consumption of petroleum products. These mandates call for biofuels to be blended in varying proportions with traditional gasoline or diesel. For example, U.S. federal biofuel standards call for a minimum proportion and volume of biofuels to be sold each year but do not specify how that proportion is met. In addition, a number of states and at least one city have requirements or plans to require use of biofuels in varying proportions, blended with gasoline and diesel. For example: •
•
•
•
Hawaii, Minnesota, and the city of Portland, Oregon, all currently require ethanol to be blended at a 10 percent by volume rate with gasoline, although Hawaii only requires this for 85 percent of the gasoline sold in the state. Minnesota and Portland, Oregon require 2 and 5 percent biodiesel, respectively, to be blended with diesel fuel. Minnesota also requires the expansion of ethanol blending to 20 percent by volume by 2013. Four other states—Missouri, Montana, New Mexico, and Oregon—have biofuel mandates that will require 10 percent ethanol blended into gasoline and/or varying blends of biodiesel: Missouri and Montana have no mandated plans for biodiesel; New Mexico calls for 5 percent biodiesel blending and Oregon for 2 percent. Other states have “flexible standards.” For example, Iowa provides tax credits if at least 10 percent of the fuels used by 2009 are renewable, with the threshold rising to 23 percent in 2018. Yet this can be achieved in a flexible way, using a blend consisting of 85 percent ethanol and 15 percent gasoline, while other gasoline would
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be blended with less or no ethanol at all. Louisiana will require both ethanol and biodiesel to be blended at 2 percent, but only when state production reaches certain levels and prices of ethanol and biodiesel are sufficiently low. Finally, Washington will require that at least 2 percent of diesel sold be biodiesel by November 30, 2008, or when a determination is made that state biodiesel production can meet the 2 percent requirement. Automakers and refiners told us that these varying biofuel blends will require changes to the gasoline and diesel blendstocks––the fuels that will be mixed with the ethanol or biodiesel—to maintain engine performance and emissions requirements. The production of these new blends may also require further refinery changes as well as changes to automobile engines. Automakers also told us that in addition to increasing the costs of production, changing engines to be able to meet performance and emissions standards using a wide mix of biofuel blends would also entail potential losses in fuel efficiency. From refineries, petroleum products are distributed through an extensive supply infrastructure composed of pipelines, barges, tanker vessels, marine terminals, rail roads, trucks, and storage tanks. Pipelines are generally the cheapest domestic mode for transporting crude oil and petroleum products. Crude oil and petroleum products are transported in separate pipelines, and while different types and specifications of petroleum products are shipped in the same pipelines, they must be kept separate during transport and storage in order to maintain the specific desirable performance and emissions characteristics of these different fuels. Crude oil pipelines connect several large refining centers to crude oil sources, and petroleum product pipelines connect these refineries to population centers all over the country. Trucks and rail have generally distributed only a small fraction of petroleum products to wholesale terminals. However, they are being increasingly utilized to move ethanol to locations near final demand centers where the ethanol is blended with gasoline. This is because existing pipelines cannot currently accommodate ethanol due to an insufficient collector pipeline network linking ethanol refineries with major pipelines, and because ethanol has corrosive and other properties that complicate its transport in pipelines that also carry petroleum products. Refiners, distributors, and marketers of petroleum products maintain inventories of crude oil and petroleum products to facilitate smooth supply operations and mitigate the effects of supply disruptions. Crude oil and petroleum product inventories consist of three levels. Primary inventories comprise the crude oil or petroleum products held at production sites, refineries, and storage terminals, and in pipelines, tankers, barges, and other transportation centers. Secondary inventories consist of retail outlets and small storage facilities—those with less than 50,000 barrels of total capacity––that exist between the primary distribution system and the end user. Tertiary inventories are the petroleum products in the hands of end users, for example, in drivers’ gasoline tanks. The federal government also maintains strategic stocks of crude oil and, in the Northeast, heating oil to be released in the event of a major supply shortage. The Energy Information Administration (EIA) collects inventory data for the primary system. Information about changes in inventory levels can inform market participants about underlying demand or supply conditions that will influence prices. A number of federal agencies have programs and activities related to the oversight or monitoring of the refining, distribution, or importing of petroleum and petroleum products. For example, the Department of Transportation (DOT) oversees crude oil and petroleum
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product pipelines and monitors their operations to ensure public safety. The Federal Energy Regulatory Commission (FERC) regulates the “tariffs”—or rates and conditions—under which interstate crude oil and petroleum product pipelines operate, while individual states have oversight over intrastate pipelines within their borders. EIA collects data from refiners and others about shipments of crude oil and petroleum products by pipeline and barge between regions of the United States. In addition, a number of federal and state agencies and other local and private entities become involved in approving new supply infrastructure projects. For example, the approval to build or repair a pipeline could involve DOT’s Pipeline and Hazardous Materials Safety Administration, the Environmental Protection Agency, Bureau of Land Management (if pipelines cross federal lands), Army Corps of Engineers, U.S. Fish and Wildlife Service, as well as other federal agencies, and state and local stakeholders. Legislation in 2002 mandated the formation of an interagency committee to help expedite pipeline review and permitting processes for pipeline repairs. That committee is composed of 11 federal entities. For construction of interstate natural gas pipelines, the Federal Energy Regulatory Commission takes a lead role in coordinating the permitting process across the relevant federal agencies and can convey the right of eminent domain to builders of natural gas pipelines to resolve disputes with owners of land needed to build a pipeline.[2] However, no such federal coordinating authority or power of eminent domain exists for construction and expansion of new interstate petroleum product or crude oil pipelines. To better understand changes in domestic and international markets for petroleum products and the implications of these changes for recent price increases, you asked us to evaluate trends and effects on petroleum product prices in (1) international trade of petroleum products; (2) refining capacity and intensity of refining capacity use internationally and in the United States; (3) international and domestic crude oil and petroleum product inventories; and (4) domestic crude oil and petroleum product supply infrastructure, particularly pipelines and marine transportation. To evaluate trends in the international trade of crude oil and petroleum products, we analyzed data from EIA and the International Energy Association (IEA) and spoke with numerous government agency and oil company officials and industry experts. To assess trends in refining capacity, we evaluated IEA, EIA, and Oil and Gas Journal data, and spoke with numerous industry experts. To evaluate trends in inventories of crude oil and petroleum products, we reviewed data from EIA and IEA on inventories and demand to analyze international, U.S. national, and regional inventories. We analyzed New York Mercantile Exchange (NYMEX) and other futures market data, as well as EIA data, and asked experts about the effects of these futures prices for crude oil on inventory holding decisions. To evaluate trends in supply infrastructure for crude oil and petroleum products, we collected and analyzed available data on the pipeline and marine infrastructure system, capacity, throughputs, and constraints. We examined reports and data from supply disruption case studies to examine those cases’ impact on prices and price volatility. We spoke with numerous government agency and pipeline company officials and industry experts. This report focuses on long-term trends in the industry, rather than recent events that have influenced prices of gasoline and other petroleum products. GAO currently has ongoing work looking at such recent trends as refinery outages through the spring of 2007 and mergers in the industry since 2000.
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This report uses data from domestic and international wholesale petroleum products and crude oil markets and domestic retail markets. In contrast to retail prices, wholesale prices do not include taxes, distribution and marketing expenses, and profits. In every case for the data used in this report, we assessed and determined that the data were sufficiently reliable for our purposes. A more detailed description of the scope and methodology of our review is presented in appendix I. We performed our work from August 2006 through September 2007 in accordance with generally accepted government auditing standards.
RESULTS IN BRIEF International trade in petroleum products has expanded significantly over the past two decades, making markets for gasoline and other petroleum products increasingly global in nature. This trend has been particularly important for the United States; while in 1970 the United States was largely self-sufficient in gasoline, we now import over 10 percent of our annual gasoline consumption. Having access to more sources of supply can benefit the United States in the event of domestic supply disruptions. For example, the benefit of such flexibility in sources of supply helped U.S. marketers and retail sellers obtain gasoline and other petroleum products in the aftermath of Hurricanes Katrina and Rita, when imports of gasoline to the United States increased to fill the void left by damaged or shut-down domestic refineries and pipelines. However, the fact that petroleum product markets are international means that supply disruptions or unexpected increases in demand anywhere in the world can influence U.S. prices. Our analysis of wholesale prices in the United States, Europe, and Asia shows that prices in geographically dispersed markets rose significantly following Hurricanes Katrina and Rita, indicating that prices in these markets are linked to some extent. We also evaluated petroleum product import data and found that products came from a wider range of countries during this period, again indicating that products move in response to price signals globally. Recent plans and mandates in the United States and other countries to greatly expand the use of biofuels blended with petroleum products—for example, ethanol blended with gasoline and biodiesel blended with petroleum diesel—may have the unintended effect of reducing opportunities for trade because blending different levels of biofuels with petroleum blending stocks will require changes to these blending stocks and thereby reduce their fungibility. For example, if European countries adopt widely different blending levels biofuels in gasoline and diesel products as current plans call for, the refineries serving these countries will have to alter petroleum blending stocks for those blending levels, and this could make the blending stocks themselves less tradable across countries. For most of the past 25 years, there has been excess refining capacity globally, but this excess capacity has shrunk considerably in recent years as demand has increased faster than capacity growth, causing refineries to run closer to their production capacity, and, along with rising crude oil prices, contributing to recent increases in petroleum product prices and price volatility. Demand for petroleum products has grown more quickly than has refinery capacity for much of the past 25 years, in large part because excess refining capacity historically caused profitability of the refining sector to be low compared to that of many other industries. More recently, this tightening of the balance between supply and demand for petroleum products has, along with higher crude oil prices and other factors, contributed to increased petroleum product prices and higher oil industry profits, and could contribute to greater price
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volatility. Recently high petroleum product prices and increased profits over those seen during the 1990s in the refining industry have spurred new refinery capacity investments in the United States and internationally. However, experts say it is unclear whether or for how long the current market tightness will continue, in part because of uncertainties about how much additional refining capacity will actually be built in the face of rising construction costs, and initiatives that may reduce future demand for petroleum products such as through the blending of large volumes of biofuels into the transportation fuels markets in many countries. The absence of national standards for blending biofuels with gasoline and diesel could also increase the number of gasoline and diesel blending stocks refiners have to make, which could require additional refining investment to make those blends that could crowd out investment in refining capacity expansions. When measured as average days of consumption, long-term trends in inventories of petroleum products and crude oil in the United States indicate a general decline over the past 20 years. Similarly, gasoline and crude oil inventories in the Organisation for Economic Cooperation and Development (OECD) countries, excluding the United States, have also generally fallen over the same period.[3] Inventories, as measured by EIA IEA, and others, have some limitations as a measure of what is available to meet demand in the event of a supply shortfall, in part because the United States has imported an increasing share of its gasoline over the period during which inventories have fallen, and as such, the domestic inventory data do not account for large volumes of these products on the water or in tankers from foreign sources that are destined for the U.S. market or in storage terminals at foreign ports serving this trade in gasoline. A number of factors have contributed to the long-term decrease in inventory holdings in the United States, including reductions in both domestic crude oil production and the number of refineries. Advances in technology and changes in management processes also may have contributed to reduced inventories by enabling refiners to more closely time the production of supplies to meet expected demand. Lower operating costs associated with lower inventories may have translated into lower consumer prices during normal periods. However, in the short term, because inventories provide a smoothing effect against temporary demand and supply fluctuations, lower than normal inventories can lead to higher or more volatile prices in the event of supply disruptions or surges in demand. The nation’s petroleum product supply infrastructure is constrained in key areas and is likely to become increasingly constrained, unless timely investments are made. Industry and federal agency officials report a systemic lack of pipeline capacity in the supply infrastructure system in key states including Arizona, California, Colorado, and Nevada, and note the existing supply infrastructure is insufficient to carry the commensurate volumes of petroleum products and crude oil needed to meet growing demand there. A constrained supply infrastructure can exacerbate price effects and price volatility due to a supply disruption. For example, during a pipeline outage in 2003 that affected pipeline supplies to Arizona, retail prices of gasoline rose by about 45 cents per gallon. However, we were unable to assess the full extent of supply infrastructure constraints or the impacts of these constraints on prices and price volatility, in large part because there is no central source of data that tracks system bottlenecks. In 2006, DOT put forth a legislative proposal and Congress passed legislation that mandated the Secretaries of Energy and Transportation to conduct periodic analyses of (1) where unplanned petroleum product pipeline outages or insufficient pipeline capacity increase prices and (2) whether or not regulation is adequate to minimize the potential for unplanned losses of pipeline capacity. While there is widespread recognition that such a study
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is needed to fully identify the extent of infrastructure inadequacy and the impact on prices, to date, no such analysis has been undertaken. DOT and Department of Energy (DOE) officials told us that they were not allocated funds specifically to do the mandated analyses and that the agencies have not re-allocated other funds for this, although DOE told us it has met with DOT to discuss how this work could be approached. However, given that the study has not begun, it seems highly unlikely that agencies will be able to meet their June 2008 deadline for reporting to Congress. There are many private sector plans to expand the supply infrastructure, and if implemented in a timely fashion, these plans could significantly alleviate the stresses on the system. However, a complex permitting and siting process involving as many as 11 federal agencies and numerous state and local stakeholders has slowed or impeded the expansion and construction of new pipelines. The permitting process for building natural gas pipeline infrastructure has been made easier by the designation of FERC as a lead federal agency to streamline permitting for interstate natural gas pipeline expansion, but no such lead federal agency exists to facilitate permitting of crude oil or petroleum product pipeline construction or upgrading. GAO is making recommendations aimed at improving the functioning of petroleum product markets, including that the Secretaries of Transportation and Energy coordinate with other relevant agencies to (1) encourage uniform biofuel and petroleum product blending practices, (2) conduct a study of infrastructure system adequacy, and (3) evaluate the feasibility of assigning a lead federal agency to coordinate the permitting of infrastructure construction. In commenting on the report, the Federal Energy Regulatory Commission generally agreed with the report’s findings and recommendations, while the Departments of Energy and Transportation neither fully agreed nor disagreed.
BACKGROUND The United States is the largest consumer of crude oil and petroleum products of all nations, though demand for crude oil is growing faster globally, led by growth in developing countries such as China and India. When processed, crude oil is refined to produce petroleum products such as gasoline, diesel, and jet fuel, which have been instrumental in providing the nation with affordable fuel for automobiles, trucks, airplanes, and other forms of transportation and heating in some parts of the country. The petroleum industry consists of three main segments: the exploration and production segment (upstream); the refining and marketing segment (downstream); and a third segment typically referred to as the midstream, which consists of the infrastructure used to transport crude oil and petroleum products. Several U.S. agencies regulate and monitor the downstream and midstream oil industry and petroleum product markets.
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THE UNITED STATES IS THE LARGEST CONSUMER OF CRUDE OIL AND PETROLEUM PRODUCTS, BUT GLOBAL DEMAND HAS GROWN SIGNIFICANTLY IN RECENT YEARS While the United States is the largest consumer of crude oil and petroleum products, global demand for crude oil and petroleum products is growing at a faster pace than U.S. demand, driven by growing consumption of crude oil and certain petroleum products in developing countries such as China and India. In 2006, the United States’ share of world oil consumption was approximately 25 percent. The EIA projects in its reference, or “baseline,” scenario that world oil consumption will continue to grow and will reach 118 million barrels per day in 2030. About 43 percent of this growth will come from non-OECD countries, particularly China and India, but the United States will remain the world’s largest consumer. Under the assumptions of EIA’s reference case scenario, U.S. demand for oil is projected to increase by 30 percent between 2005 and 2030—from about 21 million barrels per day in 2005 to about 27 million barrels per day in 2030—compared to 39 percent for the entire world. Meanwhile, domestic production of oil has generally been in decline for decades, leading to greater reliance on imported oil. In 2006, the United States imported about 66 percent of its crude oil.
Source: GAO analysis of BP Statistical Review of World Energy June 2007. Notes: Other light distillates consists of aviation gasoline and light distillate feedstock (LDF) Other middle distillates consists of jet and heating kerosene, and gas and diesel oils (including marine bunkers) Fuel oil includes marine bunkers and crude oil used directly as fuel Others consists of refinery gas, liquid petroleum gas, solvents, petroleum coke, lubricants, bitumen, wax, and other petroleum products and refinery fuel and loss
Figure 2. U.S. Consumption of Petroleum Products, 1965-2006.
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When processed, crude oil produces petroleum products such as gasoline, diesel, and jet fuel, which have been instrumental in providing the nation with affordable fuel for automobiles, trucks, airplanes, and other forms of transportation, and—in some parts of the country—heating. Overall, demand for petroleum products in the United States has generally increased over the last 25 years, as shown in figure 2.
KEY ASPECTS OF THE PETROLEUM PRODUCT MARKETS: REFINING, INVENTORIES, AND INFRASTRUCTURE The petroleum industry consists of three main segments: the exploration and production segment (upstream); the refining and marketing segment (downstream); and a third segment typically referred to as the midstream, which consists of the infrastructure used to transport crude oil and petroleum products. This report is mainly concerned with certain aspects of the downstream and midstream segments, namely refining, inventories, and the pipeline and marine supply infrastructure.
Refining Refineries change crude oil into petroleum products primarily through a distillation process that separates the crude oil into different fractions based on boiling point ranges. One barrel of crude oil produces a varying amount of gasoline, diesel, jet fuel, and other petroleum products depending on the configuration–or complexity–of the refinery and the type of crude oil that is being refined. Through the addition of specialized equipment, refineries can be optimized—or “upgraded”—to produce greater proportions of specific types of products or to use different grades of crude oil. For example, hydrocracking units enable refiners to increase the production of lighter fuels including gasoline, diesel fuel, and jet fuel; catalytic cracking units increase the production of gasoline; and hydrotreating units enable refiners to produce lower-sulfur fuels required by the European Union, United States, and many other countries. Changes in product specifications, shifts in demand, and environmental regulations all have important implications for refineries. For example, the regulated shift to unleaded gasoline that began in 1974 caused refineries to install equipment to produce high-octane components to replace the lost lead. Similarly, in response to environmental regulations such as limits on the emissions of certain air pollutants refineries have invested in equipment and processes to control such emissions. The proliferation of some special gasoline blends, or “boutique fuels,” has made it more complicated to supply gasoline and raised costs, significantly affecting operations at refineries.[4] Last, to the extent that varying amounts of biofuels blended with gasoline and diesel require changes to the gasoline and fuel blendstocks, further refinery changes may be required to accommodate these blends. Shifting demand for petroleum products, such as Europe’s declining demand for gasoline and growing consumption of diesel, can also cause refiners to invest in different processes to produce the mix of products desired by the market. In general, the United States’ refineries are among the most sophisticated in the world, and domestic refineries have generally been optimized to produce large proportions of cleaner-burning gasoline to meet the huge transportation demand subject to various
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environmental constraints. Historically, U.S. and international refining capacity has broadly grown and fallen in response to shifts in demand for petroleum products. For example, U.S. and international refining capacity fell sharply during the early 1980s in response to falling demand for petroleum products, caused in part by high prices of these products and worldwide recession. By 1983, demand had fallen so much that almost 30 percent of U.S. refinery capacity was not being used. Many refineries were shut down or idled and refining capacity thus fell. Demand began growing again in the United States and internationally around 1982.
Inventories Inventories of petroleum products and crude oil are maintained by refiners, distributors, marketers, and others to mitigate the effects of disruptions, and to ensure a continuity of supply to their customers. Companies build inventories in preparation for planned maintenance and production, refining, and logistical systems. The primary inventory system comprises the crude oil or petroleum products held at production sites, refineries, and storage sites, and in pipelines, tankers, barges, and other transportation centers. Secondary inventories exist between the primary distribution system and the end user, and consist of retail outlets and small tank farms, which have less than 50,000 barrels of total capacity. Tertiary inventories are inventories held by consumers, for example, in automobile tanks. EIA collects inventory data for the primary system. EIA collects inventory data for crude oil and petroleum products held in storage at refineries, pipelines, and tank farms, and bulk terminals that can store at least 50,000 barrels of petroleum products. EIA also collects inventory data for Alaskan crude oil in transit by tanker from the terminus of the Alaskan pipeline in Valdez, Alaska, to other U.S. ports, as well as oil in the Strategic Petroleum Reserve.[5]
Pipeline and Marine Supply Infrastructure System The supply infrastructure is composed of petroleum product and crude oil pipelines, barges, vessels, marine terminals, and storage tanks. Trucks and rail also distribute a small fraction of the products––about 6 and 4 percent respectively––but are being increasingly utilized with the rise of biofuels such as ethanol, which existing pipelines cannot currently accommodate.[6] As displayed in figure 3, about 90 percent of all petroleum products currently travel by either pipeline or marine transport. Because of these two modes dominance, our analysis of the nation’s supply infrastructure system will be limited to the pipeline and the marine transport system. Pipelines are generally the least expensive mode for transporting oil and most petroleum products.[7] Most of the United States pipeline infrastructure—approximately 166,000 miles of crude oil and petroleum product pipeline—was constructed in the 1950s, 1960s and 1970s to accommodate the needs of the refining sector and demand centers at that time. These main pipelines were built to transport petroleum products from the Gulf Coast and Midwestern oil fields—where many of the nation’s refineries were—to the East Coast, the United States’ largest consuming region. The first large transmission pipelines for petroleum products were
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constructed during World War II, and ran primarily from the Gulf Coast to the Mid-Atlantic states; the network expanded significantly until the 1970s. Pipelines feed refinery centers and market hubs because the regions with the most supply are not the regions with the most demand. Most pipelines are common carriers, offering transportation services to anyone who wants them, but subject to some regulations. While crude oil and petroleum products generally do not travel on the same pipelines, numerous different petroleum products are shipped back to back in batches through the same pipelines. During this process, some blending of any two adjacent batches of petroleum products occurs where the two batches interface. This blended material may be simply mixed with the lower-valued product—for example, the mix of high- and low-octane gasoline at the interface between batches of these commodities would be downgraded, or mixed with the low-octane fuel—or, if the blended material is incompatible with either of the two petroleum products that interfaced, it must be removed and reprocessed into something that can be used. To access space on a pipeline, a shipper must ask for the right to use capacity by nominating amounts of liquid for service to be received, delivered or stored by the pipeline company. Different shippers’ nominations of common products are often combined by the pipeline in order to reduce the number of batches and therefore the amount of downgrading or reprocessing of blended products.
Source: GAO analysis of Bureau of Transportation Statistics data. Figure 3. Transport Mode of Petroleum Products in the United States, 2004.
Marine transportation of crude oil and petroleum products accounts for nearly one-third of domestic shipments. The marine transport system consists primarily of waterways; ports and vessels, including crude oil tankers; and product tankers and tank barges. Built to accommodate smaller vessels, many of the major ports have had to expand in response to increasing marine transport and trade and to accommodate larger tanker vessels.
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SEVERAL U.S. AGENCIES REGULATE AND MONITOR THE DOWNSTREAM AND MIDSTREAM OIL INDUSTRY AND PETROLEUM PRODUCT MARKETS Several U.S. agencies have jurisdiction over or monitor the U.S. downstream oil industry and petroleum product markets: •
•
•
•
•
Within DOE, EIA collects and analyzes data on the supply, consumption, and prices of crude oil and petroleum products, including inventory levels, refining capacity and utilization rates, and product movements into and within the United States. DOE’s Office of Fossil Energy manages the U.S. Strategic Petroleum Reserve (SPR), which is a federally maintained stockpile of about 700 million barrels of crude for use in the case of a major disruption of oil supplies, as well as the Northeast Home Heating Oil Reserve, a component of the SPR that has 2 million barrels of emergency fuel oil for homes and businesses in the Northeast that could be released during heating oil supply interruptions or high periods of demand caused by severe winter weather. FERC is an independent agency that regulates the transmission of oil through interstate pipelines by setting and enforcing pipeline “tariffs”—the prices and terms under which shippers send their products through the pipelines and the rules governing access to these pipelines.[8] The Federal Trade Commission (FTC) enforces antitrust and consumer protection statutes. For example, in the petroleum industry, the FTC generally reviews proposed mergers and approves such mergers only if they are deemed not to have anticompetitive effects. DOT’s Pipeline and Hazardous Materials Safety Administration regulates safety for oil pipelines that transport oil and petroleum products. Among other things, it oversees oil pipelines’ design, maintenance, and operating procedures. DOT’s Maritime Administration (MARAD) reports to Congress on the status of public ports’ supply infrastructure needs. The Environmental Protection Agency (EPA) develops and enforces regulations that implement environmental laws including the Clean Air Act, the Clean Water Act, and the Oil Pollution Act, which aim to control the discharge of pollutants into the environment by refiners and other industries. EPA also administers the National Environmental Policy Act, which requires federal agencies to consider environmental impacts of proposed actions.
In addition, individual foreign countries play regulatory roles and can affect trade conditions for products through their individual or collective actions. The IEA is an organization established by treaty of 26 mainly net oil-importing OECD countries to cope with oil supply disruptions and coordinate an international response in the case of a disruption to the global oil supply. Member countries agree to keep significant strategic stocks of crude oil and/or petroleum products to be available in the event of a severe supply disruption. IEA also maintains a database that provides information on IEA member crude oil and petroleum product inventory levels, refining capacity, and utilization rates.
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PETROLEUM PRODUCTS MARKETS HAVE BECOME INCREASINGLY GLOBAL WITH GREATER TRADE AND PRICES INCREASINGLY LINKED ACROSS COUNTRIES International trade in petroleum products has expanded significantly over the past 20 years, making the markets for gasoline, diesel, and jet fuel increasingly global in nature, and providing additional gasoline supply options for the United States. This trend has been particularly important for the United States, which has seen large increases in the volume of imported gasoline. A key impetus for global trade in petroleum products has been a structural surplus in production of gasoline and deficit in production of diesel in Europe as a result of a systematic switch in European countries to diesel-burning automobiles. While many experts we spoke with believe that growth in international trade of petroleum products will likely continue, they identified several factors that may limit or change the patterns of trade, including plans and mandates to introduce significant volumes of biofuels and the potential expansion of differing fuel specifications that a proliferation of biofuel blends would entail.
International Trade in Petroleum Products has Expanded Significantly International trade in petroleum products has expanded significantly over the past 20 years, making the markets for gasoline, diesel, and jet fuel increasingly global in nature. Specifically, our analysis of IEA data shows that OECD imports of gasoline, diesel, and jet fuel more than doubled between 1984 and 2006, from about 80 million barrels per month to over 160 million barrels per month. Similarly, OECD exports increased from about 55 million to over 140 million barrels per month over the same time period. While OECD exports and imports in these products have more than doubled, OECD demand for these products rose by less than 40 percent during the same time period. Figure 4 shows the increase in OECD imports and exports of gasoline, kerosene-type jet fuel, and diesel fuel.[9] Trade in gasoline has been particularly important for the United States, which has seen large increases in the volume of imported gasoline. While in 1970 the United States was largely self-sufficient in gasoline, we now import over 10 percent of our annual consumption of gasoline and smaller percentages of jet fuel and some other products.[10] U.S. imports of gasoline and gasoline blending components, which accounted for about 31 percent of our imports of refined petroleum products in 2005, averaged about 1.1 million barrels per day, or more than 10 percent of U.S. daily consumption. According to DOE, imports have supplied about half of U.S. gasoline demand growth from 1993 to 2005.[11] These “total gasoline” imports include finished gasoline, which can be sold directly to retail markets, as well as gasoline blending components that are combined in the United States to make finished gasoline to serve various markets, some of which use special, cleaner-burning gasoline blends as part of their plans to meet federal air quality requirements.
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Source: GAO analysis of IEA data. Figure 4. Imports and Exports of Gasoline, Kerosene-type Jet Fuel, and Diesel Fuel for All OECD Countries, 1984 – 2007.
Source: GAO analysis of EIA data. Figure 5. U.S. Imports of European Gasoline and Gasoline Blendstocks, 1993 – 2007.
A key impetus for global trade in petroleum products has been a structural surplus in production of gasoline and a deficit in production of diesel in Europe. This surplus of gasoline is largely the result of a systematic switch in European countries toward automobiles with diesel-powered engines, which are more efficient than gasoline-powered engines. European regulators promoted diesel fuel use in Europe by taxing diesel at a lower rate, and European demand for diesel fuel-powered vehicles rose. The European refining and marketing sector responded to this change in demand by importing increasing amounts of diesel, and exporting a growing surplus of gasoline to the United States. The United States has purchased
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increasing amounts of gasoline, including gasoline blendstocks, from Europe in recent years, as shown in figure 5. These imports have generally had a strong seasonal component, with higher levels of imports during the peak summer driving months and lower imports during the fall and winter. The major exception to this seasonality came in the months October 2005 through January 2006, when imports surged in response to U.S. shortfalls as a result of damage to and shutdowns of refineries and pipelines following Hurricanes Katrina and Rita in August and September 2005, respectively. Experts and company representatives told us they believe this structural imbalance within the European Union will continue for the foreseeable future, and perhaps widen, resulting in more exports of European gasoline and blending components to the United States. Specifically, company representatives and industry experts told us that European refiners are unlikely to significantly expand their refining capacity in the near future or reconfigure to produce less gasoline for a number of reasons, including the following: •
•
•
The profitability of the U.S. gasoline market acts as a draw for surplus gasoline worldwide. Many company representatives told us that the United States’ continued appetite for gasoline—combined with many countries’ declining demand—has resulted in most surplus gasoline being exported to the United States, and that this trend would likely continue in the future. For example, some refining interests in Europe told us they had configured their refinery operations to be essentially a U.S. “gasoline machine.” Construction costs have increased significantly, raising the cost of investments in refining capacity or upgrades. For example, some refining interests in Europe and elsewhere told us that some planned conversion and upgrading of refinery capacity in Europe was on hold, because of increased construction costs worldwide. Some of these upgrade plans called for enhanced diesel fuel production mainly for the European market, as well as surplus gasoline exported to the United States. European refiners told us that they are reluctant to make large investments necessary to produce significantly more diesel because doing so will increase their greenhouse gas emissions. Their concern is that as greenhouse gas emissions caps are lowered, companies will be required to pay to reduce emissions or buy costly emissions credits.
EIA and other experts have stated that, at times, imports from Europe could be provided more competitively than gasoline from the U.S. Gulf Coast and other domestic refineries. In addition, more sources of supply can also benefit the United States in the event of domestic supply disruptions. For example, the flexibility in sources of supply helped U.S. marketers and retail sellers obtain gasoline and other petroleum products in the aftermath of Hurricanes Katrina and Rita in August and September of 2005, respectively, when a large fraction of the nation’s refineries and pipelines were temporarily shut down. During the 3 months following the hurricanes, imports of gasoline to the United States increased by about 30 percent compared to what they were during the same months in the previous year, and imports came from a number of countries that do not typically sell to the U.S, market. Imports of other petroleum products into different regions of the country also rose. As illustrated by figure 6, U.S. imports of petroleum products surged in response to Hurricanes Katrina and Rita compared to levels during the same months of the previous year.[12]
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In addition to gasoline, kerosene-type jet fuel imports into the Gulf Coast surged to about 3.3 million barrels in October of 2005, compared to just 20,000 barrels in October 2004. Some countries that did not export significant quantities of this fuel in 2004 exported significant quantities following the hurricanes to the United States in 2005. For example, France exported 580,000 barrels of kerosene-type jet fuel to the United States in October 2005, but nothing in October 2004 or October 2006.
Source: GAO analysis of EIA data. Figure 6. Petroleum Product Imports into the United States, 2004-2006.
Our analysis of wholesale prices in the United States, Europe, and Asia shows that prices in geographically dispersed markets rose significantly following Hurricanes Katrina and Rita, indicating that prices in these markets are linked to some extent. Because imports surged from many countries in response to the resulting supply disruptions in the United States, gasoline prices around the world rose along with prices in the United States before prices eventually returned to pre-hurricane levels. Figure 7 illustrates the price spikes that occurred in late August and late September 2005 as a result of the severe damage to oil and gas production facilities in the Gulf of Mexico and to refineries and pipelines onshore from Hurricanes Katrina and Rita. The figure clearly shows that European and, to a lesser extent, Asian spot gasoline prices—wholesale prices for gasoline traded on a daily basis at major market centers—responded to the resulting petroleum product supply disruptions in the United States. The additional supplies to U.S. markets from Europe and elsewhere reduced prices in the United States, and spot prices everywhere declined to pre-hurricane levels before the middle of October.
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Source: GAO analysis of EIA data. Note: Breaks in lines represent days for which no data were recorded. Figure 7. Wholesale Gasoline Prices during the 2005 Hurricanes, 2005 – 2006.
While experts have stated that the availability of additional sources of petroleum product supplies has benefited the United States through lower and less volatile prices, and foreign gasoline supplies clearly helped reduce prices following Hurricanes Katrina and Rita, the fact that petroleum product markets are international means the United States will be exposed to supply disruptions or unexpected increases in demand anywhere in the world. Further, because some foreign suppliers are further away from the U.S. demand centers they serve than the relevant domestic supply center, the length of time it takes to get additional product to a demand center experiencing a supply shortfall may be longer than had the United States had more refining capacity. For example, imports of gasoline to the West Coast may come from as far away as Asia or the Middle East, and the transport time and therefore cost is greater. To the extent that imported gasoline or other petroleum products come from far away, the lengthening of the supply chain has implications for the ability to respond rapidly to domestic supply shortfalls. Specifically, if supplies to relieve a domestic regional supply shortfall must come from further away, the price increases associated with such shortfalls may be greater and/or last longer. In this sense, the West Coast is more vulnerable to price increases or volatility than is the Northeast, which can receive shipments of gasoline into New York Harbor or elsewhere in the U.S. Northeast from Europe, often on voyages of less than a week.
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Growth in International Trade of Petroleum Products is Expected to Continue but Growth in Biofuel use May Limit or Change the Patterns of Trade With demand for petroleum products growing globally, experts we spoke with believe the trade in petroleum products will continue to increase for a number of reasons. For example, global trends toward lower-sulfur fuels have resulted in more uniform sulfur specifications, creating more trade opportunities. Strong global demand for certain petroleum products— especially distillates such as diesel and jet fuel—will increase competition for, and facilitate global trade of, these petroleum products. For example, since 2005, diesel wholesale prices have generally been at a premium compared to the price of gasoline, in response to sharp consumer demand, and in the United States, diesel demand grew 6.9 percent in 2005, compared to 2.5 percent for gasoline. Demand for jet fuel is growing with the increase in air transportation, and given that jet fuel has uniform global specifications, jet fuel will continue to trade relatively freely based on global price signals. While many experts we spoke with believe that growth in international trade of petroleum products will likely continue, the planned expansion of the use of biofuels, such as ethanol made from corn or other crops, and biodiesel made from soybeans or other crops, in the United States and many other countries could reduce the growth of demand for petroleum products and thereby reduce the opportunity for trade. At the U.S. federal level, the EPA administers the Renewable Fuel Standard Program, which went into effect in 2007 and requires most U.S. gasoline refiners, importers and blenders to sell a minimum portion of biofuels each year. Refiners can meet the standard by blending biofuels with conventional gasoline or diesel in various proportions. Plans and mandates in a number of countries and regions, including the United States to introduce larger volumes of biofuels, primarily as additives to gasoline or diesel, could displace demand for and trade in petroleum products. In addition and as discussed previously in this report, some of these biofuel policies mandate that all gasoline or diesel sold in an area be blended in specific proportions with biofuels, with differences across states in the timing and level of such blending. Still other states specify a certain proportion of biofuels to be blended but allow flexibility in how they are blended, thereby creating the potential for widely different biofuel blended fuels within even a single state—for example, the mandated biofuel requirement could be met by a uniform proportion of ethanol blended into every gallon of gasoline used in the state, or by using a small amount of E85 (fuel composed of 85 percent ethanol and 15 percent gasoline components) with ethanol blended into the rest of the gasoline, and any combination of blends and volumes that meets the overall requirements would also satisfy the mandate. States and localities have pursued such policies for a variety of reasons, including viewing biofuels as a means to boost farm economies by increasing demand for feedstock crops while also contributing to a cleaner environment.[13] However, the current absence of uniform standards for biofuels and varying plans by various countries and regions to blend different volumes of biofuels with petroleum-based gasoline and diesel could reduce the fungibility of these fuels and thereby reduce opportunities for trade.
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GLOBAL AND DOMESTIC REFINING CAPACITY HAVE NOT KEPT PACE WITH DEMAND, LEADING TO TIGHT DEMAND AND SUPPLY BALANCE AND RECENTLY CONTRIBUTING TO HIGHER PETROLEUM PRODUCT PRICES For most of the past 25 years, there has been excess refining capacity globally, but this excess capacity has been reduced over time as demand has increased faster than capacity has grown. Capacity growth has lagged behind demand for a number of reasons, including low profitability in the refining sector and demands on industry to meet changing fuel specifications and reduce emissions of environmental pollutants. More recently, unexpectedly rapid growth in demand for petroleum products caused refineries to run closer to their production capacity. Current market tightness has contributed to higher and more volatile prices and increased profits in the refining industry. While these higher profits have encouraged increased investments in refining capacity, it is unclear whether or for how long the current market tightness will continue. This uncertainty is, in part, because rising construction costs and uncertain future demand make it difficult to estimate how many of the planned refining projects will actually be completed and because biofuel initiatives in many countries could reduce demand for petroleum products while potentially requiring further refining investment to make and keep separate different gasoline and diesel specifications to be blended with ethanol and biodiesel.
Demand for Petroleum Products Has Grown More Quickly than has Refinery Capacity, Tightening the Supply and Demand Balance Worldwide For much of the past 25 years, demand for petroleum products in the United States and internationally has outpaced growth in refining capacity. Demand for petroleum products fell dramatically from 1978 to 1982, creating significant excess capacity—by 1983, almost 30 percent of U.S. and world refining capacity was idle. Demand for petroleum products began growing again around 1982, and this demand growth, along with the shutting down of some idle refining capacity, began to narrow the gap between capacity and demand. Since that time, growth in demand for petroleum products has generally exceeded growth in refinery capacity, causing refineries to run more intensively to meet demand. Figure 8 shows how refinery utilization in the United States and internationally, with a few exceptions, including the countries of the former Soviet Union, has increased significantly since the early 1980s. Refining capacity in the United States has been growing since 1994 through expansions at existing refineries. The last major complex refinery on a new, or “green field” site in the United States was built in the 1970s, and many, mostly smaller, refineries were shut down starting in the early 1980s. However, as figure 9 shows, even as the number of refineries in the United States fell since 1981, refiners have since 1994 generally expanded total capacity at remaining facilities. Capacity expanded by an annual average of 192,000 barrels per day between 1994 and 2006—more than the average-sized refinery in 2006, which had a capacity of 116,000 barrels per day. For example, ExxonMobil’s Baytown refinery grew by about 166,000 barrels per day in capacity between 1994 and 2006, more than equivalent to adding a new refinery. In this sense, it is potentially misleading to say that no new refineries have been
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built in the United States since the 1970s. Instead, experts have said that expansion in the United States has centered at existing facilities because such expansion is less expensive than building an entirely new refinery at a new, “green field” site because of lower construction, permitting, and land acquisition costs. Some industry officials we spoke with said that construction at a green field site can be about two to three times more expensive than expanding capacity at existing sites on a per barrel basis.
Source: GAO analysis of BP Statistical Review of World Energy June 2007. Figure 8. Refinery Utilization in the World and Selected Countries, 1980-2006.
Source: GAO analysis of EIA data. Figure 9. U.S. Crude Oil and Petroleum Product Consumption and Number and Capacity of Operable Refineries, 1973 – 2006.
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Figure 10 shows how much of the recent growth in refining capacity in the United States has been concentrated in the Gulf Coast. This growth in capacity in the Gulf Coast is consistent with the view of many industry experts we spoke with that the Gulf Coast provides one of the most competitive environments for U.S. refiners. Experts cited several factors, including ready access to imported crude oil supplies, numerous options for shipping product to the rest of the United States by pipeline and waterways, and a concentration of highly skilled workers. U.S. refineries also have invested in equipment to upgrade their refineries to be able to produce more high-value products from a wider variety of raw inputs. For example, hydrocracking equipment enables refiners to adjust the yields of various products, and coking capacity allows refiners to process heavier crude oils. Figure 11 shows how the capacity of such downstream units, particularly hydrocracking and coking, has grown faster than distillation capacity overall. The addition of such downstream units does not increase the distillation capacity of refineries—the traditional measure of capacity—but enables refineries to produce a greater portion of products in high demand (such as gasoline, diesel, and jet fuel) and also to process more heavy and sour crude inputs. In fact, the proportion of gasoline, diesel fuel and jet fuel produced per barrel of crude input in the United States has increased from 77 percent in 1993 to 81 percent in 2005 even as the quality of crude oil inputs used has deteriorated.
Source: GAO analysis of EIA data. Figure 10. Refinery Capacity by U.S. Region, 1985-2006.
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Source: GAO analysis of EIA data. Figure 11. U.S. Refinery Distillation Capacity and Capacity of Selected Downstream Units, 1982-2006.
Industry officials and experts we spoke with said that several factors have caused refinery capacity to grow more slowly than demand in the United States. First, industry officials and experts said that refining has been a low-, even negative-return business for much of the past two decades, with profits too low to encourage significant expansion. Companies in the oil industry overall, which includes upstream oil exploration and production activities as well as downstream refining and retail marketing, have in general performed better than some industries and worse than others. However, according to an analysis by Deutsche Bank, cash returns on investment for oil companies in the Standard and Poor’s 500 index were less than the cost of capital from 1986 to 2000. In other words, it cost companies more to raise the money to invest than those investments earned. Within the oil industry, the refining segment has been less profitable than other lines of business in the petroleum industry, according to EIA data, as illustrated in figure 12. Except for a few years since 1977, returns for U.S. refining and marketing operations have been lower than returns in foreign refining and marketing and lower than exploration and production. Specifically, during the entire period 1977-2005, average return on investment for the U.S. refining industry was 7 percent, compared to 9 percent for foreign refining and slightly over 10 percent for all other lines of business. For the integrated oil companies that still control a major portion of the nation’s refining capacity, U.S. refining must compete with foreign refining and upstream investment options for capital. The lower returns for U.S. refining can make it harder for companies to justify expanding U.S. refining capacity.
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Source: GAO analysis of EIA data. Note: This graphic is based on the performance of major energy producers covered by EIA’s Financial Reporting System (FRS). These companies represented about 81 percent of U.S. refining capacity in 2005. Figure 12. Return on Investment in U.S. and Foreign Refining Compared to Other Lines of Business for Major Energy Producers, 1997 – 2005.
Another indication that the refinery industry has long had low expectations of profitability is that existing refinery capacity has sold very cheaply. U.S. refineries have often sold for significantly less than what it would cost to build a new similar refinery. According to an analysis by the National Petroleum Council of the value of existing refinery purchases between 1998 and 2004, refineries sold for about one-fourth to one-third the cost of equivalent new construction. The cost of buying an existing refinery was also less than the general cost of expanding capacity on an existing refining site, which experts indicated could be less than one-half the cost of new construction. This suggests that refiners have had low expectations of future returns in the U.S. refining market. This also indicates that until recently, a refiner looking to expand capacity in the United States may have been able to do so more affordably by purchasing an existing refinery. This would add to that refiner’s capacity, but would not expand domestic refinery capacity overall. A second reason experts cited for slow domestic refinery capacity growth is that more rigorous product specifications; the proliferation of special gasoline blends, or “boutique fuels” around the country; and environmental controls have all required refineries to invest in additional processes in order to meet the specifications and regulations, and these investments did not typically add to base capacity. Officials we spoke with said that the large investments required to reduce harmful air emissions at refineries and meet more stringent product specifications drew from the capital that may otherwise have been available to invest in expanding capacity. A third reason for slow domestic refinery growth, according to some industry representatives, is that permitting difficulties have discouraged refinery expansions. Refineries are required to obtain permits from relevant state and local authorities in order to build or expand refinery capacity. These are often difficult to obtain owing to regulatory
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hurdles and public opposition. Other experts suggested that permitting adds to the difficulty of expanding capacity but has been a less important factor than overall low expectations of returns. DOE officials told us that resistance to refinery expansions by nearby communities could be a more important factor in discouraging new domestic refinery construction or expansions. Finally, EIA officials and others pointed to the surplus production of gasoline in Europe as a major, more recent, reason domestic refinery capacity has not kept up with domestic demand. They stated that Europe could at times provide gasoline to the Northeast more competitively than some Gulf Coast refiners, and therefore gasoline imported from Europe has displaced domestic supplies and discouraged domestic refinery expansions. More recently, global demand for gasoline, diesel, and jet fuel grew particularly quickly around 2004, partly as a result of rapid growth in China, where demand surged by over 15 percent. In order to increase production and meet this recent surge in demand for petroleum products, refiners have had to run their refineries even more intensively—capacity cannot be added quickly because of the long lead times involved in designing and constructing a refinery or an expansion project. Since 2004, world refinery utilization rates have risen to around 86 percent, the highest levels since 1980, when data first became available. Experts told us that many refineries have been running near their production capacity in order to meet demand. This is particularly true in the United States and Europe, where refineries have been running at or near 90 percent utilization since the 1990s, even though spare capacity still existed worldwide, particularly in the countries of the former Soviet Union and to a lesser extent in the Asia Pacific region.
Current Market Tightness has Contributed to Higher Petroleum Product Prices, Higher Price Volatility, and Higher Industry Profits The recent tightening of the balance between supply and demand for petroleum products has, along with higher crude oil prices and other factors, contributed to increased petroleum product prices and higher industry profits, and has contributed to greater price volatility. In addition, a tight demand and supply balance means less flexibility in industry’s response to unanticipated events. For example, at times of excess capacity, if a particular refinery were to unexpectedly shut down for emergency maintenance, capacity that wasn’t being used could be brought on line to meet demand. However, when refineries are generally running near capacity, there is less excess capacity to call on, and what available capacity there is tends to be located farther away from demand because the lower-cost and nearer refining capacity tends to be used up first. An analysis by the FTC illustrated the effects of tight refining capacity at the regional level. This analysis compared the impact on gasoline prices of two refinery outages in the upper Midwest in the spring and summer of 2001 with a major refinery outage in Oklahoma in July 2003. Each of the Midwest refinery failures was associated with wholesale gasoline price increases of between 30 and 40 cents.[14] By contrast, the Oklahoma refinery failure was found to have little effect on gasoline prices in that state. The FTC attributed the difference in the price responses to the fact that the upper Midwest region lacks sufficient refinery capacity to meet the region’s demand, while Oklahoma produces significantly more petroleum products than the state needs. Therefore, when a major disruption occurs, the upper
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Midwest must rely on supplies from distant refineries, while Oklahoma simply exports fewer petroleum products to other states. Further, as we have previously reported, the West Coast of the United States generally has higher gasoline prices than much of the rest of the country.[15] Among the reasons for these consistently higher gasoline prices are a tight supply and demand balance for gasoline, the fact that the region is isolated from other major domestic and foreign refining regions, and the adoption in California of a unique blend of gasoline that is more costly to make than many other blends and that is not routinely produced by many refineries outside the West Coast. Prices in the West Coast can rise rapidly in response to supply disruptions as a result of these factors. Profits in the refining industry have increased significantly since 2002, in part as a result of sustained market tightness and, in the United States, owing to wide price differentials between heavy and light crude oils. For example, the difference between crude oil input prices and petroleum product prices, a strong indicator of refining profits, has increased worldwide, though particularly in the United States. In the United States, these wide price spreads have caused returns on investments in the refining and marketing segment of the petroleum industry to reach record levels in 2004 and 2005, the latest data we were able to obtain. In the United States, these higher margins are, in part, the result of the ability of U.S. refineries to take advantage of low-price, low-quality crude oil inputs. Sophisticated U.S. refineries are able to convert large quantities of low-quality crude oil inputs into highervalued products, while refineries in the rest of the world do not have such capacity to the same extent. Shifts in global crude oil production and demand have contributed to a glut of such low-quality oils, lowering their price relative to higher-quality crude oils and improving the position of U.S. refineries relative to that of their international competitors.
Increased Profit Margins have Led to More Investment, but Future Market Tightness Will Depend on Several Factors Currently high petroleum product prices and high profits in the refining industry have spurred new refinery capacity investments in the United States and internationally. Global investment in refining has increased in recent years. According to IEA data, capital spending grew from $34 billion in 2000 to $51 billion in 2005 and is expected to average $60 billion per year between 2006 and 2010. Analysis by IEA of plans and projects currently underway worldwide suggest that almost 10.5 million barrels per day of capacity may be added through 2011. This rate of refinery capacity growth is somewhat higher than expected demand growth, which is projected to grow by about 9.2 million barrels per day by 2011. The majority of this capacity expansion is expected to take place overseas, especially in China, India, and the Middle East. In the United States, EIA officials have said that announced investments through 2011 could add an additional 1 million barrels per day to domestic refinery distillation capacity, along with significant additions to downstream processing capacity. If realized, these domestic and international investments could help alleviate the tight balance between refining supply and demand. However, since tight refining capacity is just one of a number of factors affecting prices, the biggest factor being crude oil prices, even a less tight refining market may not bring much price relief at the gasoline pump.
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While recent profits and prices have renewed interest in expanding refining capacity, experts said it is unclear whether or for how long current refining market tightness will continue. Future refining market tightness depends on changes in refining capacity and on changes in the demand for petroleum products. Industry officials and experts we spoke with said future conditions are highly uncertain for several reasons: •
•
•
•
It has become much more costly to expand refinery capacity in recent years due to rapidly rising construction costs. Various construction materials such as iron, steel, and concrete are important in energy projects, and their costs have increased significantly. For example, while prices for iron and steel fell in the decades prior to 2002, prices increased by 9 percent annually between 2002 and 2004, and by 31 percent from 2004 to 2005. Similarly, industry officials said that many decades of low investment levels have led to a small pool of qualified project engineers to design and oversee construction and expansion projects, causing labor prices to soar. Moreover, the Nelson-Farrar refinery construction cost index, which tracks prices for materials such as iron and steel, equipment and skilled and unskilled labor, shows that costs for refinery investment rose by 17 percent from 2002 to 2005 in real terms. Industry officials indicated that these cost estimates did not capture the full extent to which refinery expansion costs have increased. Officials also said that the waiting lists to purchase key refinery equipment are getting longer. In the United States and in Europe, some planned refining expansions have been delayed or canceled, in part because of these rising costs and delays in acquiring equipment and skilled labor. Uncertainty about future demand makes refinery investments risky and may inhibit investments. The United States is considered a mature market, with demand for motor gasoline forecast by EIA to grow by 1.2 percent annually between 2005 and 2030. Meanwhile, refinery capacity has on average expanded by almost 1 percent annually since 1999. Some industry officials we spoke with believe that U.S. demand for petroleum products will peak in the next decade and then begin to decline, implying only a temporary need for additional refining capacity. Company representatives told us that various proposals under consideration dampen the U.S. refining investment climate. For example, the Administration has proposed to reduce U.S. petroleum gasoline consumption by 20 percent by 2017 through increased use of biofuels and more stringent automobile fuel economy standards. If achieved, this could turn the United States from a gasoline importer to a net exporter within 10 years; and current refining capacity could meet future demand even without expansions that are currently planned. Similar initiatives to blend large volumes of biofuels into the transportation fuels markets in other countries could similarly displace demand for petroleum products. It is unclear whether such initiatives could ease the demand and supply tightness that currently exists. On the one hand, reducing demand growth can reduce pressure on refinery capacity. On the other hand, reduced expectations of future demand can alter the attractiveness of refinery investments, and some refiners may respond by cutting back refinery expansion plans. New initiatives to blend biofuels in varying proportions into transportation fuels could potentially add to the need for further refining investments both to refine and to keep separate new blending stocks, possibly absorbing resources that could have
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been used to expand capacity. Automobile industry experts we spoke with agreed that each different ethanol blend requires a specific gasoline or diesel blend stock in order for the resulting blended fuel to meet performance and emissions standards. In other words, the gasoline that is blended with ethanol to make E10 (10 percent ethanol) is different than the gasoline used to make E85 (85 percent ethanol). The absence of national standards for blending biofuels with gasoline and diesel could also increase the number of gasoline and diesel blending stocks refiners have to make, and could lead to a proliferation of new blendstocks. Further, to the extent that new equipment is needed at refineries in order to produce, handle, or keep separate these various blendstocks, refineries will need to invest in this equipment in order to meet various federal, state, and local biofuel mandates and standards. These added investments could crowd out resources that could otherwise have gone to expanding refinery capacity.
DOMESTIC AND OECD INVENTORIES OF PETROLEUM PRODUCTS AND CRUDE OIL HAVE DECLINED RELATIVE TO DEMAND, WITH MIXED EFFECTS ON PRICES AND PRICE VOLATILITY When measured as average days of consumption, long-term trends in inventories of petroleum products and crude oil in the United States indicate a general decline over the past 20 years. Similarly, gasoline and crude oil inventories in OECD countries excluding the United States have also generally fallen over the same period. However, there are limitations to inventory data as measured by EIA and IEA, in part because these data do not fully match stocks with their intended markets; in general petroleum product exporting regions will typically have large stocks of these products relative to that region’s demand, while inventories held in net importing regions will typically be lower relative to demand. For example, petroleum products stocks of gasoline in Canada, Europe, and the Caribbean that are destined for the United States are counted as inventories in those countries but not as inventories in the United States. A number of factors have contributed to the long-term decrease in inventory holdings in the United States, including reductions in domestic crude oil production and in the number of refineries as well as advances in technology and management processes that allowed for reduced inventories and a concomitant reduction in operating costs. Lower operating costs associated with lower inventories may have translated into lower consumer prices during normal periods. However, in the short term, inventory levels tend to fluctuate within a “normal” range, and—since inventories provide a smoothing effect against temporary demand and supply fluctuations—lower than normal inventories can lead to higher prices in the event of supply disruptions or surges in demand.
Inventory Levels of Petroleum Products in the United States and Other OECD Countries have Generally Fallen over the Past Two Decades Privately held inventories of petroleum products and crude oil in the United States have generally fallen over the past two decades, in terms of average number of days worth of
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supply, or “days forward cover.”[16] Specifically, as illustrated in figure 13, days forward cover for gasoline in the United States averaged about 30 days in 1984 but fell to an average of about 12 days for the first 5 months of 2007. Similarly, crude oil days forward cover fell from about 29 to about 22 days, and jet fuel and diesel fuel days forward cover also fell over the same period.
Source: GAO analysis of EIA data (annual average of monthly data). Figure 13. Crude Oil (Excluding Strategic Reserves), Finished Motor Gasoline, Kerosene-type Jet Fuel and Diesel Fuel Days Forward Cover in the United States, 1984 – 2007.
Other OECD countries have also generally seen a reduction in days forward cover for motor gasoline. Figure 14 shows the general downward trends in gasoline days forward cover for the OECD regions of Europe, Pacific, and North America excluding the United States. Specifically, European stocks declined from about 50 days in 1984 to about 40 days in 2001, before increasing to almost 46 days on average for the first 5 months of 2007. The much larger inventory figure for Europe compared to that for the United States reflects the fact that the inventory data include strategic stocks of gasoline held by some private companies.[17] The recent increase in European stocks of gasoline coincides with a period in which demand for gasoline fell in Europe relative to supply, and exports of gasoline to the United States increased a great deal. Figure 14 also shows large reductions in gasoline stocks in North America, excluding the United States, from about 44 to 18 days forward cover over the same time period, while stocks in Pacific OECD countries fell more modestly from 20 to almost 16 days. Crude oil stocks in two of the three other OECD regions, Europe and Pacific, decreased over the period, while stocks in North America excluding the United States rose significantly, driven in part by increases in Canadian oil sands production and the storage and delivery infrastructure associated with this increased production. Figure 15 illustrates these changes in crude oil inventories in days forward cover. We do not have inventory data for non-OECD countries. However, as with petroleum products, net crude oil exporting countries would be expected to have much higher levels of days forward cover for crude oil than net importing countries, especially if strategic stocks are excluded.
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Source: GAO analysis of IEA data (annual average of quarterly and monthly data). Figure 14. Motor Gasoline Days Forward Cover, by OECD Region, 1984-2007.
Source: GAO analysis of IEA data (annual average of quarterly and monthly data). Figure 15. Crude Oil Days Forward Cover, by OECD Region, 1984 – 2007.
Inventories, as measured by IEA, EIA, and others, have some limitations as a measure of what is available to meet demand in the event of a supply shortfall. For example, as discussed above, the United States has imported an increasing share of its gasoline over the period during which inventories have fallen, and as such, the domestic inventory data do not account for large volumes of these products on the water in tankers from foreign sources that are destined for the U.S. market or in storage terminals at foreign ports serving this trade in gasoline. Our analysis indicates that about 16 million barrels of gasoline and gasolineblending components were en route to the United States on the average day during 2006,
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representing about an additional 2 days of forward cover, and an unknown additional amount is held in storage terminals that would be available for shipment in the event of a supply shortfall in the United States. Data on U.S. gasoline inventories may further under-represent available inventories if we ignore the part of inventories held at foreign refineries that are intended to serve the U.S. petroleum products market. The inventories represented in these refineries’ storage systems and in the tanker and pipeline system supporting the flow of products to the United States, or at least some portion, could be considered part of U.S. inventories for the purpose of evaluating our days forward cover of products in the event of a supply disruption. However, it would be difficult to estimate the precise volumes of these foreign inventories as we do not collect such data from offshore suppliers and because many of these inventories are at varying distances from U.S. markets and would have to be evaluated differently, depending on how long they would take to reach the United States in the event of a domestic supply shortfall.[18] Another limitation in interpreting inventory data arises because much of the measured volumes of petroleum products in pipelines cannot be effectively removed from the pipelines in the event of a supply shortfall because they are needed to keep the pressure in the pipelines at operable levels. Similarly, some inventories are in so-called “tank bottoms,” or the part of storage tanks that cannot effectively be retrieved in the event of a supply shortfall. As a result of these and other limitations, we do not have an accurate measure of precisely how much is in the full supply chain to the United States, or the actual number of days’ worth of usable supply we could rely on in the event of a supply disruption. Looking forward, the refining expansions discussed previously in this report may lead to increases in the days forward cover measure as pipelines and storage facilities associated with the new refining capacity add to inventory holdings. However, any increase in days forward cover is likely to be modest overall because demand is also projected to grow, and companies continue to strive to develop more efficient inventory holding practices and reduce costs associated with holding any excess inventory.
A Number of Factors Have Contributed to the Long-Term Decrease in Inventory Levels Since 1980 A number of factors have contributed to the long-term decrease in U.S. days forward cover. These factors include (1) a reduction in the number of refineries and falling domestic crude oil production, (2) the fact that demand has been rising faster than refining capacity for much of the past 20 years, (3) gains in technological and management efficiency that have allowed companies to reduce the level of operating inventories, and (4) the rise of futures markets for crude oil and gasoline that have enabled oil companies and others to reduce exposure to market risk by holding financial as well as physical stocks of these commodities.[19] In the United States the decline in U.S. crude oil production resulted in decreased inventory in gathering pipelines and storage infrastructure, as pipelines and storage tanks were decommissioned. This decline in production-related inventories could be quite significant, although we do not have data to measure it directly. Oil production in the United States peaked in 1970 at around 10 million barrels per day, but by 2005 had fallen to less than 6 million barrels per day. This decline in production has left a number of abandoned crude oil
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pipelines and therefore represents a reduction in measured inventories. Similarly, the closure of many small refineries and the decommissioning of these refineries’ storage and pipeline connections to the greater supply infrastructure also reduced inventories held at these facilities and in the pipeline connections. As discussed previously in this report, this reduction in the number of refineries was significant. For example, in 1980, there were well over 300 refineries in the United States, while in 2006 the number was about 150. This sheer drop in numbers probably overstates the drop in associated inventories because, while the number of refineries fell, the average size of refineries rose, both because it was smaller refineries that tended to be shut down and because many of the remaining refineries expanded their capacity significantly. Nonetheless, EIA has stated that refinery closures had an important impact on petroleum stocks prior to 1995. A related cause of the reduction in days forward cover for petroleum products has been the fact that for much of the past 20 years, demand for these products has risen faster than domestic refining capacity. Because days forward cover is measured as the number of days’ worth of demand that is in the domestic supply chain, any increase in demand that is not met by a commensurate increase in domestic supply will lead to a reduction in days forward cover. However, as discussed previously in this report, this is potentially misleading because the supply chain between foreign refiners and the United States is relevant for measuring actual days forward cover and the U.S. imports of gasoline have been increasing dramatically over the past decade, and imports of crude oil have been increasing for much longer than that. According to company representatives and industry experts we spoke with, as well as the National Petroleum Council, delivery system efficiency improvements have also resulted in reduced crude oil inventory levels. Company representatives told us improved information technology has given managers better tools needed to optimize stock levels, and that this was mirrored in many other industries over this same period, as improved logistics and management practices enabled companies to more closely track production and delivery. By reducing inventories, refiners were able to reduce their operating costs, providing incentives to invest in efficiency-improving measures. Some officials told us that low refining profit margins were a major driver in getting companies to reduce their inventory holdings. Finally, the relationship between the future price of crude oil and petroleum products and the amount of inventory stored has, at times, contributed to changes in overall inventory levels. For example, according to a 1997 EIA report, during the period between 1995 and 1996, the prevalence of instances where the current trading price of crude oil or petroleum products was higher than the future expected price appeared to be an important factor behind the reduction in stocks.[20] In such a price environment, oil companies and others could sell currently held inventories and buy futures contracts to meet their future expected needs. In recent years, the future price of crude oil has most frequently been higher than the current price, and industry officials told us that this has been a factor in explaining why absolute inventory levels increased between December 2004 and early 2007. For example, total U.S. crude oil stocks, excluding strategic stocks, were about 355 million barrels in June 2007, or about 31 percent higher than in January 2004, according to EIA data.
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Long-Term Inventory Cost Reductions have Likely Reduced Prices of Gasoline and Other Petroleum Products, but, in the Short Term, Reductions in Inventory Levels below Normal Ranges Can Lead to Higher Prices during Supply Shortfalls To the extent that improved technology and inventory management over the long term have resulted in lower operating costs, some of the savings may have been passed on to consumers in the form of lower prices. We found no consensus among industry experts about the extent of such price reductions, nor any empirical analyses that would quantify the savings to consumers from lower inventory holding costs. However, because refineries compete with one another to sell their products, they would likely be forced to pass on some savings in operating costs in order to remain in operation, especially during that portion of the last three decades in which there was unused refining capacity as well as during recent years when surplus gasoline production in Europe has increasingly found its way to U.S. markets. However, because inventories provide a smoothing effect against temporary demand and supply fluctuations, lower than normal inventories can signal underlying changes in supply and demand conditions that will cause prices to rise. For example, if a large refinery in the United States were to suffer an unexpected outage, the resulting reduction in domestic supplies would likely result in a drawdown of that refinery’s inventories to meet its demand, and if that is insufficient, the refinery would buy from other refiners. If inventories were on the high end of the normal range, such a disruption would likely have little effect on petroleum product prices, all else remaining the same. On the other hand, if inventories were on the low side of or below the normal range—the result of other supply shortfalls or unexpectedly high demand—the additional refinery outage would be more likely to cause significant price increases. The size of the supply disruption relative to available inventories, as well as to the size of the refining sector, can also influence how prices respond. For example, if a large refinery outage were to occur in the Gulf Coast refining region, the large volume of inventories and the large number and capacity of other refiners relative to that refinery’s production would likely mean that the effect on prices of petroleum products would be small. Similarly, the availability of large stocks of gasoline in Europe, often less than 1 week away by tanker to the U.S. East Coast market, probably insulates the latter market from extreme price fluctuations in the event of a domestic supply shortfall. On the other hand, if the refinery outage were to occur in the West Coast, where one refinery’s production would be significantly larger relative to available inventories and total sector capacity, a significant price response is more likely. For these reasons, lower than normal inventories are frequently cited as a factor in price run-ups of petroleum products. For example, the Northeast diesel price spike of January 2000 was preceded by lower than normal inventory buildup, and the California Energy Commission cited relatively low inventory levels as one of several contributing factors to the gasoline price spike in the spring of 2006.
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U.S. SUPPLY INFRASTRUCTURE IS CONSTRAINED IN KEY AREAS AND LIKELY TO BECOME INCREASINGLY CONSTRAINED, THEREBY INCREASING PRICES AND PRICE VOLATILITY UNLESS TIMELY INVESTMENTS ARE MADE The nation’s crude oil and petroleum product supply infrastructure is constrained in key areas and may become inadequate to handle future volumes of petroleum products and biofuels unless sufficient investment is undertaken. Inadequate supply infrastructure can lead to higher prices and price volatility during supply disruptions or unexpected increases in demand because the supply infrastructure cannot handle the changed or increased delivery of fuels. However, the extent of the problem and the prospect for the future of the supply infrastructure is uncertain, in part because there has been no comprehensive study done to assess infrastructure adequacy. There are many planned infrastructure expansions that could alleviate the stress on the system to some extent. However, a complex approval process— involving numerous federal, state, and private entities—and other factors increase the time and cost of building and maintaining infrastructure.
The Nation’s Supply Infrastructure is Constrained in Key Areas and Likely to Become More Constrained Industry and agency officials report that key crude and petroleum product pipelines are constrained and operating at or near capacity. As the Secretary of Energy noted in a December 4, 2007 discussion with industry media, the U.S. energy infrastructure system— including oil pipelines—is “pressed,” and it is important that pipeline and other energy infrastructure owners maintain their assets effectively, to maintain adequate supplies. Both DOT and industry officials report a systemic lack of pipeline capacity in the supply infrastructure system in key states including Arizona, California, Colorado, and Nevada, and note existing pipeline supply infrastructure is insufficient to carry the commensurate volumes of petroleum products and crude oil needed to meet growing demand. Industry officials told us that pipelines in the Southwestern region, such as Arizona and Las Vegas, have reached maximum utilization, or become “constrained.” For example, industry experts told us that a new petroleum product pipeline from the Gulf of Mexico to El Paso is already approaching full capacity. Denver’s petroleum product pipelines have also become generally constrained and unable to meet increased gasoline demand for summer travel. This raises the cost of delivering petroleum products to Denver; in instances when pipelines are full, shippers must make alternate shipping arrangements by more costly rail or truck. Further, a key petroleum product line from the U.S. Gulf Coast to North Carolina is reportedly constrained, thereby increasing delivery costs for petroleum products in that region, and key petroleum product pipelines radiating outward from the major refining center of Houston are also reportedly constrained. Finally, in certain areas, pipeline infrastructure to support certain demand or production centers’ needs does not exist. For example, there are no petroleum product pipelines into Florida. Additionally, despite strong demand in California, the existing petroleum product pipelines support the flow of product from California to other Southwestern states, but no petroleum pipelines flow into California from other regions.
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Industry representatives and federal studies also report that many of the nation’s port facilities are operating at or near capacity. For example, one-fourth of the ports in a U.S. Maritime Administration (MARAD) survey described their infrastructure impediments as “severe.” Officials from the interagency U. S. Committee on the Maritime Transportation System, which includes MARAD, the National Oceanic and Atmospheric Administration, and the U.S. Army Corps of Engineers told us that U.S. ports and waterways are constrained in capacity and utilization, and anticipate marine supply infrastructure will become more constrained in the future. The Ports of Los Angeles, Long Beach, Oakland, Houston, Savannah, and Charleston reported congestion and emphasized in a 2005 report that they are experiencing higher than projected growth levels. The capacity of the supply infrastructure not keeping pace with increasing demand in certain areas has raised concerns about the adequacy of the infrastructure to accommodate expected increasing volumes of crude oil and petroleum products. Population increases in the West and South are expected to increase the need for pipelines, marine transportation, and capacity utilization there. DOT reports that already high pipeline capacity utilization levels may not meet growing demands unless significant expansion occurs. The situation is similar for the U.S. marine infrastructure. In a 2005 report, MARAD evaluated the status of U.S. ports and waterways and concluded that domestic marine transport supply infrastructure will become more constrained in the future. As imports of petroleum products are projected to increase by over 80 percent by volume between 2004 and 2030, according to EIA, this anticipated demand growth will challenge a marine transport system that is already operating, in some instances, at the limits of its capacity. The introduction of biofuels will also increase the strain on the existing supply infrastructure. For example, ethanol-producing plants tend to be relatively small near the sources of biofeedstocks—currently mostly corn—used to make ethanol. At present, the ethanol produced by these plants, unless they are located next to rail facilities, are typically trucked to central rail loading facilities and then shipped to demand regions on unit trains— trains whose cars are entirely made up of a single product and typically going to a single destination. Trucking biofuels to these central locations is costly and also uses petroleum products, thereby reducing the volumes of these latter fuels the ethanol can displace. Experts we spoke with generally agreed that eventually a more efficient collection system will likely be built—probably consisting of feeder pipelines—to connect the relatively small ethanol plants to major rail or supply and demand centers. Nonetheless, according to DOE, the existing petroleum product pipelines are currently not configured to transport ethanol from regions where it is currently produced to regions where it is consumed. Because pipelines are ultimately the cheapest form of domestic shipment of petroleum products and crude oil, it may make sense to ultimately ship ethanol through the pipeline system, and existing or new petroleum pipelines could be used in certain areas to transport ethanol if ongoing efforts by operators to identify ways to modify their systems to make them compatible with ethanol or ethanol-blended gasoline are successful. In addition, as discussed previously in this report, a proliferation of biofuel blends in this country will require additional variations in the blends of petroleum products that are mixed with these biofuels. Pipeline companies report that varying fuel specifications complicate petroleum product delivery and supply infrastructure systems by requiring separate storage and increasing the complexity of the distribution system. Also, pipeline operators told us that sending more and smaller batches of these special blends has slowed the flow of fuels through
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pipelines because pulling off more and smaller batches of fuels requires a slower speed to not miss significant parts of these batches. However, when we asked, these pipeline operators did not offer any quantification of the extent to which effective tank capacity reduction or pipeline slowness has occurred.
Infrastructure Disruptions Lead to Increases in Prices and Price Volatility and Constraints in Supply Infrastructure Could Exacerbate Price Effects A constrained supply infrastructure can be a major factor influencing prices of petroleum products during supply disruptions. For example, during the rupture in the Kinder Morgan pipeline in Arizona in August 2003, Arizona’s gasoline prices rose by about 45 cents during the 3-week period ending on August 25, 2003. Due to the connectivity of the pipeline network among California, Arizona, and Nevada, the disruption not only caused prices to spike in Arizona itself, but the extra burden from Arizona’s demand also contributed to higher prices elsewhere in the West; during the disruption, California’s prices rose by 40 cents to peak at $2.10, and Washington, Nevada and Oregon all experienced price increases of over 30 cents per gallon.[21] Any constraint in the supply infrastructure can reduce supply reliability by making it more difficult to reallocate supplies in response to even relatively minor disruptions in the supply and distribution system. In this way, a constrained supply infrastructure could increase price volatility and exacerbate price effects due to disruptions. When certain localities are inadequately served by pipelines or reasonably priced marine supply infrastructure, alternative transport modes tend to be more costly, leading to higher prices for consumers. For example, since relatively few pipelines connect the West Coast with other regions, some supplies of petroleum products and crude oil must be shipped by truck or barge from other domestic regions or by tanker from foreign countries; such modes of transport are slower and more costly than via pipelines. For example, it can take around 2 weeks for a vessel to travel from the Gulf Coast to Los Angeles port—including transit time through the Panama Canal. This can increase recovery time from an unplanned refinery outage, other supply disruption, or an unanticipated surge in demand, thereby leading to higher or longer-lasting price spikes. Federal agency officials and industry experts told us that the slow permitting process and corresponding delays in infrastructure development could lead to higher and more volatile petroleum product prices in the future. For example, while the recent expansion of pipeline capacity from the Gulf Coast to El Paso, following the opening of the Longhorn pipeline in June 2004, has been expected to ease the infrastructure constraint on Arizona’s petroleum product supplies, permitting impediments continue to perpetuate the lag between the growth of demand for petroleum products on the West Coast on the one hand and the growth of the pipeline capacity to move products to the region on the other. The California Energy Commission has recently stated that similar constraints on marine infrastructure expansions to accommodate future growth in demand for imports of petroleum products will be a major challenge for the West Coast. Such failure of the region’s supply infrastructure to handle the requisite volumes of petroleum products to meet rising demand will continue to contribute to the persistence of higher and more volatile prices in the West Coast compared to other regions.
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We were unable to assess the extent of supply infrastructure constraints or the impacts of these constraints on prices and price volatility, in large part because there is no central source of data that tracks system bottlenecks. Information that would indicate whether a pipeline is operating at or near capacity is also not collected in a central location by federal agencies or industry trade groups. These data would include pipeline throughputs, measured by the amount of product flowing into a pipeline and the volume of output received at key market locations. Companies are not required to report such information. By contrast, FERC requires natural gas pipelines to report, via their web sites, throughput information that allows regulatory, public, and private entities to track bottlenecks and identify where shortages in supply, or system constraints, affect regional prices. A number of studies and analyses of constraints in natural gas pipelines have quantified the effects on natural gas prices. For example, EIA routinely uses natural gas pipeline capacity and outages in making projections about natural gas prices. These data on natural gas pipeline capacity and the flow of natural gas are collected and evaluated to determine the reliability of the infrastructure to meet demand, and it is well understood that constrained pipelines lead to higher natural gas prices and can even lead to disruptions of service in severely constrained cases.[22] We recognize there are differences between the natural gas industry on one hand and the petroleum industry on the other, particularly because of the fact that the former industry evolved under a rate-regulated utility framework, while the petroleum industry did not. Specifically, under rate regulation, the former requirement that utilities meet all demand at their regulated prices at any point in time necessitated the monitoring of supply and infrastructure constraints that could cause a failure of service. By contrast, petroleum product prices have largely not been regulated, and prices have generally been allowed to adjust to equilibrate supply with demand at any point in time. Further, we are not suggesting in this report that petroleum product markets should be regulated like natural gas or any other markets. However, these historical regulatory differences notwithstanding, we believe that it is important to understand the extent to which constraints on the current petroleum product supply infrastructure affect prices as well as the adequacy of the infrastructure to meet growing demand. Federal agencies, industry experts, and Congress have all recognized this as a priority. For example, industry consultants and agency officials have acknowledged the importance of a system-wide study of pipeline capacity constraints and regulatory impediments to future investment. In addition, DOT officials have stated that the extent of capacity restrictions in the nation’s pipeline infrastructure is becoming more apparent, that the current regulatory mechanisms may not lead to appropriate reinvestment in the industry. In June 2006, DOT put forth a proposal and in December 2006 Congress passed legislation that mandated the Secretaries of Energy and Transportation to conduct periodic analyses of the adequacy of the nation’s pipeline supply infrastructure. The first report to Congress of the results of such an analysis is required by June 2008.[23] The language for the mandate stated that “such analyses should identify areas of the United States where unplanned loss of individual pipeline facilities may cause shortages of petroleum products or price disruptions and where shortages of pipeline capacity and reliability concerns may have or are anticipated to contribute to shortages of petroleum products or price disruptions. Upon identifying such areas, the Secretaries may determine if the current level of regulation is sufficient to minimize the potential for unplanned losses of pipeline capacity.” Despite widespread recognition that such a study is needed to fully identify the extent of infrastructure inadequacy and the impact on prices, to date, no such analysis has been undertaken. DOT and DOE officials told us that
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they were not appropriated funds specifically to do the mandated analyses and that the agencies have not re-allocated other funds for this, although DOE told us in its comments that DOE and DOT staff have met to discuss how this work could be approached. Given that the study has not begun, it seems highly unlikely that the agencies will be able to meet their June 2008 deadline for reporting to Congress.
Expansions in Supply Infrastructure Are Planned, but High Construction Costs, Investment Risk, and a Complex Regulatory Environment Can Deter or Delay These Needed Infrastructure Investments There are many private sector plans to expand the supply infrastructure, and if implemented in timely fashion, these plans could significantly alleviate the stresses on the system. For example, there is a long-anticipated project for a 500-mile petroleum product pipeline expansion from Louisiana to Georgia, several plans for new crude pipelines to accommodate the expected increased flows of Canadian oil sands, as well as other crude and refined product pipeline plans to meet more localized needs. However, many such plans are in a conceptual stage and/or subject to permitting approval and other possible complications. Thus, industry representatives told us, it is difficult to determine how many of the industry plans for new construction or expansion of existing pipelines will be realized. However, the high cost of construction, uncertain investment climate, and complex regulatory environment increase the time it takes to build this supply infrastructure and raises risk and investment costs. With regard to construction costs, a shortage of skilled labor and specialized equipment to perform the work, and high prices of steel and concrete have increased construction costs and the time it takes to expand the nation’s supply infrastructure system. For example, pipeline companies and other industry experts we spoke with said that major pipeline expansion and construction projects take anywhere from 2 to 15 years to complete and currently cost about $1 million per mile to build. With regard to the uncertain investment climate, pipeline companies and industry experts told us that uncertainty about petroleum product demand, biofuel development and shipping, and future changes to fuel specifications complicate the decisions about where and when to build new or expand existing infrastructure. Regulations governing pipeline and other infrastructure expansions, including regulations governing water and air pollution, endangered species protection, and public safety, have evolved to protect the environment and ensure public safety. However, there can be tension between these goals and the goals of ensuring adequate energy supplies and keeping prices down. For example, in order to build a new pipeline or significantly expand capacity or upgrade an existing pipeline, companies must first navigate a mixed and sometimes complex jurisdiction of federal, state, and local regulators, as well as secure right of way approval from the necessary landowners whose lands will be crossed by the pipeline. At the federal level alone, as many as 11 agencies may be involved in granting approval to build new pipeline projects. In addition, industry experts told us that some potential market entrants have had difficulty meeting permitting requirements and are often unable or unwilling to wait out lengthy delays in obtaining permits, such as when two companies in southern California reportedly recently backed out of plans to build storage terminals there after trying to complete the federal, state and local approval processes. A study conducted for Association of Oil Pipe Lines, an FTC report on gasoline prices, and industry officials told us
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that building or expanding pipelines has become increasingly difficult in certain situations. For example, a major pipeline operator encountered federal and local legal and regulatory issues that delayed for 10 years the development of a key pipeline from the Gulf Coast to El Paso, Texas. As a result of such delays and impediments to investment, regional demand that could support new pipeline capacity must be served by more costly transportation modes for years, as has been the case in parts of the Rocky Mountains and Southwest and West Coast regions. Finally, an uneven balance of costs and benefits of expansion for various entities can also contribute to declining investment in supply infrastructure by certain entities. For example, DOT reports that common carrier pipelines achieve only modest returns from relieving constrained pipeline capacity. However, it reports consumers would benefit proportionately greater through the enhanced competition resulting from the increased capacity of new pipeline investments. Pipeline companies, on the other hand, report they will expand when sufficient demand is secured, particularly through the “presale” of capacity in the proposed pipeline. Ideally, the permitting and approval process should be streamlined without sacrificing the important protections provided by regulatory oversight. Industry and federal agency officials have pointed out that a federal model exists for this in the permitting process for interstate natural gas pipelines. Specifically, FERC facilitates expansions and construction of natural gas pipelines by serving as the lead agency to process company permit applications, conduct the required environmental impact study, and coordinate the timing of other necessary permits that fall under the purview of various federal agencies. In addition, FERC authorizations convey the right of eminent domain to pipeline builders to resolve specific right of way issues in the event an agreement cannot be reached between a landowner and a project sponsor. FERC officials told us that although its authorizations convey the right of eminent domain, pipeline companies rarely have to exercise it because its existence is usually sufficient to get landowners to negotiate a solution with pipeline builders. Streamlining the federal regulatory process with regard to crude oil and petroleum product pipeline repairs has already begun in response to a federal statute passed in 2002 to coordinate environmental reviews and permitting needed for pipeline repairs and more clearly define federal roles in the pipeline repair process.[24] However, this streamlined federal process has not been applied to constructing new crude oil or petroleum product pipelines or significantly upgrading or increasing capacity of existing pipelines.[25]
CONCLUSION The choices the United States and other countries make about how to ensure sufficient supplies and stable prices of petroleum products and other fuels such as ethanol and biofuels will greatly influence energy prices in the United States. For biofuels in particular, cost and availability will depend in part on how well international, federal, state, and local governments coordinate their biofuel standards and methods of integrating them with petroleum products. Harmonizing fuel specifications worldwide, while continuing to allow for regional differences in fuels specifications that are there to meet specific environmental or vehicle performance goals, would make it easier to refine and transport common blends, streamline delivery, increase opportunities for trade, provide additional sources of supply, and potentially reduce prices and price volatility. However, if the world and the United States end
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up with numerous different biofuel blends—as appears to be happening under existing plans and mandates—this could expand the array of incompatible gasoline and diesel blending stocks and final blended products that cannot be interchanged at the retail level, reducing opportunities for trade. In addition, these products will have to be segregated during shipment, further straining the supply infrastructure. Unless the supply infrastructure catches up and keeps up with these changes, the domestic energy supply will be less secure and prices will tend to be higher or more volatile. Even without these changes, rising demand for crude oil and petroleum products over the last 25 years has challenged the supply infrastructure for these commodities in certain areas, leading to higher prices during supply disruptions or during periods when pipelines or ports lack sufficient capacity to transport the products suppliers wish to ship. As noted by the Secretary of Energy in December 2007, the U.S. energy infrastructure system—including oil pipelines—is “pressed,” and it is important that pipeline and other energy infrastructure owners maintain their assets effectively, in order to maintain adequate supplies of energy. In the absence of a comprehensive analysis of the likely weaknesses in our infrastructure, policy makers and regulatory agencies involved in overseeing the safety and adequacy of supply infrastructure remain in the dark about the extent of these problems and their effects on prices of petroleum products. Further, as demand for petroleum products and biofuels grows, the existing system may become increasingly constrained and need to be upgraded and expanded to handle greater and different product flows. Because federal and state agencies and other entities will be involved in approving such upgrades and expansions, it is essential that they be well informed as to the current state of the supply infrastructure and the areas in most critical need of further investment. Furthermore, the lack of a lead agency to streamline the complex and costly permitting process for U.S. supply infrastructure construction or expansion projects and the lack of ability of federal agencies to convey the power of eminent domain in cases where conflicts over infrastructure placement cannot be resolved may deter potential market entrants from investing in much-needed upgrades in a timely fashion. As a result, we could end up with less security of supply and higher and more volatile prices in the future.
RECOMMENDATIONS FOR EXECUTIVE ACTION To better monitor and evaluate the development of our nation’s supply infrastructure systems, as well as to facilitate the continued tradability of products across domestic and global markets and to ensure that gasoline supplies from Europe and elsewhere remain compatible with U.S. gasoline specifications, we are making a number of recommendations that, if adopted, should improve prospects for the future security of petroleum product supplies and price stability. •
To avoid additional proliferation of differing fuel specifications that would further burden the existing supply infrastructure and create impediments to trade, we recommend that the Secretary of Energy coordinate with EPA and other relevant federal agencies, states, IEA, the European Union, and other foreign entities to encourage development of biofuels and petroleum products standards and blending practices that maximize the fungibility of these fuels and minimize the spread of
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•
•
differing fuel types that would further strain the supply infrastructure, while recognizing that some fuel differences to reflect local environmental requirements, engine performance, or other factors are likely beneficial. To comprehensively analyze the U.S. supply infrastructure’s capacity to accept, handle, and transport the increasing volumes and types of petroleum products and biofuels expected to traverse its system, we recommend the Secretaries of Energy and Transportation undertake the comprehensive study of existing and projected increases to the infrastructure system—including terminal capacity and pipeline throughputs—to evaluate whether future demand is likely to be met by existing infrastructure and planned increases as mandated by Congress in 2006. To the extent that the data to comprehensively conduct such analyses may at present not be collected, the Secretaries should consider evaluating the merits of enhancing the reporting of utilization and throughputs, perhaps using natural gas pipeline and storage reporting requirements as a model. In conjunction with the completion of the first comprehensive study of the supply infrastructure, we recommend the Secretary of Transportation work with DOE, FERC, EPA, and other federal agencies to evaluate the feasibility and desirability of designating a lead federal agency, with authority to convey the power of eminent domain, to coordinate across agencies and streamline the permitting and siting process for crude oil and petroleum product interstate pipeline expansions, upgrades, and new construction, using FERC’s role with natural gas pipelines as a model. If this is found to be feasible and desirable, we recommend the aforementioned agencies work together to determine which agency should take the lead role and to prepare a legislative proposal for Congress to provide any additional authority needed to implement this recommendation.
APPENDIX I: SCOPE AND METHODOLOGY The Chairman and a member of the Senate Commerce, Science, and Transportation Committee asked GAO to evaluate trends and effects on petroleum product prices in (1) international trade of petroleum products; (2) refining capacity and intensity of refining capacity use internationally and in the United States; (3) international and domestic crude oil and petroleum product inventories; and (4) domestic crude oil and petroleum product supply infrastructure, particularly pipelines and marine transportation. To address the first objective, we examined data from the Department of Energy’s (DOE) Energy Information Administration (EIA) and the International Energy Association (IEA) to evaluate trends in the international trade flows for crude oil and petroleum products and their price correlations over time at international trading hubs. In addition, IEA data were used to calculate total global imports and exports of crude oil and petroleum products as well as for key global regions including Europe, Asia and the United States. We met with more than 20 oil industry companies—including refiners and pipeline companies—a number of financial and investment corporations, more than 25 industry groups, and more than 15 domestic and international government agencies to corroborate trend analyses, reports, and data. We conducted audit work in various locations in Texas, California, New York, and Washington, D.C., as well as Belgium, France, Germany, and the United Kingdom to obtain industry’s
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perspective on recent trends in the international trade of petroleum product as well as prospective trends going forward. In addition, we analyzed EIA and New York Mercantile Exchange, (NYMEX) data on historical spot and futures prices for crude oil and petroleum products at international and domestic trading hubs to see how price volatility has changed over time. To address the second objective, we assessed trends in refining capacity, refining capacity additions, utilization, complexity, and planned investments using IEA, EIA, and Oil and Gas Journal data, and determined the data were sufficiently reliable for our purposes. We met with more than 20 oil-industry companies—including refiners and pipeline companies—a number of financial and investment corporations, more than 25 industry groups, and numerous staff and officials of more than 15 domestic and international government agencies in California, Texas, New York, Washington D.C. ,as well as Belgium, France, Germany and the United Kingdom to corroborate trend analyses, reports and data. We also reviewed and analyzed trends in refinery investment, operating costs, and profitability in the U.S. and internationally, using literature and data on U.S. and international refining practices, trends and forecasts, and interviewed experts on these trends. To address the third objective, we used data from EIA and IEA on crude oil and petroleum product inventories and projected demand to conduct international, U.S. total domestic, and U.S. Petroleum Administration for Defense District (PADD) inventory trend analysis on inventories in absolute terms and in “days forward cover” terms. We analyzed NYMEX and other futures market data, as well as EIA data, to observe the effects of the expected future price for crude oil on inventory holding decisions. To collect these data, we conducted a site visit to meet with industry and government representatives in Belgium, France, Germany, and the United Kingdom to gain information about the European Union’s policy of maintaining strategic petroleum product reserves and their effects on price levels and price volatility. To address the fourth objective, we interviewed federal and state agencies that oversee the economic, safety, and environmental impacts of pipelines and marine transportation on current and future utilization capacity of the petroleum product infrastructure. Where possible, we collected and analyzed data on the age of the pipeline and marine infrastructure system, capacity, throughputs, and constraints. We compared data reporting requirements for petroleum products with reporting requirements for liquefied natural gas, and identified differences in such reporting requirements. We spoke with common carrier pipeline operators, port authorities, government entities, and trade association and consumer advocate groups to gain their perspectives on supply infrastructure investment, capacity utilization levels, and potential system constraints. We also reviewed previous relevant GAO reports and testimonies, and Department of Energy and Department of Transportation reports. In addition, we examined reports and data from supply disruption case studies to examine those cases’ impact on infrastructure, prices, and price volatility. During our audit work we consulted with the following entities: •
We met with the following oil industry companies, including refiners, supply infrastructure and oil service companies: BP; Buckeye Partners; Chevron Corporation; ConocoPhillips Company; ExxonMobil Corporation; Fluor Corporation; Frontier Oil Corporation; Hess Corporation; Holly Corporation; Kinder Morgan Energy Partners; Longhorn Partners Pipeline; Magellan Midstream Partners;
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•
•
•
Marathon Oil Company; Mid-continent Express Pipeline; Oiltanking GmbH; Paramount Petroleum Corporation; Plains All American Pipeline L.P.; RaceTrac Petroleum, Inc.; Sunoco, Inc.; TEPPCO Partners L.P.; Tesoro Corporation; UOP LLC; Valero Energy Corporation. We met with the following financial organizations: Deutsche Bank; Goldman, Sachs and Co; JP Morgan Chase Bank; Morgan Stanley; New York Mercantile Exchange, Inc. (NYMEX). We met with the following industry groups and expert institutions: Allegro Energy Consulting; American Association of Port Authorities; American Petroleum Institute (API); Association of Oil Pipe Lines (AOPL); Conservation of Clean Air and Water in Europe (CONCAWE); Consumer Federation of America; Energy Analysts International, Inc.; European Petroleum Industry Association (EUROPIA); Global Insight, Inc.; Institut Francais du Petrole (IFP); Muse Stancil and Co.; National Association of Regulatory Utility Commissioners; National Petrochemical and Refiners Association; Oil and Gas Journal; Petroleum Marketers Association of America; Pipeline Safety Trust; PIRA Energy Group; Purvin and Gertz, Inc.; Stillwater Associates LLC; Turner, Mason and Company; the Rabinow Consortium, LLC; UK Petroleum Industry Association; Union of European Petroleum Independents (UPEI); University of California Energy Institute; Western States Petroleum Association; Wood Mackenzie Research and Consulting. With regard to government and agency sources, we met with the following U.S. agencies and governmental institutions: Department of Defense, including the Army Corps of Engineers; Department of Energy, including the Energy Information Administration; Department of State; Department of Transportation, including Pipeline and Hazardous Materials Safety Administration (PHMSA); Department of Homeland Security; Federal Energy Regulatory Commission; Federal Trade Commission; Interagency Committee on Marine Transportation; Oak Ridge National Laboratory. We met with the following state and local governmental agencies: California Energy Commission (CEC); California Environmental Protection Agency Air Resources Board (CARB); Hawaii Energy Planning and Policy Branch; Port of Houston Authority. We met with the following international government and multilateral organizations: European Commission Directorate-General for Energy and Transport; EBV (German Stockholding Agency); French General Directorate for Energy and Raw Materials; International Energy Agency (IEA); International Monetary Fund (IMF).
The report primarily uses data from the domestic and international wholesale petroleum product and crude oil markets. In contrast to retail markets, wholesale prices do not generally include extra costs such as federal and state taxes, distribution and marketing expenses and profits. In every case for the data used in this report, we assessed and determined that the data were sufficiently reliable for our purposes. We performed our work from August 2006 through September 2007 in accordance with generally accepted government auditing standards.
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APPENDIX II: COMMENTS FROM THE DEPARTMENT OF ENERGY
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APPENDIX III: COMMENTS FROM THE FEDERAL ENERGY REGULATORY COMMISSION
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REFERENCES [1]
GAO, Energy Markets: Mergers and Other Factors That Influence Gasoline Prices, GAO-07-894T (Washington, D.C.: May 23, 2007); GAO, Energy Markets: Factors Contributing to Higher Gasoline Prices, GAO-06-412T (Washington, D.C.: Feb. 1, 2006); GAO, Energy Markets: Gasoline Price Trends, GAO-05-1047T (Washington, D.C.: Sept. 21, 2005); GAO, Motor Fuels: Understanding the Factors That Influence the Retail Price of Gasoline, GAO-05-525SP (Washington, D.C.: May 2005). [2] FERC also serves as the lead agency in coordinating the permitting process across federal agencies and can similarly convey the right of eminent domain for electricity transmission lines. [3] The Organisation for Economic Co-operation and Development is a group of 30 countries committed to democracy and the market economy to support sustainable economic growth, maintain financial stability, and assist other countries’ economic development. These countries are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Spain, Sweden, Switzerland, Turkey, United Kingdom, and the United States. However, we consider the United States separately for the purposes of this report. [4] GAO, Gasoline Markets: Special Gasoline Blends Reduce Emissions and Improve Air Quality, but Complicate Supply and Contribute to Higher Prices, GAO-05-421 (Washington, D.C.: June 2005). [5] The Strategic Petroleum Reserve (SPR) is a federally maintained stockpile of about 700 million barrels of light crude oil for use in the case of a major disruption of oil supplies. [6] Access to the rail market is limited and tanker trucks’ expenses depend on distances traveled. [7] By petroleum products, we refer to primarily gasoline, diesel, jet fuel, heating oil. Most petroleum products and crude oil are shipped primarily by pipeline within the United States. Imports of petroleum products and crude oil, however, travel to the United States mainly over sea by vessel. [8] FERC also collects administrative, financial, and operational information on crude oil and petroleum product pipeline companies. [9] Figures represent trade originating or ending in OECD member nations, including trade between OECD nations, from OECD nations to non-OECD nations, and from nonOECD nations to OECD nations. Because figures include some trade from OECD nations to other OECD nations, such trade is counted as both an import and an export and therefore includes some duplication of counting. Furthermore, figures do not account for trade between non-OECD nations and therefore understate the total global trade of these products. [10] Total gasoline includes both finished motor gasoline and motor gasoline blending components. [11] Imports of distillate fuels and jet fuel have also risen in the last 20 years, while imports of residual fuel oil have declined.
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[12] The graphic shows that imports remained significantly higher than in the same months during the previous year at least through January 2006. This was likely the result of lasting damage to U.S. refining production caused by the hurricanes. [13] States are subject to some federal requirements in setting biofuel policies. Currently, EPA has determined that only blends of up to 10 percent ethanol are allowed in conventional gasoline vehicles and blends of up to 85 percent ethanol are permitted in flexible fuel vehicles. However, the state of Minnesota and the Renewable Fuels Association, as well as DOE are developing research and tests to gather the data required to facilitate EPA certification of fuel blends up to E15 or E20. [14] The price increases were measured in gasoline prices in Chicago relative to Houston prices. [15] See, for example, GAO’s Motor Fuels: Gasoline Prices in the West Coast Market, GAO-01-608T, (Washington, D.C.: Apr. 25, 2001). [16] In the United States, inventory data reported in this report refer only to privately held stocks, not the federally held crude oil and heating oil strategic reserves. As will be discussed later in this report, this is not true of some other OECD member inventory data. [17] Unlike in the United States, where the federal government holds strategic stocks of primarily crude oil—but also a relatively small stock of fuel oil in the U.S. Northeast Home Heating Oil Reserve—European countries hold a large fraction of their strategic stocks in petroleum products, including gasoline and certain distillate fuels. Some European countries require private companies to maintain these stocks. [18] It is also not clear that the benefits of collecting and maintaining such data outweigh the costs. Evaluating these trade-offs was beyond the scope of this report, but such an evaluation would have to be made before making a decision to collect a broader range of inventory data. [19] Assessing the relative importance of these factors with any precision would be very difficult and we did not undertake this task in this report, so the list of factors should not be seen as a ranking of those factors in any way. [20] Energy Information Administration, Petroleum 1996: Issues and Trends, (Washington D.C., September 1997). [21] Note that there may have been additional factors influencing prices during this period, so we are not asserting that the pipeline outage was responsible for the entire change in prices. [22] It should be noted that whether or not the benefits of collecting and maintaining such data outweigh the costs is unknown. Evaluating these trade-offs was beyond the scope of this report, but such an evaluation would have to be made before making any decision to collect a broader range of pipeline or other infrastructure data. [23] Pub. L. No. 109-468, §8. [24] Pub. L. No. 107-355, § 16 [25] In 2006, DOT identified the need for additional Congressional authority to reduce the regulatory burden on companies trying to construct new pipelines or repair existing ones. Specifically, DOT proposed legislation that, according to DOT, would among other things provide “minimal authority” to assist pipeline operators in overcoming state and local-level impediments to constructing new pipelines and would further streamline the permitting process for pipeline repairs. At this time, Congress has not
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provided this additional authorization. DOT’s proposal did not call for a federal agency to have the authority to convey the power of eminent domain in cases where conflicts over infrastructure placement cannot be resolved but it would have authorized the Secretary of DOT to “designate an ombudsman to assist resolving disagreements between Federal, State, and local agencies and pipeline operators arising during agency review of pipeline repairs and hazardous liquids pipeline construction projects…”
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 53-83
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 2
THREE-DIMENSIONAL SIMULATION OF BASE CARRIER TRANSPORT EFFECTS IN BACK SIDE POINT CONTACT SILICON SOLAR CELLS* K. Kotsovos† and K. Misiakos Institute of Microelectronics, NCSR Demokritos, Attiki, Greece
ABSTRACT This work presents a theoretical investigation of rear junction point contact silicon solar cells through three-dimensional numerical simulation based on the solution of minority and majority carrier transport equations in the base of the cell. The device series resistance is evaluated through the simulated current-voltage (IV) curves under AM1.5 illumination conditions and its dependence on back contact geometry is examined. Results are presented which show the influence of the majority carrier transport in the base to the solar cell performance. A comparison is also performed with two other similar types of point contact solar cells, one with the emitter located on the front surface and the other on both surfaces, as well as with a conventional solar cell structure.
I. INTRODUCTION Rear point contact (locally diffused) silicon solar cells with backside p/n junctions are structures which have already shown their promising potential in solar energy production, reaching very high conversion efficiency (27.5%) under concentrated illumination [1]. Although these devices were ideal for concentrator applications due to low series resistance and surface recombination losses, they have some additional interesting advantages, *
A version of this chapter was also published in Leading Edge Research in Solar Energy edited by P. N. Rivers published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research. † Institute of Microelectronics, NCSR Demokritos, P. O Box 60228 153 10 Aghia Paraskevi, Attiki, Greece Tel: (+30)2106503113, Fax: (+30)2106511723, E-mail:
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compared to typical solar cells designed for one-sun operating conditions. Specifically, since the metallization grid lies entirely on the back surface, there is no shading loss on the illuminated surface of the solar cell, while the interconnection of individual cells into modules is more easily implemented. However, this optimized solar cell design was considered to be too complex for use at low concentrations, so a simplified structure was proposed by Sinton et al. [2], suitable for cost-effective production. Therefore, SunPower Corporation has developed a process for that purpose, providing solar cells fabricated on high quality FZ substrates with efficiencies greater than 20% under normal sunlight [3]. The choice of high quality material is necessary for this type of solar cells, since the photogenerated carriers need to reach the back surface in order to be collected. Results of theoretical simulations regarding the back contact structure have already been published in the literature. A 3D model based on the solution of semiconductor transport equations using a variational approach has been developed by Swanson [4-5], which was applied in order to optimize the back point contact solar cell design under concentrated illumination. An optimization of the interdigitated back contact cell was performed by Chin et al. [6], while the simulated efficiency limit of this cell was calculated by Ohtsuka et al. [7] by 3D simulations. Epitaxial layer transfer has also been proposed as an alternative way to produce back contact solar cells [8], where this method is used to create thin silicon films on foreign substrates and a two-dimensional model was applied for this case. The purpose of this work is a theoretical investigation of back junction point contact solar cells by means of numerical three-dimensional simulation based on the solution of minority and majority carrier transport equations in the base of the cell. The method is based on the transformation in x and y dimensions of the basic partial differential equations through 2D Fast Fourier Transform (FFT). In Fourier space these equations become algebraic in Kx and Ky (the transformed x, y variables), thus reducing to ordinary differential equations with respect to z, that can be solved in analytical form. The basic assumption for such a problem reformulation is planar geometry and low injection. The solution of the transport equations under illumination conditions provides the device IV characteristics and solar cell’s series resistance is extracted. This model was previously used [9] to simulate a structure similar to the PERL [10-11] solar cell, a device that is consisted of an emitter covering the front illuminated surface and point contacts in the back surface. The same method was later applied for the simulation of the double junction solar cell [12], a device with an additional emitter in the back surface. Since the back junction point contact solar cell and the previous two types of solar cells, are high efficiency structures, a direct comparison among them is performed. The influence of back contact size and spacing in solar cell performance is discussed in detail. The following section presents a description of the mathematical model of our method as applied on the point contact structures under consideration. The third section includes our simulation results and discussion.
Three-Dimensional Simulation of Base Carrier Transport Effects…
55
II. MATHEMATICAL MODEL- SIMULATION ALGORITHM
II.1. Assumptions –Device Geometry y
x z
w
a
d l
3l/4
Oxide
3l/4 Base
l/4
b
Contact Emitter
l/4
c
Oxide
Contact
d
w
d
Emitter
l Emitter
Base
Contact Oxide
Emitter
e
d Contact Emitter
Figure 1. a) Three dimensional back surface geometry of the simulated front junction, back junction and double junction devices b) Back junction structure, c) Back point junction structure (the locations of the diffused regions are shown in the insert) d) front junction structure e) Double junction structure. This pattern is repeated periodically in x and y directions with a period length l.
The base of the solar cells is considered to be under low injection conditions and assumed as homogeneous with thickness w, while the junctions are infinitesimally shallow. Photogeneration in the emitter regions is considered negligible, while their ohmic losses are neglected. We set as x, y the directions parallel to the junction while z is the perpendicular
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one. The geometry of the simulated devices is shown in figure 1. The base contacts on the back surface are assumed as squares with side length d, while the period length, or field length, of the repeated pattern as shown in figure 1(a) is l. Figure 1(b) illustrates the structure of the back junction solar cell, figure 1(c), 1(d) the corresponding point back junction and single front emitter devices and figure 1(e) the double junction solar cell. The dimensions of the back point junction and base contact of the cell as shown in figure 1(c) are the same. In addition, zero front surface reflectance is assumed, while light trapping is similar to pyramidal texture scheme.
II. 2. Minority Carrier Continuity Equation and Boundary Conditions The minority carrier continuity equation for a p-type base under low-level injection and steady state is given by
∇ 2 n( x, y , z ) =
n ( x , y , z ) G ( x, y , z ) − L2n Dn
(1)
where n(x,y,z) is the minority carrier concentration, Ln is the corresponding diffusion length, Dn the diffusion constant and G(x,y,z) the local generation rate.
II. 2.1. Boundary Conditions (Back Junction Structure) The following relation describes the boundary condition at the front of the oxide passivated solar cell’s surface as shown on figure 1(b)
J n ( x, y, w) = eDn
dn( x, y, z ) dz
z=w
= eS1 n( x, y,0)
(2)
where Jn(x,y,w) is the minority carrier diffusion current in the back surface and S1 is the recombination velocity in the area covered by the oxide. At the back surface, the boundary condition at the diffused contacts is also expressed by the minority carrier diffusion current, which depends on the surface recombination velocity in that area:
J n ( x, y, w) = eDn
dn( x, y, z ) dz
z=w
= −eS 2 n( x, y, w)
(3)
where Jn(x,y,w) is the minority carrier diffusion current in the back surface and S2 is the recombination velocity in the diffused contact areas, which is assumed as constant and given by the following expression
S2 =
J 0C N A eni2
(4)
Three-Dimensional Simulation of Base Carrier Transport Effects…
57
where J0C is the saturation current density in the diffused contacts, ni the intrinsic carrier concentration of the semiconductor and NA the base doping. The rest of the back surface area is covered by the junction, and the boundary condition is:
n( x, y, w) =
ni2 NA
⎛ ⎛ e(V + Vdrop ( x, y, w) ) ⎞ ⎞ ⎜ exp⎜ B ⎟⎟ − 1⎟ ⎜ ⎜ ⎟ KT ⎝ ⎠ ⎠ ⎝
(5)
where VB is the junction bias voltage and Vdrop is the voltage drop caused by the majority carrier flow through the base series resistance. This voltage drop is initially set to zero.
II. 2.2. Boundary Conditions (Back Point Junction Structure) The front surface of this structure, shown on figure 1(c) is covered by oxide, so relation (2) gives the expression of the boundary condition in that region. Expressions (3) and (5) define the boundary conditions in the back diffused contacts and the junction area respectively. The rest of the back surface is oxide passivated, so the boundary condition is defined by the minority carrier diffusion current
J n ( x, y, w) = eDn
dn( x, y, z ) dz
z=w
= −eS 3 n( x, y, w)
(6)
where S3 is the recombination velocity in the area covered by the back oxide.
II. 2. 3. Boundary Conditions (Front Junction Structure) The emitter of the front junction solar cell, which is illustrated in figure 1(d) covers the whole illuminated surface, so the boundary condition inside the junction is
ni2 n( x, y,0) = NA
⎛ ⎛ e(V + Vdrop ( x, y,0) ) ⎞ ⎞ ⎜ exp⎜ B ⎟⎟ − 1⎟ ⎜ ⎟ ⎜ KT ⎝ ⎠ ⎠ ⎝
(7)
At the back surface, the minority carrier diffusion current is determined by the surface recombination velocity, where in the diffused base contact regions is defined by relation (4), while in the oxide passivated surface has a constant value (S1). Therefore, the general form of the boundary condition at the back surface may be written as
J n ( x, y, w) = eDn
dn( x, y, z ) dz
z=w
= −eS ( x, y )n( x, y, w)
(8)
II. 2. 4. Boundary Conditions (Double Junction Structure) The double junction structure (figure 1(e)) is consisted of an emitter covering the whole front surface (as in the front junction device), so the boundary condition in that area is given by (7). In a similar way, the conditions in the back surface are expressed by relations (3) and
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K. Kotsovos and K. Misiakos
(5) of section II.2.1. The front and back emitters of this device are biased with same voltage VB.
II.3. Majority Carrier Voltage Drop Equation The solution of continuity equation (1) may be used to obtain the voltage drop caused by the majority carrier flow. We begin from the current density relation for the majority carriers
J p = eμ p pE − eD p∇p
(9)
Charge neutrality in the semiconductor is assumed, so it follows that δp(x,y,z)=δn(x,y,z). Since the cell is operated under low injection, p≈NA, where NA is the base doping. Using these assumptions and with the aid of (1), we differentiate (9) ∇J p = eμ p N A ∇E − eD p ∇ 2 p ⇒ ∇J p = eμ p N A ∇E − eD p ∇ 2 n ⎛ n G ⎞ ⎟⎟ ⇒ ∇J p = eμ p N A ∇E − eD p ⎜⎜ 2 − ⎝ Ln D n ⎠ Dp ⎛ n ⎞ n ⎜⎜ − G ( z ) ⎟⎟ ⇒ − G = − μ p N A ∇E + Dn ⎝ τ n τn ⎠ D p − Dn ⎛ n G ⎞ ⎜⎜ 2 − ⎟ ∇E = μ p N A ⎝ Ln Dn ⎟⎠
The comparison of this equation with (1), gives a more compact expression
∇ 2V =
1 ( Dn − D p )∇ 2 n μpNA
(10)
where Dn, Dp are the diffusion constants for electron and holes respectively and μp is the hole mobility. The solution of this equation provides the voltage drop due to majority carrier flow and is subjected to the boundary conditions given in the next subsection.
II. 3.1. Boundary Conditions (Back Junction Structure) Since there is no total current flow in the oxide covering the whole front surface of the back junction solar cell, the majority carrier current value is exactly the opposite of the minority carrier equivalent:
J p ( x, y,0) = −eS1 n( x, y,0)
(11)
At the back surface, the diffused back contact areas are considered as the ground terminal, so the majority carrier voltage drop is zero:
Three-Dimensional Simulation of Base Carrier Transport Effects…
Vdrop ( x , y , w ) = 0
59 (12)
At the rest of the back surface area, covered by the rear junction, the majority carrier current is given by
⎛ ⎛ e(VB + Vdrop ( x, y, w)) ⎞ ⎞ ⎟⎟ − 1⎟ J p ( x, y, w) = J 0 ⎜⎜ exp⎜⎜ ⎟ KT ⎝ ⎠ ⎠ ⎝
(13)
where J0 is the emitter saturation current density. Expressions (11) and (13) can be converted as boundary conditions for the electric field E if we make use of (9) with the following way:
J p = eμ p pE − eDp∇p ⇒ J p = eμ p N A E − eDp∇n ⇒ J p = eμ p N A E −
Dp Dn
Jp + Jn ⇒ E =
Dp
Dn eμ p N A
Jn
(14)
The minority carrier current density Jn, which is required in expression (14) is obtained from the solution of the continuity equation described in section II. 2.
II. 3.2. Boundary Conditions (Back Point Junction Structure) The front surface of this structure is covered by oxide as in the case of the back junction structure, so expression (11) defines the boundary condition in that region. Relations (12), (13) also describe the boundary conditions inside the back diffused contact and junction areas respectively, while the rest of the back surface is covered by oxide, so the following condition holds
J p ( x, y, w) = eS 3 n( x, y, w)
(15)
As reported on the previous subsection, the majority carrier expressions may be converted to electric field boundary conditions by making use of (14).
II. 3.3. Boundary Conditions (Front Junction Structure) The boundary condition for the majority current at the front surface and inside the junction is written as:
⎛ ⎛ e(VB + Vdrop ( x, y,0)) ⎞ ⎞ ⎟⎟ − 1⎟ J p ( x, y,0) = − J 0 ⎜⎜ exp⎜⎜ ⎟ KT ⎝ ⎠ ⎠ ⎝
(16)
where J0 is the saturation current density in the emitter. The expression of the boundary condition in the oxide-covered part of the back surface is also given by
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K. Kotsovos and K. Misiakos
J p ( x, y, w) = eS1 n( x, y, w)
(17)
The diffused back contact areas are considered as the ground terminal, where the majority carrier voltage drop is given by (12).
II. 3.3. Boundary Conditions (Double Junction Structure) Since the front emitter of this structure covers the whole surface, relation (16) of the previous subsection defines the boundary condition in that area. In a similar way, back surface boundary conditions are expressed by relations (12) and (13) of section II.3.1.
II. 4. Algorithm Description In this section we will provide a description of the algorithm, which is used to obtain a numerical solution of the problem formulated in the previous subsections. The derived expressions from the solutions of the minority carrier diffusion equation and the majority carrier voltage drop equation are given in appendices B and C respectively.
II. 4. 1. Diffusion Equation Solution Algorithm (1) The algorithm starts with an initial guess for the minority carrier concentrations in front and back surface areas not covered by the emitters, while in the junction regions the corresponding boundary conditions (depending on the investigated structure) that define the minority carrier concentrations are applied. Majority carrier voltage drop is initially set to zero. (2) A two-dimensional Fast Fourier Transform (FFT) with respect to x, y is performed to both surface concentrations and the minority carrier current density in Fourier space is calculated by differentiating the general solution of the diffusion equation with respect to z (appendix B). (3) An inverse FFT is then applied to each of the transformed current densities to obtain the real current densities at the areas not covered by the junctions, while at the regions covered by oxide or the back contacts the current densities are acquired from the boundary conditions. (4) Subsequent Fast Fourier Transforms are used in order to calculate the new carrier
~
concentrations as functions of the transformed current densities J n ( k x , k y ,0) ,
~ J n (k x , k y , w) (Appendix B).
(5) Inverse Fast Fourier Transforms are performed to the previously obtained carrier concentrations to calculate the new estimated ones in real space. (6) The solution is set as a mixture of the previously calculated and the newly obtained minority carrier distributions with a defined percentage. If this solution fulfills the convergence condition, the results are stored in order to proceed with the voltage drop equation, else calculations are repeated from step 2.
Three-Dimensional Simulation of Base Carrier Transport Effects…
61
II. 4. 2. Voltage Drop Equation Solution Algorithm The results of the solution of the minority carrier diffusion equation are required in order to obtain the majority carrier voltage drop. Therefore, the corresponding procedure for the case of equation (10), which follows the one referred to the previous section, is described through the following steps: (1) An initial guess for the majority carrier voltage drop (Vdrop) on both surfaces is used. This is considered as zero. This estimate also fulfills the boundary condition at the back-diffused contacts. (2) Two-dimensional Fast Fourier Transforms with respect to x, y are performed to the voltage distributions and the electric field distributions in Fourier space
~ ~ E (k x , k y ,0) , E (k x , k y , w) are calculated by differentiating the general solution of
equation (10) with respect to z (appendix C). (3) An inverse FFT is then applied to each of the transformed electric field distributions to obtain the corresponding values in real space, while at the regions covered by oxide or the junctions the current densities are acquired from the boundary conditions. (4) In this step, Fast Fourier Transforms are used in order to obtain the electric field distributions in Fourier space and the new transformed voltage
~
~
distributions V (k x , k y ,0) , V (k x , k y , w) as
~ E (k x , k y , w) are calculated (appendix C).
functions
of
~ E (k x , k y ,0) ,
(5) Inverse Fast Fourier Transforms are performed to the previously obtained voltage distributions to calculate the new estimated equivalents in real space. (6) The solution is set as a mixture of the previously calculated and the newly obtained one in a similar way as that referred to in the previous subsection. If this solution fulfills the convergence condition, the results are stored in order to be inserted in the boundary conditions of the minority carrier diffusion equation, else calculations are repeated from step 2.
II. 4. 3. Solution of the Final Coupled Problem The separate solutions of the differential equations (1) and (10) are not necessarily selfconsistent for all working conditions, since the boundary conditions that define the minority carrier diffusion equation depend on the calculated majority carrier voltage distribution in a non-linear way. Therefore self-consistency should be achieved by following a proper iterative procedure described as following: (1) Calculation of the solution of equation (1) by following the steps described in section II. 4.1. The calculations are performed under the assumption of zero voltage drop. (2) Numerical solution of equation (10) using the minority carrier currents and density distributions as obtained previously. (3) New solution of the minority carrier diffusion equation taking into account the voltage distributions calculated from the previous step. (4) The procedure continues between steps 2 and 3 until self-consistency is achieved.
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K. Kotsovos and K. Misiakos
III. SIMULATION RESULTS The substrate of the simulated solar cells is considered as monocrystalline silicon, with base doping density NA=1016cm-3. We assume that the oxide-covered surfaces have ideal passivation properties, so there are no recombination losses at these areas. Therefore, the recombination velocity at these surfaces is zero while in the diffused contact regions is calculated from the relation (4), where we assume that the recombination current in these regions is J0c=10-12 A/cm2. The emitter saturation current value of all devices is the same (1013 A/cm2), while for all acquired results of the following sections III.1-III.4, a base diffusion length Ln of 800μm is assumed. The mobilities for minority and majority carriers are taken from Klaasen [13]. The simulated illumination is considered as the global AM1.5 sun spectrum [14] normalized to 100mW/cm2, where light trapping similar to the pyramidal textured scheme is assumed (Appendix A). The back surface contact has reflective characteristics with reflectivity R=95%. The simulation program, which is based on the algorithm of section II. 4 is used to calculate the IV characteristic of the cell and from that curve the maximum power, the short circuit current, the open circuit voltage and the series resistance of the cell are obtained. The series resistance of the cell is calculated for each point of the curve using the following relation
Voc − V − Rs =
I KT ln sc e I sc − I I
(18)
Voltage Drop (m
V)
4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 400
0.0
320
80
240
160
x (μ m)
160
240
80
320 400
) μm ( y
Figure 2. Majority carrier voltage drop at the back surface of a back point junction structure with period length 400 μm and 80 μm back diffused junction sidelength. The cell is operated in the maximum power point (576 mV). Base thickness w is 400μm and Ln=800μm.
Three-Dimensional Simulation of Base Carrier Transport Effects…
63
The value of Rs which is obtained by (18) is caused by the current crowding effect at the back point contacts, since inside these regions current density values are large [9]. Such an effect induces a voltage drop which rises fast near the base contact edges. This effect is more intense in the back point junction structure, where near the back point emitter as shown in figure 2 an additional voltage drop is induced. The maximum voltage drop value is reached inside the emitter area, where it remains constant. In this structure d/l equals 0.2, while the period of the repeated pattern and the base thickness is 400μm.
III. 1. Short Circuit Current (Jsc) Figure 3 illustrates the short circuit current of the back junction structure as a function of the back base contact size and its spacing as parameter, assuming base thickness of 200μm. As expected, the reduction of the back contact area results to an increased photocurrent since the surface recombination velocity in this area (S2) is high. Jsc is also improved when the back contact spacing is smaller since in this case current crowding is reduced and carriers are collected more efficiently.
40.6
2
Jsc (mA/cm )
40.4 40.2 40.0 39.8
d=400μm d=200μm d=50μm
39.6 39.4
0.1
0.2
0.3
0.4
0.5
d/l Figure 3. Short circuit current (Jsc) of the back junction structure as a function of back contact size for different contact spacing l. Base thickness is 200μm and Ln=800μm.
The short circuit current of the back point junction structure is shown on figure 4. In this case, the increase of the back contact size is beneficial to the device photocurrent in contrast to the previously analyzed structure. A dramatic reduction in Jsc is also observed for the largest contact spacing (400μm), since in this case the required path for the collection of photogenerated carriers is significantly increased, thus the base minority carrier diffusion length should be higher for a more efficient current collection.
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K. Kotsovos and K. Misiakos
40
36
2
Jsc(mA/cm )
38
34 32
d=400μm d=200μm d=50μm
30 28 26
0.1
0.2
0.3
0.4
0.5
d/l
42
1.03
40
0.98
38
0.93
36
0.88
34
0.83
32
0.79 front junction device double junction device back junction device point junction device
30 28 26
0.1
0.2
0.3
0.4
0.5
0.74
3D to 1D ratio
2
Jsc(mA/cm )
Figure 4. Short circuit current versus back contact size of the back point junction solar cell. The other parameters are the same as of figure 3.
0.69 0.64
d/l Figure 5. Short circuit current of all different point contact structures versus back contact size for a given contact spacing of 400μm, device thickness 200μm and Ln=800μm. The right axis is the current normalized to the corresponding value of the conventional 1D structure.
42.0
1.03
41.6
1.02
41.2
1.01
40.8
1.00
40.4
0.99
40.0
0.98
39.6
0.97
39.2
front junction device double junction device back junction device point junction device
38.8 38.4 38.0
0.1
0.2
0.3
0.4
0.5
0.96 0.95
65
3D to 1D ratio
2
Jsc(mA/cm )
Three-Dimensional Simulation of Base Carrier Transport Effects…
0.94 0.93
d/l Figure 6. Short circuit current of all different point contact structures versus back contact size for a given contact spacing of 50μm. The other parameters are the same as of the previous figure.
The next figure shows a comparison of the Jsc of the four different structures of figure 1 when back contact spacing is 400μm. The right hand axis is the current normalized to the corresponding typical solar cell structure where the back contact covers the whole back surface (1D case). Figure 6 is the same plot calculated for the smallest back contact spacing of 50μm. Since all devices are illuminated on the front side, most carriers are generated near the front surface, thus the single, double junction as a well as the typical solar cell device show an improved Jsc compared to both back junction structures. The reduction of the back contact spacing to 50μm results to a Jsc increase of these devices, especially in the point junction one, while the corresponding short circuit current of single and double junction devices remains almost unaffected from that change in l [9, 12]. A greater diffusion length would significantly improve the carrier collection ability of back contact devices, as will be discussed later.
III. 2. Open Circuit Voltage (Voc) Figure 7 demonstrates the open circuit voltage of all different structures as a function of the back contact size. The graph is referred to a specific contact size of 50μm, but it is also valid for the other ones since our simulations have shown that the influence of back contact spacing l on Voc is negligible, while base thickness is 200μm, as in the previous section. We observe that in contrast to the short circuit current, the back point junction device has the highest open circuit voltage compared to the other solar cell structures.
K. Kotsovos and K. Misiakos 684
front junction dev. double junction dev. back junction dev. point junction dev.
680 676
Voc(mV)
672
1.078 1.071 1.065 1.059
3D to 1D ratio
66
668
1.052
664
1.046
660
1.040
656
1.034
652
1.027
648
1.021
644
0.1
0.2
0.3
0.4
0.5
1.015
d/l Figure 7. Open circuit voltage (Voc) of all different point contact structures versus back contact size. The right axis is the current normalized to the corresponding value of the conventional 1D structure. Base thickness is 200μm and Ln=800μm.
The improved open circuit voltage may be attributed to the reduced surface recombination of the point junction structure, since the minimization of the area of the diffused regions is required to maximize the voltage [5], so Voc is improved at a faster rate compared to the other devices when the d/l ratio is reduced. The Voc of the front junction solar cell follow the corresponding point junction equivalent due to the low back surface recombination, while the back junction structure Voc values are slightly lower compared to the front junction cell. Finally, the double junction device has the lowest open circuit voltage of all point contact structures as expected, due to recombination in both emitters.
III. 3. Base Series Resistance (Rs) Figure 8 shows the base series resistance of the back junction structure near the cell maximum power point as a function of the back base contact size and its spacing as parameter when base thickness is 200μm. This graph shows that decreasing contact size leads to greater series resistance that grows dramatically for the smallest back contact area coverage fraction due to the current crowding at the back contact, as already reported for the front [9, 15,16] and double junction rear point contact solar cells [12]. In addition, the reduction of the back contact spacing limits the series resistance considerably. The current crowding effect is more evident in figure 9, where the series resistance of the back point junction structure is shown. It can be observed that there is an almost ten-fold increase to the Rs value for the smallest d/l ratio when the back contact spacing is changed from 50μm to 400μm. A rapid reduction of Rs is also observed when the back-diffused coverage ratio is increased.
Three-Dimensional Simulation of Base Carrier Transport Effects…
67
Figure 10 shows the series resistance dependence on the d/l ratio of the four different structures when the base contact spacing is 400μm. The simulations are performed for devices with different thickness, 200μm and 400μm respectively. 0.25
l=400μm l=200μm l=50μm
2
Rs (Ohm.cm )
0.20 0.15 0.10 0.05 0.00
0.1
0.2
0.3
0.4
0.5
d/l Figure 8. Base series resistance of the back junction structure near the cell maximum power point as a function of the back base contact size and its spacing as parameter. Base thickness is 200μm and Ln=800μm.
0.35
l=400μm l=200μm l=50μm
0.30
2
Rs (Ohm.cm )
0.25 0.20 0.15 0.10 0.05 0.00
0.1
0.2
0.3
0.4
0.5
d/l Figure 9. Base series resistance of the point back junction structure near the cell maximum power point as a function of the back base contact size and its spacing as parameter. Base thickness is 200μm and Ln=800μm.
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K. Kotsovos and K. Misiakos 0.35
22.88
2
Rs (Ohm.cm )
0.30 0.25
19.61 16.34
0.20
13.07
0.15
9.80
0.10
6.54
0.05
3.27
0.00
0.1
0.2
0.3
0.4
0.5
3D to 1D ratio
front junction device double junction device back junction device point junction device
0.00
d/l A 10.50
front junction device double junction device back junction device point junction device
0.295
2
Rs (Ohm.cm )
0.246
9.00 7.50
0.197
6.00
0.148
4.50
0.098
3.00
0.049
1.50
0.000
0.1
0.2
0.3
0.4
0.5
3D to 1D ratio
0.344
0.00
d/l B Figure 10. Series resistance of the four different structures versus d/l ratio when the base contact spacing is 400μm, Ln=800μm and different base thickness: (A) 200μm and (B) 400μm. The right hand axis is the series resistance normalized to the corresponding value of the typical solar cell structure (1D case).
The right hand axis is the series resistance normalized to the corresponding value of the typical solar cell structure (1D case). In this case the back junction device exhibits the lowest Rs, while the corresponding series resistance of the double junction structure is slightly higher. On the contrary, the single front and point junction devices exhibit the highest Rs values. The series resistance of the front junction structure is significantly influenced from the base thickness in contrast to the rest of the point contact cells, except for the case of the smallest contact coverage fraction. Therefore, it can be concluded that the series resistance of the front junction cell is significantly influenced by the majority carrier flow in the vertical (z) direction. In most cases the conventional structure (1D) has the lowest series resistance, except for the largest d/l ratio, where the back and double junction structure Rs values are smaller. The situation is different in figure 11, which is the same plot as of figure 10 where the back contact spacing is reduced to 50μm.
Three-Dimensional Simulation of Base Carrier Transport Effects…
front junction device double junction device back junction device point junction device
0.045
2
Rs (Ohm.cm )
0.040 0.035
3.27 2.94 2.61 2.29
0.030
1.96
0.025
1.63
0.020
1.31
0.015
0.98
0.010
0.65
0.005
0.33
0.000
0.1
0.2
0.3
0.4
0.5
3D to 1D ratio
0.050
69
0.00
d/l A 3.05
front junction device double junction device back junction device point junction device
0.09
2
Rs (Ohm.cm )
0.08 0.07
2.74 2.44 2.13
0.06
1.83
0.05
1.52
0.04
1.22
0.03
0.91
0.02
0.61
0.01
0.30
0.00
0.1
0.2
0.3
0.4
0.5
3D to 1D ratio
0.10
0.00
d/l B Figure 11. Series resistance of the four different structures versus d/l ratio when the base contact spacing is 50μm, Ln=800μm and different base thickness: (A) 200μm and (B) 400μm. The right hand axis is the series resistance normalized to the corresponding value of the typical solar cell structure (1D case).
In this case, the back and point junction structures show the smallest Rs values, with the back junction one having the lowest. The Rs of the double junction solar cell is slightly higher in almost all cases compared to the previous structures and it is significantly reduced when the base thickness is changed from 400μm το 200μm. This is an indication that this device is also influenced by the majority carrier flow in the vertical direction as already reported. On the contrary, the series resistance of the front junction structure is by far the highest of all, approaching the limit of the conventional 1D device for large back contact coverage fractions. This may be attributed to the fact that in the front junction and the conventional solar cell devices the emitter and back contact are located on different surfaces and minority and majority carriers move to opposite directions, thus minority carrier flow opposes majority carrier movement, while in the back and point junction devices, the diffused regions lie in the same surface, so both minority and majority carriers flow towards the back surface. Therefore in this case, the reduced series resistance values of the back and point junction structures, is a
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K. Kotsovos and K. Misiakos
clear advantage for concentrator applications, where ohmic losses need to be minimized, due to the high current generated by the solar cell. The double junction structure is also a good potential candidate for such applications since its series resistance is also low. It must be additionally noted, that all structures except from the single front junction one, may reach much lower Rs values compared to the conventional 1D device.
III. 4. Maximum Efficiency (η) Figure 12 shows the dependence of the back contact size on the back junction cell’s maximum efficiency with the contact spacing as a parameter. The plots demonstrate that there is a significant increase of the efficiency when the contact size decreases, provided that the d/l ratio is not less than 0.2, while with a further decrease of the back contact spacing shifts the efficiency to a smaller d/l ratio. According to the discussion of the previous sections, the reduction of the back contact size results to lower back contact recombination, so the open circuit voltage and the short circuit current are improved. On the other hand, a minimization of the back contact coverage fraction results to an intense current crowding effect, where the series resistance is significantly increased (figure 8), thus limiting the efficiency. The reduction of the back contact spacing limits this effect, so efficiency is improved. 22.8
efficiency (%)
22.6 22.4 22.2 22.0
d=400μm d=200μm d=50μm
21.8 21.6 0.1
0.2
0.3
0.4
0.5
d/l Figure 12. Maximum conversion efficiency of the back junction structure near the cell maximum power point as a function of the back base contact size and its spacing as parameter. Base thickness is 200μm and Ln=800μm.
Figure 13 illustrates the corresponding efficiency plots of the point back junction solar cell. In contrast with the previous figure, the efficiency of this structure is improved by increasing the back-diffused regions coverage, since in this case the photocurrent is enhanced as shown on figure 4, while series resistance is reduced. However, when back contact spacing is 50μm the device efficiency is improved when the d/l ratio is reduced from 0.5 to 0.2. In addition, when the back contact spacing is large (400μm) and the d/l ratio is 0.1 the efficiency is greatly reduced. This is due to the current crowding effect, which not only increases the
Three-Dimensional Simulation of Base Carrier Transport Effects…
71
series resistance but also requires a significantly larger minority carrier diffusion length for efficient carrier collection, as already discussed [5]. 23 22
efficiency (%)
21 20 19 18
d=400μm d=200μm d=50μm
17 16 15
0.1
0.2
0.3
0.4
0.5
d/l
23
1.07
22
1.02
21
0.97
20
0.93
19
0.88
18
front junction device double junction device back junction device point junction device
17 16 15
0.1
0.2
0.3
0.4
0.5
0.83 0.79
3D to 1D ratio
efficiency (%)
Figure 13. Maximum conversion efficiency of the back point junction structure near the cell maximum power point as a function of the back base contact size and its spacing as parameter. Base thickness is 200μm and Ln=800μm.
0.74 0.70
d/l Figure 14. Efficiency of the four different structures versus d/l ratio when the base contact spacing is 400μm. The right hand axis is the series resistance normalized to the corresponding value of the typical solar cell structure (1D case). Base thickness is 200μm and Ln=800μm.
Figure 14 compares the efficiency dependence on the d/l ratio of the four different structures, when the base contact spacing is 400μm. The right hand axis is the efficiency normalized to the corresponding value of the typical solar cell structure (1D case). The plots show that the efficiency of the back and point junction solar cell devices is significantly lower due to less efficient carrier collection, since the emitter of both structures
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K. Kotsovos and K. Misiakos
is located on the back surface. As already discussed, the efficiency of the point junction solar cell is severely limited by current crowding. The highest performing structures are the single front and double junction solar cells, which have almost the same efficiency. Figure 15 is the same plot as of figure 10 calculated for reduced the back contact spacing to 50μm. As expected, the efficiency of all structures (except from the conventional solar cell) is improved and especially the corresponding point junction one. The best performing structures are still the single front and double junction solar cells, where the single front junction cell edges out the corresponding double junction one for small contact sizes. The efficiency of the back and point junction solar cell devices is still lower, where the back junction structure has the best efficiency of these two.
23.4
efficiency (%)
23.2
1.09 1.08
23.0
1.07
22.8
1.06
22.6
1.05
22.4
1.04
22.2
1.03
22.0
1.02
3D to 1D ratio
front junction device double junction device back junction device point junction device
1.01
21.8 0.1
0.2
0.3
0.4
0.5
d/l Figure 15. Efficiency of the four different structures versus d/l ratio when the base contact spacing is 50μm. The right hand axis is the series resistance normalized to the corresponding value of the typical solar cell structure (1D case). Base thickness is 200μm and Ln=800μm.
It should be pointed out, however that no front surface reflection is assumed for all devices and in reality all devices except from the back and point junction ones have additional losses due to front grid shadowing, which limits significantly their efficiency. On the other hand, larger diffusion lengths would greatly improve the performance of back and point junction solar cells; therefore the influence of this parameter is investigated in the next section.
III. 5. Minority Carrier Diffusion Length Influence on Device Short Circuit Current, Open Circuit Voltage and Efficiency Figure 16 shows the short circuit current of all different structures, including the conventional 1D solar cell, versus minority carrier base diffusion length (Ln). The calculations are performed for device thickness 200μm and 400μm.
Three-Dimensional Simulation of Base Carrier Transport Effects…
73
42 41
39
2
Jsc (mA/cm )
40
38 37
Front junction device Double junction device Back junction device Point junction device Conventional device
36 35 34 33
400
600
800
1000
1200
1400
1600
Ln (μm) A 42
2
Jsc (mA/cm )
40 38 36 34 32
front junction device double junction device dack junction device point junction device conventional device
30 28 26 24
400
600
800
1000
1200
1400
1600
Ln(μm) B Figure 16. Short circuit current of all different back point contact structures, including the conventional 1D solar cell versus minority carrier base diffusion length (Ln) and different base thickness: (A) 200μm and (B) 400μm. The simulations are performed for the smallest contact spacing of 50μm for improved efficiency, while point contact side length in (A) and (B) is set as 16μm and 10μm respectively.
The simulations are performed for the smallest contact spacing of 50μm for improved efficiency, while point contact side length is considered as 16μm and 10μm for figure 16(A) and 16(B) respectively, as a good balance between back surface recombination and series resistance. As expected the short circuit current of the double junction solar cell is the highest, due to the enhanced carrier collection of the back emitter [12,17], which remains almost constant for the considered diffusion lengths. The Jsc of the single front junction solar cell is near to the levels of the previous structure when Ln is greater or equal than 800μm, followed by the conventional 1D structure, where there is negligible photocurrent improvement when Ln is increased. In contrast to the former structures, the back and point junction solar cells benefit a lot from the diffusion length increase, since in this case the minimization of bulk recombination results to greatly improved carrier collection. This is more evident in the case of the smaller base thickness (200μm).
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K. Kotsovos and K. Misiakos
Voc(mV)
Figure 17 shows the open circuit voltage of all different structures versus minority carrier base diffusion length (Ln) in the same manner as of previous figure.
705 700 695 690 685 680 675 670 665 660 655 650 645 640 635 630 625
Front junction device Double junction device Back junction device Point junction device Conventional device
400
600
800
1000
1200
1400
1600
Ln (μm) A 680 670
Voc (mV)
660 650 640 front junction dev. double junction dev. back junction dev. point junction dev. conventional dev.
630 620 610
400
600
800
1000
Ln(μm)
1200
1400
1600
B Figure 17. Open circuit voltage of all different back point contact structures, including the conventional 1D solar cell versus minority carrier base diffusion length (Ln). Other simulation parameters are the same as of figure 16.
As already discussed in section III.2, the limited front and back surface recombination of the point junction structure, is the cause of the improved open circuit voltage compared to the other solar cells. However, when Ln and base thickness is 400μm, bulk recombination limits the Voc of the former as well as of the back junction structure to values lower than the other structures. On the contrary, for the greatest Ln value of figure 17 the open circuit voltage gain of the point junction solar cell compared with the corresponding front junction equivalent is almost 10mV when w=400μm and exceeds 20mV when w=200μm. The Voc of the back junction structure almost equals or exceeds the corresponding front junction one for diffusion
Three-Dimensional Simulation of Base Carrier Transport Effects…
75
efficiency (%)
lengths greater than 800μm and w=200μm, while the voltage of the double junction structure is significantly lower compared to the three previously referred solar cells due to front and back emitter recombination. The conventional structure shows the most limited open circuit voltage, which is more than 35mV lower than the corresponding back point junction one when Ln is 1600μm and w=400μm, while this difference is increased to 60mV when w=200μm.
24.5 24.0 23.5 23.0 22.5 22.0 21.5 21.0 20.5 20.0 19.5 19.0 18.5 18.0 17.5
Front junction (shading loss) Double junction (shading loss) Conventional (shading loss)
Front junction device Double junction device Back junction device Point junction device Conventional device
400
600
800
1000
1200
1400
1600
Ln (μm) A Front junction (shading loss) Double junction (shading loss) Conventional (shading loss)
24
efficiency (%)
22 20 18 Single junction device Double junction device Back junction device Point junction device Conventional device
16 14 12
400
600
800
1000
1200
Ln (μm)
1400
1600
B Figure 18. Conversion efficiency of all different back point contact structures, including the conventional 1D solar cell versus minority carrier base diffusion length (Ln). Other simulation parameters are the same as of figure 16 and 17. The open-symbol colored plots refer to the front, double and the conventional solar cell structures when a 4% front grid shading loss is taken into account.
Finally, figure 18 shows the conversion efficiency of all different structures as a function of the minority carrier base diffusion length (Ln) in the same manner as of figures 16 and 17.
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K. Kotsovos and K. Misiakos
As expected the point and back junction structures benefit the most from the diffusion length increase due to more efficient carrier collection, where for diffusion lengths greater than 800μm their efficiencies are almost equal, while the efficiency of the point junction solar cell exceeds the corresponding back junction one by a small margin when Ln=1600μm and w=400μm. In addition when w=400μm, these structures show superior performance compared to the conventional solar cell, when Ln=1200μm or larger, while for the largest diffusion length value of the graph, their efficiencies approach the levels of the single front and double junction ones. This small efficiency premium (approximately 0.5% absolute for the case of the single front junction cell and 0.34% for the double junction equivalent) is eliminated if front surface grid shadowing is taken into account, as shown on the graphs where a 4% shading loss is assumed. In this case, the back and point junction solar cells exhibit the highest efficiencies when Ln is greater than 1200μm (Ln/w>3). If the device thickness is reduced to 200μm and base diffusion length is greater than 1200μm (Ln/w>6), the point junction cell shows the highest efficiency of all structures, neglecting shadowing losses. When grid shadowing is set to 4%, the back and point junction structures reach higher efficiencies compared to the single and double junction solar cells for diffusion lengths greater than 800μm (Ln/w>4). Therefore, the choice of thin, high quality silicon wafers is absolutely necessary for the fabrication of the back and point junction solar cells. Topsil produces such FZ wafers with minority carrier lifetimes greater than 1ms for use in the PV industry [18], while wafers grown under the MCZ method (magnetically confined Czochralski) that are already used for the fabrication of high efficiency PERL structures [19] are good candidates as a starting material and they cost less than electronic quality FZ wafers.
IV. CONCLUSION In this work back junction, point contact (locally diffused) solar cells have been investigated through 3D simulations and compared with corresponding single front junction, double junction as well as conventional (1D) solar cell devices. It was shown that the simulated base series resistance of the back junction structure reached significantly lower values compared to the single front and double junction devices, especially for small back contact spacing. The back point junction solar cell reached the highest open circuit voltage due to reduced surface recombination, although current-crowding effects would severely affect its efficiency by reducing the solar cell’s photocurrent and increasing the base series resistance if the diffused areas are too small or too remotely spaced. A proper choice of back diffused contact spacing and size, would result to low Rs, close to the values of the back junction structure. Therefore, these cells are preferable for concentrator applications, since their efficiency would be significantly less affected from resistive losses compared to the single front junction back point contact solar cell and the conventional device. However, high quality starting material and relatively thin substrates (Ln/w>4) are required so that these devices reach efficiencies significantly higher than the conventional 1D device and close to or higher than the single front or double junction structure. On the other hand, the double junction solar cell could also be proposed as a very good choice for all applications, since it performs marginally lower compared to the corresponding front junction one on high quality substrates, and it has the best efficiency on low quality ones. In addition its simulated base series resistance reached values near to those of the back junction solar cells.
Three-Dimensional Simulation of Base Carrier Transport Effects…
77
REFERENCES [1] [2] [3]
[4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19]
R. A.Sinton, Y. Kwark, J. Y. Gan, R. M. Swanson, IEEE Electron Device Lett., Vol. 7 (10), p.1855, 1986. R. A. Sinton and R. M. Swanson, IEEE Trans. on Electron Devices, Vol. 37 (10), p.348, 1990. W. Mullikan, D. Rose, M. J. Cudzinovic, D. M. De Ceuster, K. R. McIntosh, David D. Smith, and R. M. Swanson, Proceedings of the 19 EPVSEC, Paris, France, p. 387, 2004. R. M. Swanson, EPRI Rep., AP-2859, 1983. R. M. Swanson, Solar Cells, Vol. 17, p. 85, 1986. D. J. Chin and Navon D. H., Solid State Electron., Vol. 24, p.109, 1981. H. Ohtsuka, Y. Ohkura, T. Uematsu and T. Warabisako, Prog. Photovoltaics: Res. Appl., Vol. 2, p. 275, 1994. Nichiporuk O., Kaminski A., Lemiti M., Fave A. and Skryshevski V, Sol. Energy Mat. and Sol. Cells, 86, p. 517, 2005. K. Kotsovos and K. Misiakos, J. Appl. Phys., Vol. 89, p. 2491, 2001. J. Zhao, A. Wang, P. Altermatt and M. A. Green, Appl. Phys. Lett., Vol. 66 , p. 3646, 1995. Zhao J., Wang A., και Green M. A., Progr. In Photovoltaics: Res. Appl., Vol. 7, p. 471, 1999. K. Kotsovos and K. Misiakos, Sol. En. Mat. and Sol. Cells, Vol. 77, p. 209, 2003. D.B.M. Klaassen, Solid-State Electronics, Vol. 35, p. 953, 1992. R. Hulstrom R. Bird and C. Riordan, Solar Cells, Vol. 15, p. 365, 1985. Zhao J., Wang A., and Green M. A., Sol. Energy Mat. and Sol. Cells,Vol. 32, p. 89, 1994. Catchpole K. R. and Blakers A. W., Sol. Energy Mat. and Sol. Cells, 73, p. 189, 2002. E. Van Kerschaver, C. Zechner, and J. Dicker, IEEE Trans. El. Devices, Vol. 47 (4) , p. 711, 2000. Vedde J., Jensen L., Larsen T. and Klausen T., Proceedings of the 19 EPVSEC, Paris, France, p. 1075, 2004. Zhao J., Wang A. and Green M. A., Progr. In Photovoltaics: Res. Appl., Vol. 8, p. 549, 2000.
APPENDIX A. LIGHT GENERATION PROFILE MODEL The surface of the simulated devices is textured as shown in figure A.1. The back surface is assumed reflective with a constant reflection coefficient Rb. This light-trapping scheme improves the absorbing properties of the investigated material, since incoming rays enter the cell with an angle of incidence, which is different than normal, so the material absorption coefficient αi is increased according to the following relation.
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θ Figure A.1. Assumed light trapping scheme used for the model calculations.
α ieff =
αi sin θ
(A.1)
where αieff is the effective material absorption coefficient under a given wavelength, while θ is the angle shown in figure A.1. Assuming that photon flux decays exponentially with increasing depth and that light is coupled out after performing a double pass across the cell, then the photon generation rate which is independent from x and y directions for all wavelengths of the considered AM1.5 spectrum, is written as N −1
G ( z ) = ∑ (α ieff g i e
−α ieff z
i =1
+ Rb e
−α ieff w
α ieff g i e
−α ieff ( w − z )
N −1
) Δλ i = ∑ Gi ( z )
(A.2)
i =1
where gi is the number of generated electron-hole pairs for the given wavelength i. By substituting in (A.2), the generation rate in front and back surface are obtained N −1
G (0) = ∑α ieff g i (1 + Rb e
− 2α ieff w
i =1
N −1
G ( w) = ∑ α ieff g i (e i =1
−α ieff w
N −1
)Δλi = ∑ Gi (0)
(A.3)
i =1
+ Rb e
−α ieff w
N −1
) Δλi = ∑ Gi ( w) i =1
(A.4)
The differentiation of (A.2) provides the following expression N −1 dG ( z ) N −1 −α z −α w −α ( w − z ) 2 = ∑ − α ieff g i (e ieff − Rb e ieff e ieff ) Δλ i = ∑ ΔGi ( z ) dz i =1 i =1
(A.5)
while the corresponding values for both surfaces are
dG ( z ) dz
N −1
z =0
2 = ∑ − α ieff g i (1 − Rb e i =1
− 2α ieff w
N −1
)Δλi = ∑ ΔGi (0) i =1
(A.6)
Three-Dimensional Simulation of Base Carrier Transport Effects…
dG ( z ) dz
N −1
z=w
2 = ∑ − α ieff g i (e i =1
−α ieff w
− Rb e
−α ieff w
N −1
)Δλ i = ∑ ΔGi ( w)
79 (A.7)
i =1
The expressions (A.2)-(A.7) will be used in the following sections for the solution of the transport equations.
APPENDIX B. SOLUTION OF THE MINORITY CARRIER CONTINUITY EQUATION Performing a two-dimensional Fourier Transform on equation (1) the following expression is obtained:
d 2n~(k x , k y , z ) dz 2 where
= (k x2 + k y2 +
~ G( z) 1 ~ n k k z ) ( , , ) − x y L2n Dn
(B.1)
~ n~ (k x , k y , z ), G ( z ) are the Fourier transforms with respect to x, y of
n( x, y, z ), G ( z ) respectively. This is an ordinary differential equation with independent variable z, which has the following general solution:
~ G( z) R1 z − R1 z ~ n (k x , k y , z ) = A(k x , k y )e + B (k x , k y )e + k1 Dn where R1 =
k x2 + k y2 + 1
L2n
(B.2)
and k1 is determined by differentiating (B.2) with respect to z
twice and equating the result with the right part of (B.1). By performing the necessary operations and with the use of (A.2) we get N −1
n~ (k x , k y , z ) = A(k x , k y )e − R1z + B(k x , k y )e R1z + ∑ i =1
~ Gi ( z ) 2 Dn ( R12 − α ieff )
(B.3)
The solution defined by (B.3) incorporates the constants A and B, which should be determined through the boundary conditions. These constants may be expressed as functions
~ (k , k ,0), n~ (k , k , w) in the following way: of n x y x y
A( k x , k y ) =
~ N −1 ~ G ( w) − Gi (0)e R1w n~ (k x , k y ,0)e R1w − n~ (k x , k y , w) + ∑ i 2 Dn ( R12 − α ieff ) i =1 e R1w − e − R1w
(B.4)
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K. Kotsovos and K. Misiakos
B (k x , k y ) =
~ N −1 ~ Gi (0)e − R1w − Gi ( w) − R1w ~ ~ n ( k x , k y , w) − n ( k x , k y ,0)e +∑ 2 ) Dn ( R12 − aieff i =1
(B.5)
e R1w − e − R1w
~
~
where G (0), G ( w) are the carrier generation rates in the front and back surface respectively and are given by (A.3) and (A.4). The minority carrier diffusion current can be obtained by differentiating (B.3) with respect to z
~ J n (k x , k y , z ) eDn
=
dn~ (k x , k y , z ) dz
(
=
R1 B (k x , k y )e R1z − A(k x , k y )e − R1z
)
(B.6)
~ ΔGi ( z ) +∑ 2 2 i =1 D n ( R1 − α ieff ) N −1
After substituting (B.4) and (B.5) in (A.6) we get the final expressions for the current in both surfaces: ~ J n (kx , k y ,0) eDn
(
= R1
)
~ N −1 ~ G (0) eR1w + e−R1w − 2Gi (w) 2n~(kx , k y , w) − n~(kx , ky ,0)(eR1w + e−R1w ) + ∑ i 2 Dn (R12 −αieff ) i =1 eR1w − e−R1w
~ ΔGi (0) +∑ 2 2 i =1 Dn (R1 −αieff )
(B.7)
N−1
~ Jn (kx , ky , w) eDn
(
= R1
eR1w −e−R1w
~ ΔGi (w) +∑ 2 2 i=1 Dn (R1 −αieff) N−1
~
)
~ N−1 ~ 2Gi (0) − eR1w +e−R1w Gi (w) R1w −R1w ~ ~ n(kx , ky , w)(e +e ) −2n(kx , ky ,0) +∑ 2 Dn (R12 −αieff ) i=1 (B.8)
~
where ΔGi (0), ΔGi ( w) are defined in (A.6) and (A.7). The expressions (B.7) and (B.8) may be used to calculate the minority carrier diffusion currents in Fourier space as a function of the corresponding surface concentrations. The opposite procedure could be performed by solving the system of (B.7) and (B.8) to obtain the transformed surface minority carrier concentrations as a function of the corresponding diffusion currents
Three-Dimensional Simulation of Base Carrier Transport Effects…
n~(k x , k y ,0) =
N −1 ~ − J n (k x , k y ,0) + ∑ i =1
~ ΔGi (0) 2 Dn ( R12 − α ieff )
R1
N −1 ~ J n (k x , k y , w) − ∑
coth(R1 w) +
~ ΔGi ( w) 2 Dn ( R12 − α ieff )
~ N −1 Gi (0) 1 +∑ 2 R1 sinh(R1 w) i =1 Dn ( R12 − α ieff ) ~ N −1 ΔGi (0) ~ − J n (k x , k y ,0) + ∑ 2 2 i =1 Dn ( R1 − α ieff ) 1 n~(k x , k y , w) = + R1 sinh(R1 w) ~ N −1 ΔGi (w) ~ J n (k x , k y , w) − ∑ ~ 2 2 N −1 Gi (w) i =1 Dn ( R1 − α ieff ) coth(R1 w) + ∑ 2 2 R1 i =1 Dn ( R1 − α ieff ) i =1
81
(B.9)
(B.10)
The expressions (B.7)-(B.10) are used to solve the diffusion equation by application of the algorithm described in section II.4.1.
APPENDIX C. SOLUTION OF THE MAJORITY CARRIER VOLTAGE DROP EQUATION A similar analysis is used for the solution of equation (9), so by performing a twodimensional Fourier Transform in (9) and using (B.3) we get ~ d 2V ( k x , k y , z ) dz
2
~ = R 2V (k x , k y , z ) +
~ ⎞⎞ Dn − D p ⎛⎜ A(k x , k y )e − R1z + B ( k x , k y )e R1z N −1 Gi ( z ) ⎛ 1 ⎜ ⎟⎟ + − 1 ∑ 2 ⎜ 2 2 ⎟⎟ μ p N A ⎜⎝ L2n i =1 D n ⎝ Ln ( R1 − α ieff ) ⎠⎠
where R =
(C.11)
k x2 + k y2 .This ordinary differential equation has the following general solution
when R≠0 ~ V (k x , k y , z) = A1 (k x , k y )e − Rz + B1 (k x , k y )e Rz + ~ ⎞⎞ ⎛ Dn − D p ⎛⎜ c1 A(k x , k y )e − R1z + c2 B(k x , k y )e R1z N −1 c3 G 1 i ( z) ⎜ + − 1⎟ ⎟ ∑ 2 2 2 2 ⎜ ⎜ μpNA ⎝ Dn ⎝ Ln ( R1 − α ieff ) ⎟⎠ ⎟⎠ Ln i =1
(C.12)
where c1, c2, c3 are constants, which can be calculated by differentiating (C.12) with respect to z twice and equating the result with the right part of (C.11). Therefore, by completing these operations the general solution may written in the following form
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K. Kotsovos and K. Misiakos
D p − Dn ~ ~ V (k x , k y , z ) = A1 (k x , k y )e − Rz + B1 ( k x , k y )e Rz + n (k x , k y , z ) μpNA
(C.13)
The constants A1 and B1 may be expressed as a function of the transformed surface voltage distributions in a similar manner as that of previous section
A1 (k x , k y ) =
B1 (k x , k y ) =
~ ~ V (k x , k y ,0)e Rw − V (k x , k y , w) + k1 (n~(k x , k y ,0)e Rw − n~(k x , k y , w)) e Rw − e −Rw ~ ~ V (k x , k y , w) − V (k x , k y ,0)e− Rw + k1 (n~(k x , k y , w) − n~(k x , k y ,0)e− Rw )
(C.14)
e Rw − e−Rw (C.15)
where k1 =
Dn − D p
μpNA
. The electric field can be calculated through differentiation of (C.13)
with respect to z, as following
~ dV (k x , k y , z ) dn~ ( k x , k y , z ) ~ = R A1 (k x , k y )e − Rz − B1 (k x , k y )e Rz + k1 E (k x , k y , z ) = − dz dz ~ J n (k x , k y , z) = R A1 (k x , k y )e − Rz − B1 (k x , k y )e Rz + k1 eDn
(
(
)
)
(C.16) The substitution of (C.14) and (C.15) in (C.16) leads to the following expressions for the electric field on both surfaces as a function of the corresponding voltage distributions
~ ⎛ ~ V (kx , k y , w) + k1n~(kx , k y , w) ⎞ ~ ~ ⎟+ ⎜ E (kx , k y ,0) = R V (kx , k y ,0) + k1n (kx , k y ,0) coth(Rw) − ⎟ ⎜ sinh ( ) Rw ⎠ ⎝ ~ J (k , k ,0) k1 n x y eDn
(
)
~ ⎞ ⎛ V (k x , k y ,0) + k1n~(k x , k y ,0) ~ ~ E(k x , k y , w) = R⎜ − V (k x , k y , w) + k1n~(k x , k y , w) coth(Rw) ⎟ + ⎟ ⎜ sinh(Rw) ⎠ ⎝ ~ J n (k x , k y , w) k1 eDn
(
(C.17)
)
(C.18)
Conversely, the surface voltage distributions may be related to the corresponding electric fields by using (C.17) and (C.18)
Three-Dimensional Simulation of Base Carrier Transport Effects…
~ J n (kx , k y ,0) ~ E(k x , k y ,0) − k1 eDn ~ coth(Rw) − V (kx , k y ,0) = R ~ J n (kx , k y , w) ~ E(kx , k y , w) − k1 eDn 1 − k1n~(kx , k y ,0) R sinh(Rw) ~ J n (kx , k y ,0) ~ E(kx , k y ,0) − k1 eDn 1 ~ V (k x , k y , w) = − R sinh(Rw) ~ J n (k x , k y , w) ~ E(kx , k y , w) − k1 eDn coth(Rw) − k1n~(kx , k y , w) R
83
(C.19)
(C.20)
Expressions (C.17)-(C.20) are valid when R≠0 and may be used to solve equation (9) by application of the algorithm described in section II.4.2. If R=0 the general solution of (9) is reduced to the following simple form
~ V (0,0, z ) = A1 (0,0) z + B1 (0,0) − k1n~ (0,0, z )
(C.21)
so the previously described procedure may be used to find the required relations for the electric field on both surfaces depending on the voltage distributions and conversely.
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 85-158
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 3
MULTIPLE EFFECT DISTILLATION OF SEAWATER WATER USING SOLAR ENERGY – THE CASE OF ABU DHABI SOLAR DESALINATION PLANT* Ali M. El-Nashar ADWEA Research Center, UAE
ABSTRACT This report describes the solar desalination test plant in Abu Dhabi, UAE and gives a summary of its first year performance and economics. The plant has been operating successfully for 18 years supplying fresh water to the City of Abu Dhabi. The plant was commissioned in September 1984 and was running until the year 2002 when it was dismantled after fulfilling its objectives. The aim of the plant is to investigate the technical and economic feasibility of using solar desalination of seawater in providing fresh water to remote communities in the Middle East and to obtain long-term performance and reliability data on the operation of the plant. The plant has proved its technical feasibility and proved to be reliable in operation with few minor maintenance problems that required slight plant modification. Maintenance routines were established to maintain high plant performance. The economic feasibility of the plant was established by comparing the cost of water from a solar MED plant with a conventional MED plant using fossil fuel for plant capacity ranging from 100 m3/day to 1000 m3/day. It was found that the cost of water from solar MED plants is competitive with that from a conventional MED plant if the cost fuel continues to rise.
Keywords: desalination, solar energy, solar desalination, economic feasibility, operating performance, solar distillation.
*
A version of this chapter was also published in Leading Edge Research in Solar Energy edited by P. N. Rivers published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research.
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Ali M. El-Nashar
1. INTRODUCTION Many remote areas of the world such as coastal desert areas in the Middle East or some Mediterranean and Caribbean islands are suffering from acute shortage of drinking water particularly during the summer season. Drinking water for these locations are normally hauled in by tankers or barges or produced by small desalination units using the available saline water. The transportation of water by tankers or barges involves a lot of expense and is fraught with logistical problems which can make fresh water not only very expensive when available but also its supply being very susceptible to frequent interruptions. The use of small conventional desalination units using a fossil fuel such as diesel oil as the energy supply can suffer from the same procurement problems that are encountered with transporting fresh water, namely transportation expenses and supply reliability. Some of the remote areas are blessed with abundant solar radiation which can be used as an energy source for small desalination units to provide a reliable drinking water supply for the inhabitants of the remote areas. Recently, considerable attention has been given to the use of solar energy as an energy source for desalination because of the high cost of fossil fuel in remote areas, difficulties in obtaining it, interest in reducing air pollution and the lack of electrical power source in remote areas. Desalination of seawater and brackish water is one of the ways for meeting future fresh water demand. Conventional desalination technology is fairly well established, and some of the processes may be considered quite mature although there is still considerable scope for improvement and innovation. Conventional desalination processes are energy intensive, and one of the major cost items in operating expenses of any conventional desalination plant is the energy cost. Thus, one of the major concerns about using desalination as a means of supplying fresh water to remote communities is the cost of energy. Apart from energy cost implications, there are environmental concerns with regard to the effects of using conventional energy sources. In recent years it has become clear that environmental pollution caused by the release of green house gases resulting from burning fossil fuels is responsible for ozone depletion and atmospheric warming. The need to control atmospheric emissions of greenhouse and other gases and substances will increasingly need to be based on growing reliance on renewable sources of energy.
Figure 1. Picture of Abu Dhabi solar desalination plant.
Multiple Effect Distillation of Seawater Water Using Solar Energy …
87
A solar-assisted desalination plant was designed, constructed and put into operation on September 1984 as part of a cooperative research program between Japan and the United Arab Emirates (UAE) to test the technical and economic feasibility of using solar energy for desalination of seawater[1,2,3,4]. The plant (see figure 1) has been in operation in a Umm Al Nar near Abu Dhabi City until the year 2002 when it was dismantled. This report describes the main features of the first year of operation and compares its economics with conventional systems using the same desalination technology.
2. HISTORY OF ABU DHABI SOLAR DESALINATION PLANT In July 1979, when Mr. Ezaki, the then Japanese Minister of International Trade and Industry, visited the United Arab Emirates (UAE) and discussed the utilization of solar energy utilization in the UAE with Dr. Mana Saeed Al-Otaiba, the UAE Minister of Petroleum and Mineral Resources, they agreed on a joint project between the two countries to develop solar energy utilization for desalination of seawater. Under this agreement, several discussions were held at various levels. On January 22, 1983, the Record of Discussion (ROD) was finally signed for the joint implementation of a Research and Development Cooperation on Solar Energy Desalination Project by the New Energy Development Organization (NEDO) in Japan, and the Water and Electricity Department in the Abu Dhabi Emirate of the UAE[5]. An outline of the ROD is as follows: • • • • •
Execusion period of the project is 3 years starting January 22, 1983 Location of the project is Umm Al Nar in the suburbs of Abu Dhabi City Product water capacity of the test plant has a yearly average value of 80 m3/day Research operation period of the test plant is one year Japanese project executor: Engineering Advancement Association of Japan (ENAA)
The design, procurement and fabrication of the test plant started in February 1983 and the test plant was completed in October 1984. For the following year, research operation on the test plant was jointly conducted by ENAA and WED and was concluded in October 1985. Upon completion of the cooperative research project, the test plant was put in operation and was used as a research tool for a number of research projects carried out by WED. The plant was decommissioned in June 2002 after successfully operating for 18 years producing fresh water to Abu Dhabi City.
3. DESCRIPTION OF ABU DHABI SOLAR DESALINATION PLANT The solar desalination plant is designed for an expected yearly average fresh water production of 80 m3/day. A simplified schematic of the plant is shown in Figure 2.A bank of evacuated tube solar collectors, whose orientation with respect to the sun has been optimized to collect the maximum amount of solar radiation, is used to heat the collector fluid to a maximum temperature of about 99oC. The effective collector area of this bank is 1862 m2.
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The heat collecting water leaving the collector bank flows into the top of the heat accumulator which has a total capacity of 300 m3. The heat accumulator is of the thermally stratified liquid type where, by virtue of density variation between the top and bottom layers, the higher temperature water is located in the upper region of the accumulator tank while the lower temperature water occupies the lower region. The lower temperature water is drawn from the tank bottom and pumped through the collectors by the heat collecting pump which has a capacity of 80m3/hr at 26m discharge head. The heat collecting water is drawn from the top of the accumulator tank by the heating water circulating pump and is forced to flow into the heating tubes of the first effect of the MED evaporator. This evaporator is designed for a maximum distillate production of 120m3. By transferring heat to the cooler brine flowing on the outside of the tubes, the heating water is cooled down and is then discharged into the accumulator.
Figure 2. A simplified schematic of the solar desalination plant.
The MED evaporator has 18 effects stacked one on top of the other with the highest temperature effect (No. 1) located at the top of the stack and the lowest temperature effect (No. 18) located at the bottom. The 18 effects are actually arranged in a double-stack configuration where effects 1, 3, 5,….17 are in one stack and effects 2, 4, 6…18 in the second. The double-stack arrangement is incorporated into one evaporator vessel as will be shown in detail later. In addition to the 18 effects, the evaporator has a final condenser designed to condense the vapor generated in the bottom (last) stage (No. 18). Heat input supplied to the first effect by the heating water is repeatedly used by evaporating a portion of the brine flowing into each effect. The evaporator operates under vacuum that is effected by a positive displacement pump connected to the final condenser. The absolute pressure to be maintained in the final condenser is designed to be 50 mmHg. The pressure to be maintained in each effect varies from slightly below atmospheric in the first effect to about 50 mmHg in the 18th effect. Seawater is used to condense the vapor generated in the 18th effect. Part of the discharged warm seawater leaving the final condenser returns to the sea, while the other part constitutes the evaporator feedwater. The feedwater flow rate amounts to 17.3 m3/hr; it flows through 17
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preheaters before reaching the first effect, one preheater for each effect except the 18th effect. These preheaters are designed to raise the feedwater temperature incrementally by flowing from the bottom effect (No. 18) to the top effect (No.1).
3.1. Plant Description 3.1.1. The Solar Heat Collector Subsystem The solar energy collecting system (SECS) has the function of collecting the solar energy when it is available during the day using the collector bank and storing this energy in the heat accumulator which supplies thermal energy to the evaporator with minimum fluctuations in the supply temperature. This is desirable since steady state operation of the evaporator near its optimum operating condition is highly recommendable. The basic unit in the collector bank is the Sanyo evacuated tube solar collector which is shown in isometric in figure 3. This is a flat plate-type collector that employs selective coating absorber plates enclosed in glass tubes maintained under high vacuum of 10-4 mm Hg. Ten glass tubes with their absorber plates are incorporated in each collector. Along the centerline of each glass tube is located a single copper tube which is attached to the middle of the absorber plate. The heat collecting water flows through this center pipe and absorbs the solar energy collected.
Figure 3. Isometric view of a collector.
The ends of each glass tube are sealed to a special stainless steel end cap using a ceramic glass material having a coefficient of thermal expansion approximately the same as that of the glass tube. The difference in the thermal expansion between the copper tube and the glass tube is taken up by bellows installed between the end cap and the copper tube. Each collector consists of 10 individual tubes arranged in parallel. The heat collecting water moves inside the center tubes in a parallel/series arrangement whereby in five of the tubes the flow is in one direction and in the other five it is in the opposite direction. Attached to one end of the center tubes is a header tube with an orifice located in the middle of the header tube. The other ends are connected to return bends which are used to connect pairs of center tubes in series. Several collectors (14 in number) are connected in series by coupling the different header tubes. Each collector has an absorber area of 1.75 m2 and is coated with a black selective coating having an absorptivity, α ≥ 0.91 and an emittance,
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ε ≤ 0.12. The specifications of a single collector as provided by the manufacturer are shown in Table 1. Table 1. Specifications of a single collector Item Selective coating Absorber area External dimensions Net weight Flow rate Max. operating pressure
Specification Absorptivity α ≥ 0.91 Emissivity ε ≤ 0.12 1.75 m2 2860 mm x 985 mm x 115 mm 64 kg 700 – 1,800 lit/hr 6 bar
Figure 4. One array pair.
The collector bank consists of 1064 collector units making up a total collector area of 1064 × 1.75 = 1862 m2. 28 collectors are combined to form a single array pair of collectors with its own support structure as shown in Figure 4. Each array pair consists of two parallel stacks of collector with each stack consisting of 14 collectors in series. The array pair is 14.5 meters long and 6.0 meters wide and is oriented in the north/south direction at a slope of 1/50. Water is supplied from the main pipe on the south side and passes through the 14 collectors connected in series and exit into the main pipe on the north side. 76 array pairs are arranged in a U-shape to form the whole collector bank. All array pairs are connected in parallel and each is provided with two isolating valves- at inlet and exit-, a drain valve, and an air vent. The bank is divided into six blocks designated A, B, C, D, E and F. Blocks A and F consists of 12 array pairs while the other blocks each consists of 13 array pairs. Figure 5 is a block diagram of the collector field.
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from MED evaporator
Tank #3
Block F
Block A Tank #2
Block E
Block B Block C
Tank #1
Block D
to MED evaporator
Figure 5. Collector bank consisting of six blocks A, B, C, D, E and F.
3.1.2. The Heat Accumulator Subsystem The heat accumulator subsystem (see Figure 6) is designed to provide thermal energy to the evaporator during its 24 hours per day operation. It consists of three carbon steel tanks having a total capacity of 300 m3 and contains hot water at a temperature ranging from 74oC to 99oC and at atmospheric pressure. The tanks are insulated with a 100 mm layer of fiberglass to minimize heat loss to the ambient air. All three cylindrical tanks have the same internal diameter (3.8m) and wall thickness (9mm). However, the tank heights are not identical with tank No. 1 having an effective height of 10m while tanks No. 2 and 3 having an effective height of 7.6m. The heat collecting water from the collector bank is introduced at the top of tank No. 1. The heat collecting water to the collector bank is taken from the bottom of tank No. 3. Heating water to the evaporator is drawn from the top of tank No. 1 and returns to the bottom of tank No. 3. The water is therefore stratified in such a way that the top water layers of tank No. 1 are always at the highest temperature and the bottom layer of tank No. 3 at the lowest temperature. The heat accumulator tanks have enough capacity to be able to provide the required thermal load (for the evaporator) for about 16 hours after sunset provided that the tanks are fully charged just before sunset. This feature makes it possible to operate the desalination unit during night time. Only during extended overcast or hazy days when sandstorms prevail we expect plant shut-down to occur due to insufficient energy collection.
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Figure 6. Heat accumulator subsystem.
3.1.3. MED Evaporator Subsystem A horizontal tube, thin film multi-effect distiller (MED) is used for desalination of seawater. The distiller is manufactured by Sasakura Engineering Co., Ltd. It was chosen because of its capability to accommodate large load fluctuations and its small consumption of electrical power. The maximum capacity of the distiller is 120 m3/day. A flow diagram of the MED desalination process is shown in Figure 7. Preheated feedwater is sprayed into the top of the first effect and descends down the evaporator stack, flowing as a thin film over the tube bundle in each effect. The feedwater flashes and thereby cooled by several degrees as it passes from one effect to the next. It is rejected at the bottom of the plant as cool, concentrated brine. In the top effect, heating water from the accumulator is used to partially evaporate the thin seawater film on the outside of the tubes. The generated vapor passes through demisters to the inside of the tubes in the second effect where it condenses to form part of the product. It simultaneously causes further evaporation from the external seawater film and the process is repeated from effect to effect down the plant. The heat input from the accumulator is thus used over and over again in successive evaporation/condensation heat exchangers in each effect to produce more product and new vapor, thereby obtaining a maximum quantity of fresh water with minimum heat input. The vapor generated in the last effect (18th) is condensed in a seawater-cooled condenser and part of the seawater is used as feedwater to the stack. The remaining seawater is rejected to the sea and carries most of the heat away from the process.
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Figure 7. The MED evaporator.
3.2. Design Features Table 2 shows the design conditions and specifications at the time of the original planning of the test plant. At the planning stage, no detailed solar radiation data was available for Abu Dhabi city and the only data available was that for nearby Kuwait. Therefore the data for Kuwait was used with the annual mean daily solar radiation on horizontal surface taken as 5000 kcal/m2 day. Based on the measurements at the test plant made during 1985 and subsequent years, the annual average daily values were found to be slightly higher than this value (5270 kcal/m2 day for 1985).
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Design parameter Solar radiation Ambient temperature Rainfall Wind speed Relative humidity Seawater temperature System capacity Solar collector type Heat accumulator Evaporator
Assumed value/range 5,000 kcal/m2 day (annual mean value on horizontal surface) 30oC (daytime mean temperature) 18.1 – 390.1 mm/year 5 m/s (for collector design) 30 m/s (for structures) Max. 100%, min. 10%, normal 25-90% 55,000 ppm TDS (design base) 80 m3/day as expected yearly average Evacuated glass tube collector 1862 m2 (effective absorbing area) Thermally stratified vertical cylinder Capacity 300 m3 Horizontal-tube, multiple effect stack type Evaporator, capacity 120 m3/day, specific heat consumption 43.8 kcal/kg- product water
4. MEASUREMENTS AND DATA ACQUISITION SYSTEM Table 3 lists the plant parameters measured every 15 minutes and the measured data is sent to the data acquisition system (DAS). The DAS is shown in Figure 8 and consists of two separate subsystems: one is the on-line control room subsystem and the other is data analysis subsystem. The data analysis subsystem consists of a Thermodac 32 data logger manufactured by Eto Denki, Co., PC (model PC-8001 mkII manufactured by NEC company) and a PC printer (model PC-8023C manufactured by NEC company). The data analysis subsystem consists of a data logger (model Thermodac 3 manufactured by Eto Denki, Co.), PC (model PC-8801mk II by NEC company) and PC printer (model PC-8024 by NEC company).
Figure 8. The data acquisition system.
Multiple Effect Distillation of Seawater Water Using Solar Energy … The control room subsystem has the following functions: • • • •
Sampling of data at 15 minute intervals Calculate hourly average values once per hour Record data on CD at even hours (i.e. 8:00, 10:00, 12:00,…) Print a summary report every 12 hours.
The data analysis subsystem has the following functions: • • • •
Make daily, weekly and monthly reports. Format new data disks Copy data disks for backup Edit hourly or daily data on data disks. Table 3. Items of data acquired every 15 minutes from data loggers Thermodac 32 and Thermodac 3 Channel # Measuring survice THERMODAC 32 1 Ambient temp. 2 Collector field outlet temp. 3 Accumulator inlet temp. 4 Accumulator outlet temp. 5 Heating water inlet temp. 6 Heating water outlet temp. 7 No. 1 effect temp. 8 Preheater No. 1 outlet temp. 9 No. 18 effect temp. 10 Seawater temp. 11 Empty collector temp. #1 12 Empty collector temp. #2 13 Relative humidity 14 Heat collecting water flow 15 Heating water flow 16 Product water flow 17 Solar radiation 18 Heat collected from field 19 Heat used by evaporator 20 Heat collected by block F 21 Heat collected by block A 22 Pump P-101 running hours (heat collecting pump) 23 Pump P-205 running hours (product water pump) 24 Electrical energy consumption THERMODAC 3 1 No. 1 effect temp. 2 No. 4 effect temp. 3 No. 7 effect temp. 4 No. 10 effect temp. 5 No. 13 effect temp. 6 No. 16 effect temp. 7 No. 18 effect temp.
Tag #
Signal output
Unit
TE-111 TE-102-1 TE-102-2 TE-102-3 TE-104 TE-105 TE-206-1 TE-203 TE-206-2 TE-202 TE-301 TE-302 HUE-111 FIT-101 FIT-105 FQ-205 SQ-111 CAQ-102 CAQ-105 CAQ-101-1 CAQ-101-2 N/A
DC 1-5 V DC 1-5 V DC 1-5 V DC 1-5 V DC 1-5 V DC 1-5 V DC 1-5 V DC 1-5 V DC 1-5 V DC 1-5 V Thermocouple Thermocouple DC 1-5 V DC 1-5 V DC 1-5 V DC 24V pulse DC 24V pulse DC 24V pulse DC 24V pulse DC 24V pulse DC 24V pulse On/off pulse
o
C C o C o C o C o C o C o C o C o C mV mV % m3/hr m3/hr m3 kcal/hr m2 kcal kcal kcal Kcal hr
N/A
On/off pulse
hr
N/A
DC 24V pulse
kWh
TEW-206-1 TEW-206-4 TEW-206-7 TEW-206-10 TEW-206-13 TEW-206-16 TEW-206-18
Pt 100 Pt 100 Pt 100 Pt 100 Pt 100 Pt 100 Pt 100
o
o
C C o C o C o C o C o C o
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The items of data shown in table 3 are transferred to the computer through an RS-232C interface to the control room computer to be processed. The results of the mean of four 15minute data values are displayed every hour on the CRT in the control room. The following hourly values are displayed on the CRT: • • • • • • • • • • • • • • • • • • • • • • • • •
Climatic temperature (oC) Solar radiation (kcal/m2hr) Heat consumption (kcal/kg dist.) OHTC of heater (first effect) (kcal/m2hroC) Seawater flow (m3/hr) Seawater TDS (ppm) Seawater inlet temp. (oC) Seawater outlet temp. (oC) Heat collected by block F (kcal/hr) Heat collected by block A (kcal/hr) Heat collecting pump flow rate (m3/hr) Heat accumulator inlet temp. (oC) Heat accumulator outlet temp. (oC) Heating water inlet temp. to evaporator (oC) Heating water return temp. from evaporator (oC) Heat supplied to accumulator (kcal/hr) Heat supplied to evaporator (kcal/hr) Heat supplied to evaporator (kcal/hr) Evaporator feedwater flow rate (m3/hr) Preheater #1 outlet temp. (oC) First effect temp. (oC) 18th effect temp. (oC) Product water flow rate (m3/hr) Absorber plate temp. of empty collector (oC) Header tube temp. of empty collector (oC)
4.1. Measuring the Heat Collected in Block F Measuring the heat loss in the piping system in such a large collector bank is obviously laborious and will require the accurate measurement of collector fluid temperature at many locations within the field. This was deemed impractical and was ruled out from the outset. The solution which was found practical is to isolate a single block of collectors and use it for test measurements in order to find the piping heat loss in this block, then estimate the heat loss in the piping system of the whole collector bank based on the results obtained from the measurements carried out on the selected block. Block F was selected for this purpose since this block was already provided with resistance temperature detectors at inlet and outlet of the block, as well as a vortex flowmeter for measuring the water flow rate through the block. Figure 9 is a schematic diagram of block F showing the location of the temperature measuring probes. Two RTDs are attached at block inlet (location E) and block outlet (location F). The RTDs, which are three-wire sheathed platinum resistance elements, are
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model RN33-AMAS and are manufactured by Yokogawa Hokushin Corporation. They are connected to Thermodac 32 via resistance-to-voltage converters which produce 1-5 volt DC signal outputs that are fed to temperature recorders. The two output signals from the resistance-to-voltage converters which are attached to the RTDs at locations E and F are connected to a programmable computing unit (PCU), model SPLR-100A manufactured by Yokogawa (see Yokogawa Instruction Manual for Model YF100 vortex flowmeters (1993)), in which the 4-20 mA signal from the vortex flow meter is also connected to the PCU. A variety of arithmetical computational functions can be performed by the PCU. Programs can be developed and written to ROM (Read Only Memory) using a dedicated programming language connecting the PCU to an SPRG Programmer. The pulse output signal from the PCU represents the heat collected between E and F and was measured by subtracting the two input temperature signals, TF - TE, and multiplying by the flow rate signal and the specific heat of the heat collecting fluid (water) at the operating temperature to obtain the heat collected between E and F (block heat collected).
Figure 9. Location of measuring sensors in block F.
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The analog signals from the resistance-to-voltage converters, as well as the pulse output signal from the PCU were connected to the DAS for recording and printing and for transfer to a PC computer system via an RS-232 interface cable. The pulse output signal was integrated over a period of one hour and scanning of the data was made every 15 minutes. The inlet and outlet temperature measurements (TA and TB) of each of the 12 arrays making up block F were measured using copper-constantan thermocouples which were attached to the array header pipes as shown in Figure 9. The assembly of these thermocouples into the array supply and return pipes, as well as the locations of the 24 (2 x 12 arrays) thermocouples used are also shown in this figure. The mV output signals from these thermocouples were recorded on an hourly basis. The heat collected by the 12 arrays was calculated by multiplying the temperature difference, TA – TB, by the flow rate and the specific heat in a manner similar to that used for estimating the block heat collected. A remote converter-type vortex flowmeter (model YF105, Yewflo by Yokogawa) is used with a model YFA11 vortex flow converter are used for flow measurement. This vortex flow meter measures the flow rates and converts the measurements to a 4 to 20 mA DC output signal. The accuracy of the instrument is ± 1.0% of reading plus ± 0.1% of full scale. A solar radiation sensor (pyranometer)- model H 201 manufactured by Nakaasa Instrument Co.- is used to measure the global insolation on the collector absorber plate. The sensor has a measuring range of 0 to 2 kW/m2 and has an accuracy of ± 0.5% of full scale. The mV output signal from the sensor is first amplified before being converted into a pulse signal for connection to Thermodac 32 data logger. This signal is integrated over hourly intervals in order to obtain the hourly values of the solar radiation. The ambient temperature was measured by a three-wire RTD connected to the DAS. Figure 10 shows a block diagram of the data acquisition and analysis for the heat collection system. The estimated percentage error in the heat measurement was estimated as 1.5 – 3% while the error in the collector efficiency measurement 2.0 – 3.5%.
Figure 10. Block diagram of data acquisition system for heat collection.
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5. DATA ANALYSIS 5.1. Calculating the Solar Radiation on Absorber Plate The global solar radiation intensity on a tilted surface having a tilt angle α to the ground, and an azimuth angle β can be expressed by Eq. 1.
It = Id + I s
(1)
where Id is the direct component of solar radiation and Is is the diffuse component. According to [5], the components can be expressed as:
Id = Io × P
1 sin( h )
× cos( θ )
(2) 1
1 + cos(α ) 1 1 − P sin( h ) × I s = × I o × sin( h ) × 2 1 − 1.4 ln( P ) 2
(3)
where P is the atmospheric transmittance, h is the solar altitude, θ is the incidence angle on the tilted surface. The solar angles are shown in Figure 11. The transmittance P is defined as the ratio between the normal solar radiation at the ground and the corresponding value at the outer limit of the atmosphere:
P=
IN I oN
(4)
where IN is direct normal radiation at the ground and IoN is the corresponding value at the edge of the atmosphere. Since the hourly global radiation is measured at a tilted surface having the same tilt angle as the collector absorber plates, It, it is possible to solve the following equation for the hourly values of P:
It = Io × P
1 sin( h )
× cos(θ ) +
1 sin( h )
1 1− P 1 + cos(α ) × I o × sin( h) × × 2 1 − 1.4 ln( P) 2
(5)
With the hourly values of P estimated, it is possible to calculate the direct and diffuse components from Eqs. 2 and 3.
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Figure 11. Solar angles.
5.2. Calculating the Performance of the Collector Bank The heat collection amount, Qc, was calculated from the measured collector water temperatures and flow rate
Qc = mc C p (Tc 2 − Tc1 )
(6)
where mc is the water flow rate through the collector bank (or block) and Tc1 and Tc2 are the inlet and outlet water temperatures, respectively. The heat collection efficiency is expressed by the following polynomial equation
ηc ≡
Qc = a + b x + c x2 Ac I t
(7)
a, b, and c are constants and x is a parameter defined as
Tc1 + Tc 2 − Ta 2 x= It
(8)
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where Ta is the ambient air temperature and It is the solar radiation on a tilted surface. Susbstituting the expression for Qc from Eq. 6 and the expression for x from Eq. 8 into Eq. 7 we get a relationship for the collector outlet temperature, Tc2 in terms of the collector inlet temperature, ambient temperature, solar radiation and collector absorber area
C1Tc22 + 2C 2Tc 2 + C 3 = 0
(9)
where C1, C2 and C3 are given by the following expressions
C1 = γ Ac C 2 = γ Ac (Tc1 − 2Ta ) + β Ac I t − 2mc I t C 3 = γ Ac (Tc1 − 2Ta ) 2 + 2βAc I t (Tc1 − 2Ta ) + 4αAc I t2 + 4mc I t Tc1 with the above equations, the hourly values of the outlet water temperature Tc2 can be derived if the hourly inlet water temperature, Tc1, is given.
5. 3. Calculating the Performance of the Evaporator The performance of the evaporator consists of estimating the overall heat transfer coefficients (OHTC) of the first effect (heater), the other evaporator effects (2nd – 18th effects), the 17 preheaters and the condenser as well as evaluating the economy (or specific heat consumption) of the evaporator. The list of measurements carried out for the evaporator are shown in Table 4. Table 4. Measurements made at evaporator Measurement
Location
Symbol
Unit
Flow rate
Heating water flow
mhw
m3/h
Seawater flow
msw
m3/h
Feedwater flow
mfw
m3/h
Product water flow
md
m3/h
Heating water inlet
Thw1
o
C
Thw2
o
C
First effect
Tev(1)
o
C
18th effect
Tev(18)
o
C
Tpr(1)
o
C
Seawater inlet to condenser
Tcon1
o
C
Seawater outlet from condenser
Tcon2
o
C
Heat amount
Heat supplied by heating water
Qhw
kcal/h
Total dissolved solids
Seawater
Cb(0)
Kg salt/kg water
Temperture
Heating water outlet
st
1 preheater outlet
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5.3.1. Calculating the Brine Concentration at Each Effect The brine total dissolved solids (TDS) at each effect is estimated from a mass balance for each effect considering the fact that the heater (first effect) receives all the feedwater while all the other effects receive only half of the amount of brine leaving the first effect. This stems from the fact that the evaporator consists of one effect at the top followed by two stacks in parallel with all odd-numbered effects in one stack and even-numbered ones in the other. The brine concentration in the first effect is estimated from:
Cb (1) =
mfw × C b ( 0) ( mfw − md / 18)
(10)
where mfw is the feedwater flow rate, md is the distillate flow rate and Cb(0) is the seawater concentration. The concentration of the even-numbered effects is obtained from
C b (2 N ) =
0.5 × ( mfw − md / 18) × C b (1) [0.5 × ( mfw − md / 18) − N × md / 18]
(11)
where N varies from 1 (2nd effect) to 9 (18th effect) The concentration of the odd-numbered effects is obtained from Cb(2N + 1) = Cb(2N) Where N varies from 1 (3rd effect) to 8 (17th effect).
(12)
5.3.2. OHTC of Heater (First Effect) In the heater (first effect) hot water from the accumulator flows through the tubes in a horizontal tube bundle while a relatively cold seawater is flowing as a thin boiling film on the outside of the tubes. Heat is therefore transmitted from the hot water inside the tubes to seawater on the outside. The overall heat transfer coefficient for the heater can be expressed as
Uh =
Qh Ah (ΔT ) h
(13)
where Qh is the rate of heat transfer (kcal/h), Ah is the heat transfer area (Ah = 24.9 m2) and (ΔT)h is the log-mean-temperature difference obtained from the equation:
(ΔT ) h =
{Thw1 − Tev (1)} − {Thw 2 − T pr (1)} {T − Tev (1)} ln hw1 {Thw 2 − T pr (1)}
The rate of heat transfer can be estimated from
(14)
Multiple Effect Distillation of Seawater Water Using Solar Energy …
Qh = mhw C p (Thw1 − Thw 2 )
103 (15)
The specific heat Cp is calculated at the average temperature (Thw1 + Thw2)/2.
5.3.3. Average OHTC of other Evaporator Effects In the 2nd –18th effects the mechanism of heat transfer is different from that in the first effect. In these effects, boiling takes place on the outside of the horizontal tubes while condensation occurs on the tube inside. The average overall heat transfer coefficient for the 17 evaporators was estimated from the equation
U ev =
Qev Aev (ΔT ) ev
(16)
where Qev is the average heat transfer rate for each evaporator effect, (ΔT)ev is the average log-mean-temperature difference for each evaporator and Aev is the heat transfer area of each evaporator (Aev = 63.1 m2). The heat transfer rate Qev is obtained from the fact that the distillate production consists of two components: production by the 17 (2nd –18th ) effects and production by the 17 (1st – 17th) preheaters:
md = (md ) ev + (md ) pr
(17)
Where ( md )ev is the distillate production by the 17 evaporator effects and ( md )pr is the production by the 17 preheaters. ( md )pr is calculated from a heat balance equation over all the preheaters:
(md ) pr =
mfw C p (Tpr (1) − Tcon2 ) Lav
(18)
The latent heat of vaporization Lav is estimated at an average temperature of [Tev(1) + Tev(18)]/2. The average heat transfer by each evaporator effect is obtained from:
Qev =
mev × Lav 17 md Lav − mfw C p (Tpr (1) − Tcon2 ) = 17
(19)
The average log-mean-temperature difference (ΔT)ev is calculated as the average temperature difference between the heating steam inside the evaporator tube bundles and the boiling brine on the outside. Noting that the heating steam temperature in a particular effect i is slightly lower than the brine temperature in the preceding effect (i.e., effect i -1) due to:
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the boiling point elevation (BPE), the temperature drop across the demister inside (Δp)demis,
(ΔT)ev was estimated from the following relation
(ΔT ) ev =
18
17
i =1
i =1
Tev (1) − Tev (18) − ∑ BPE − ∑ (Δp) demis 17
(20)
The values of the boiling point elevation (BPE) and the demister pressure drop (Δp)demis are calculated using the correlations given in the appendix.
5.3.4. Average OHTC of Preheaters In the 17 preheaters seawater flowing inside the tube bundles of heat exchangers is heated up by steam condensing on the tube outside. For any preheater, the average OHTC (kcal/hr m2oC) can be calculated using the equation:
U ph=
Q ph A ph × (ΔT ) ph × 17
(21)
where Qph is the heat transfer rate for all preheaters , kcal/hr and Aph is the heat transfer area of each preheater, m2 (Aph = 19.5 m2). Qph is calculated from the measured feedwater flow rate and the temperature difference between the outlet of preheater #1 (top preheater) and the outlet of the condenser:
Q ph = M fw × C p × (T ph (1) − Tcond 2 )
(22)
The log-mean temperature difference (ΔT)ph is assumed to be identical for each preheater.
5.3.5. OHTC of Condenser The OHTC of the condenser is calculated from the measured seawater flow rate and condenser inlet and outlet temperatures according to the equation:
U cond =
Qcond Acond × (ΔT ) cond
(23)
where Qcond is condenser heat flow rate, kcal/hr, Acond is the condenser heat transfer area, m2 (Acond = 35.3 m2). The log-mean temperature difference for the condenser is calculated from the equation:
(ΔT ) cond =
(Tev (18) − Tcond 1 ) − (Tev (18) − Tcond 2 ) (T (18) − Tcond 1 ) ln ev (Tev (18) − Tcond 2 )
(24)
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5.3.6. Evaporator Economy The performance ratio (PR) of the evaporator is calculated as the ratio between the product flow rate, Md (kg/hr) and the equivalent amount of heating steam to the heater (first effect):
PR =
md (Qh / L)
(25)
where Qh is amount of heat supplied to the heater (first effect) and L is the latent heat of vaporization (kcal/kg).
6. WEATHER CONDITION IN ABU DHABI For a solar desalination plant, the solar radiation and ambient temperature have a great effect on the heat collection efficiency of the collectors while the temperature and salinity of the seawater influence the capacity of the distiller. Consequently, these data which have been yielded by the research operation constitute valuable basic material for analyzing the performance of the operation of the plant.The total solar radiation on a horizontal surface for 1985 ( see Table 5) came to 1,923,000 kcal/m2 year which gave a mean daily value of 5,270 kcal/m2 day. When the monthly average total solar radiation an a horizontal surface is considered, the maximum value was achieved in June which was 1.95 times as high as the minimum value recorded in December. Table 6 shows the atmospheric transmittance and the figures in this table were determined by calculations from the total solar radiation values on a tilted surface using the Bouger’s and Berlage’s formulae[5]. Generally, there is a tendency on any given clear day for the atmospheric transmittance at dawn and dusk when the solar altitude is low to work out on the high side and for it to be on the low side around midday when the solar altitude is high. Table 6 gives the values for the atmospheric transmittance at noon everyday and consequently the air mass (air mass = sin(h) where h is the solar altitude) is ranging from 1.0 to 1.5. Since values yielded for cloudy days are assumed to be meaningless, the same table gives the mean atmospheric transmittance values for the above five days in each month as the monthly averages. This indicates that the closer the atmospheric transmittance is to 1.0, the purer is the air, and seasonal changes are apparent in that it is high during winter and low during summer. The monthly average daily mean, maximum and minimum ambient temperatures are shown in Table 7. Table 8 shows the monthly average daily maximum relative humidity in Abu Dhabi and Table 9 shows the seawater salinity. The results of the TDS analysis of seawater are indicated in table 9. Variations are visible in the measured values with the salinity being slightly higher in summer months compared to winter months.
Table 5. Daily total radiation on tilted surface at 21o 09’ (data of 1985) Month Solar radiation Kcal/m2 day Solar radiation kWh/m2 day
Jan. 3700
Feb. 5010
Mar. 5270
Apr. 6210
May 6350
Jun. 6770
Jul. 5810
Aug. 5830
Sep. 5740
Oct. 4970
Nov. 4130
Dec. 3470
4.3
5.8
6.1
7.2
7.4
7.9
6.7
6.8
6.7
5.8
4.8
4.0
Table 6. Atmospheric transmittance at noon Month Transmittance
Jan. 0.74
Feb. 0.76
Mar. 0.69
Apr. 0.70
May 0.65
Jun. 0.66
Jul. 0.61
Aug. 0.61
Sep. 0.64
Oct. 0.67
Nov. 0.70
Table 7. Monthly average daily mean, max. and min. ambient temperatures (1985) Month Mean Maximum Minimum
Jan. 20.2 24.8 16.7
Feb. 19.4 23.9 15.7
Mar. 22.8 28.2 18.7
Apr. 26.1 31.8 21.3
May 30.5 36.3 25.9
Jun. 32.1 37.8 27.2
Jul. 34.0 39.9 30.0
Aug. 35.2 42.6 30.7
Sep. 32.3 39.0 27.3
Oct. 29.4 34.5 24.8
Nov. 25.5 29.9 21.5
Dec. 21.0 25.6 17.1
Table 8. Monthly average daily maximum relative humidity in Abu Dhabi (1985) Month Humidity
Jan. 90.9
Feb. 82.6
Mar. 82.0
Apr. 81.5
May 77.6
Jun. 80.4
Jul. 78.0
Aug. 77.6
Sep. 87.8
Oct. 85.2
Nov. 87.3
Dec. 83.6
Table 9. Seawater salinity Sampling date TDS (ppm)
25 Sep. 84 52,100
2 Jan. 85 51,200
2 Mar. 85 51,900
17 Jul. 85 53,500
22 Oct. 85 53,000
Dec. 0.72
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7. OPERATING CHARACTERISTICS In this section the results of plant characteristics during the first year of operation is presented. Typical measured performance for each of the main plant subsystems, e.g. heat collecting subsystem, heat accumulator subsystem and evaporator subsystem, are presented. The major performance parameters for the whole plant are also shown.
7.1. Heat Collecting Subsystem 7.1.1. Heat Collector Efficiency Instantaneous Heat Collection Efficiency Figure 12 shows the measured collector efficiency of the whole collector bank for a typical month (June 1985) and the ideal efficiency of a single collector measured under controlled conditions at the manufacturer’s laboratory. The ideal efficiency can be correlated to the x-parameter by the following polynomial equation:
η c0 = 0.913 − 2.46 x − 1.92 x 2
(26)
The measured collector efficiency is seen to be lower than the ideal efficiency due to heat losses from the piping system as well as losses due to attenuation of solar radiation received by the absorber plates because of dust deposition on the glass tubes of the collectors. In order to exclude the data during the warm-up and cool down periods in the early morning and before sunset, only the data for the period 10:00 am to 5:00 pm were plotted. The amount of heat collected was estimated from the measured inlet and outlet water temperature to the collector field and the flow rate of water. Therefore, all the heat loss from the internal and external piping system was included in the instantaneous efficiency shown in Figure 12. Figure 13 shows the instantaneous efficiency of the collector bank at mid-day during the months of January and June 1985. In a clear day, the efficiency at mid-day (12:00 noon) is usually close to the highest value for that day. It can be seen that, for the month of January where some days are usually overcast, the mid-day efficiency drops for those overcast days. June is normally a sunny month with rare overcast periods, the mid-day efficiency fluctuates only slightly. The mid-day efficiency can drop slightly during periods of sand storms where the air is laden with small dust particles that reduce the solar radiation falling on the absorber plates of the collectors.
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Ali M. El-Nashar Measured efficiency
Ideal efficiency
collector efficiency
1
y = 0.913 - 2.46 x - 1.92
0,8
2
0,6 0,4 0,2
Data of June 1985
0 0
0,02
0,04
0,06 0,08 x-param eter, hm 2oC/kcal
0,1
0,12
0,14
Figure 12. Measured efficiency of collector bank and the ideal efficiency of a single collector for a typical day.
Collectir mid-day efficiency
Jan. 1985
Jun. 1985
0,8 0,6 0,4 0,2 0 0
5
10
15
20
25
30
35
Day number
Figure 13. Daily instantaneous efficiency at mid-day during January and June 1985.
Daily efficiency
Jan. 85
июн.85
1 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0,1 0 1
6
11
16
21
Day num ber
Figure 14. Daily heat collection efficiency for January and June 1985.
26
31
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7.1.2. Daily Heat Collection Efficiency The daily heat collection efficiency is defined as the ratio of the amount of heat produced by the collector bank divided by the amount of solar radiation falling on the absorber plates. The daily amount of heat produced and the daily amount of incident solar radiation are estimated from the summation of their hourly values during a day which are measured and recorded by the data acquisition system. Figure 14 shows the daily heat collection efficiency for the months of January and June 1985. It can be seen that the daily efficiency for sunny days is normally above 50% except for days with prolonged overcast periods, such as in January, during which the daily efficiency can drop below 40%.
7.2. Heat Accumulator System 7.2.1. Heat Loss from the Heat Accumulator Table 10 gives the monthly heat loss from the heat accumulator as a percentage of the incident solar radiation on the collector field for several months during 1985. As can be seen, the heat loss varies from 4.6% (for June) to 6.6% (for December). The percentage heat loss is increased during winter months compared to summer months and also increases during the month where the plant experiences several shutdowns either emergency shutdown or automatic shutdown due to insufficient accumulator charge. Months where the plant has been in emergency shutdown for long periods of pump maintenance, for example, can have accumulator loss exceeding 8%. Table 10. Monthly heat loss from the heat accumulator as a percentage of incident solar radiation (data of 1985) Month Heat loss %
Jan. 5.6
Mar. 6.3
May 5.0
Jun. 4.6
Sep. 5.6
Nov. 5.3
Dec. 6.6
7.2.2. Thermal Stratification Ratio The thermal stratification ratio is the ratio of the mass of the strata of water in the heat accumulator where a temperature gradient exists to the total mass of water inside the accumulator. The total mass of water inside the 3 accumulator tanks is essentially constant at 300 m3. The thickness of the temperature gradient strata is measured using the temperature sensor (RTD) located in the middle of tank # 2 (mid-temperature tank). The heat accumulator operates in two main modes: the simultaneous heat collection and discharge mode during day periods and the discharge mode during night periods. Table 11 shows the percentage thermal stratification ratio for each of these two modes for a number of days. During the heat discharge mode (at night), the temperature gradient strata averages 19.5 m3 which corresponds to a stratification ratio of 6.5%. During the simultaneous heat collection and discharge mode (during day time) this strata averages 21.9 m3 which corresponds to a stratification ratio of 7.3%.
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Ali M. El-Nashar Table 11. Thermal stratification ratio of heat accumulator (data of 1985) Date
Heat discharge
Jan. 14 Jan. 15 Jan. 19 Feb. 2 Feb. 13 Feb. 20 Mar. 10 Mar. 20 Mar. 29 Apr. 4 Apr. 10 Apr. 20 May 3 May 11 May 20 Average
4.6% 3.8% 4.6% 6.7% 6.6% 6.1% 10.6% 8.8% 6.5% 9.4% 7.2% 1.7% 6.4% 5.6% 8.3% 6.5%
Simultaneous heat collection and discharge 6.0% 7.9% 4.8% 8.1 6.1% 8.3% 6.3% 3.9% 5.8% 5.7% 7.6% 11.5% 8.9% 9.2% 9.3% 7.3%
7.3. Evaporating System 7.3.1. Evaporator Performance The performance ratio (PR) is defined here as the amount of product water produced by the evaporator per 526 kcal of heat supplied by the heating water. Table 12 shows the average PR values and average specific heat consumption for several months during the first year of the test plant operation. The effect of the product water flow rate on the PR is shown in Figure 15 which is based on actual tests carried out during plant commissioning in November 1984. Table 12. Performance ratio of the evaporator Month Jan. 1985 Feb. 1985 Mar. 1985 Apr. 1985 May 1985 Jun. 1985 Sep. 1985
Product water flow m3/hr 4.6 5.3 5.0 5.2 5.0 5.1 4.9
Specific heat consumption kcal/kg 40.71 39.04 39.31 38.83 39.04 39.98 40.31
Performance Ratio 12.9 13.5 13.4 13.5 13.5 13.2 13.0
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Performance Ratio, PR
14 13 12 11 10 0
1
2
3 4 Product w ater flow , m 3/hr
5
6
7
Figure 15. Performance Ratio versus product water flow.
OHTC, kcal/hr m2 oC
Overall Heat Transfer Coefficients The overall heat transfer coefficients (OHTC) shown in Figure 16 are estimated from the measured temperatures and flow rates. Shown in this figure are the average HTC for the evaporators, the average OHTC of the preheaters and the OHTC of the heater (first effect) and condenser. The evaporators are heat exchangers in which vapor is condensed inside tubes while seawater brine boils on the outside of the tubes. These heat exchangers have the highest OHTC compared with the other heat exchangers as shown in the figure. The data shown in this figure represent typical values of the OHTC,s obtained during the first year of plant operation. Some deterioration in the OHTC’s has occurred during the subsequent years which necessitated acid cleaning to remove scale deposited on the heat exchanger tubes.
3000 2500
Heater
2000 1500 1000
Evaporators Preheaters 1
2
3
4
5
6
7
8
9 10 11 12 13 14
Condenser
Measurem ent #
Figure 16. Measured OHTC during the period June 1-7, 1985.
7.4. Performance of the Plant Figure 17 and Figure 18 show pie chart plots depicting the January and June split of the incident solar radiation falling on the collector bank among collector loss (including piping loss and loss due to dust effect), accumulator heat loss, heat loss by the evaporator and the heat going for desalination. It can be seen that for January, 37% of the incident solar radiation is converted into thermal energy for desalination while for June it is 47%. This is due to the fact that for winter months heat losses from the collector bank, the accumulator tanks and the evaporator are larger than during the summer period because ambient winter temperatures are substantially lower than summer temperatures.
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Ali M. El-Nashar
January 1985 37% 54%
3% 6%
Collector loss
Accumulator loss
Evaporator loss
Heat for distillation
Figure 17. Split of the incident solar radiation for January. June 1985
47%
47%
1% 5%
Collector loss
Accumulator loss
Evaporator loss
Heat for distillation
Figure 18. Split of the incident solar radiation for June.
60 40 20 0 Jan.
Feb.
Mar.
Specific w ater production (kg/m 2day)
Apr.
May
Jun.
Specific heat consum ption (kcal/kg dist.)
Specific pow er consum ption (kWh/m 3)
Figure 19. Plant performance parameters for the first six months of 1985.
Figure 19 shows the monthly values of three major plant performance parameters: the specific water production in kg/m2 day, the specific heat consumption in kcal/kg dist. and the specific power consumption in kWh/m3. The specific water production is defined as the rate of water production per unit collector area. It varies between 43.9 kg/m2 day and 78.1 kg/m2 day with the lower values for the winter months and the higher values for the summer months. The specific heat consumptions is defined as the rate of heat supplied to the
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evaporator per unit of water production. It is essentially constant at about 39 kcal/m3 of product water. The specific power consumption, defined as the electrical energy required per cubic meter of product water, varies between 7.08 kWh/m3 and 8.15 kWh/m3 with the higher values typical for winter months and lower values for summer months.
8. PLANT MAINTENANCE AND MODIFICATIONS In this section, the major maintenance and plant modification activities will be described. Among the major maintenance activities that had to be carried out regularly are the following: • • • • • • •
Cleaning the collectors to remove dust and dirt deposited. Inspection for corrosion replacing corroded components Inspect vacuum inside collector glass tubes Monitor scale formation on evaporator heat exchanger tubes and carry out acid cleaning if necessary Monitor level of water in heat accumulator and add makeup water and anticorrosive chemical as required Evaporator pump maintenance Monitor pressure difference across seawater intake filters and clean when necessary
Plant modifications were necessary in order to avoid the harmful effects of emergency plant shutdown due to power failure.
8.1. Heat Collecting System 8.1.1. Cleaning the Solar Collector Field The performance of the solar collector field is affected by the extent of dust deposition on the glass tube which influences the transmittance of the glass tube to solar radiation. It is therefore important to clean the collector field at regular intervals to maintain good performance. The cleaning was carried out using a high-pressure water jet spray device. Since fresh water is used for cleaning, it is important to economize on the use of fresh water for collector cleaning without adversely affecting the performance of the collectors. The amount of water required for each cleaning session depends on the extent of dust deposition on the collectors; more water is required when more dust has accumulated on the collectors. Since sandstorms are seasonal in character, the amount of dust deposited in a particular period depends on the month of the year. Several tests were carried out to determine the required amount of fresh water needed for each collector block. Figure 20 shows the measured water quantity used for each cleaning session for one block for different months. As can be seen, there is wide variation in the quantity of cleaning water required which may be attributed to variation in the personal skills of the different cleaners as well as variation in the amount of dust deposition on the glass tubes. The average quantity of water for each cleaning session is about 1000 liters.
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Ali M. El-Nashar
2500 2000 Water 1500 quantity 1000 (liters) 500 0 January
M ay
Se ptem be r
M onth
Figure 20. Water quantity required for cleaning a single block for different months.
8.1.2. Corrosion of the Collector Air Vent Valves A total of 76 air vent valves were installed on the arrays of solar collectors to vent the air out during the water filling up process. Water started to leak from these valves after few months of operation and several valves have to be replaced with spare ones. Because of a limited supply of vent valves, few of the leaking valves have to be plugged as a makeshift measure until new valves are procured, a procedure usually taking several months due to administrative delays. The problem with the leaky vent valves occurred soon after a power failure happened during a sunny day causing the heat collecting pump to shutdown while the water is still inside the collectors which caused partial evaporation of the water and frequent opening and closing of the vent valves. To prevent further damage to the vent valves, it was decided that plant re-start after the restoration of power following a power failure is made either early in the morning or at dusk. 8.1.3. Vacuum Loss Inside Glass Tubes As previously stated, the glass tubes operate under a high vacuum of 10-4 mmHg. High collector efficiency depends on maintaining this high vacuum level inside the collector. The vacuum level is monitored every year by checking the condition of the getter. At the end of the first year of operation, the condition of the vacuum on almost all glass tube was essentially as new. 8.1.4. Scale Prevention The most important item for the evaporator is scale prevention. There are two kinds of scale that could form in seawater distillation: a hard scale and a soft scale. The hard scale consists mainly of calcium sulfate (CaSO4) and very difficult to remove from the heat transfer surfaces once formed. The only way to avoid the formation of this scale is to operate the evaporator within the solubility limits of Ca+2 and SO42- ions in the brine. The evaporator was designed in such a way that in normal operation, the concentration of these ions are not allowed to reach saturation. On the other hand, soft scale which consists mainly of calcium carbonate (Ca CO3) and magnesium hydroxide (Mg(OH)2) can be avoided by injecting a chemical inhibitor such as Belgard EV into seawater feed. In our evaporator 10 ppm of Belgard EV is injected and was found satisfactory with the high-salinity seawater of the Gulf (52,000 ppm). Scale formation was monitored on an hourly basis during plant operation by
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observing the heat transfer coefficient of the heater (first effect) since it has the most likelihood of scale formation since it operates at the highest temperature. For an emergency, an acid injection system is used to carry out an acid cleaning procedure to remove any soft scale formed.
8.1.5. Anti-Corrosion Chemical for Use in the Heat Collecting Water An anticorrosive chemical must be used in the heat collecting water, which circulates through a closed system, to protect the equipment from corrosion. “High Clean CL-100” was selected in view of the heat collector tube material being of copper and the heat accumulator and piping material being of iron. “High Clean CL-100” was found to be effective in protecting both materials from corrosion. This chemical is a solution of alkanol-amino salt of nitrogen-containing condensate having the chemical symbol: [R-SO2NH(CN2)n COOH] where R = C6H5 and n = 1 to 3. The solution is a light brown transparent liquid having a pH of 8 – 8.5. A concentration of 5,000 ppm was recommended by the manufacturer. However, the concentration of the chemical as poured into the makeup water tank after draining and leakage was gradually reduced as the stock of the chemical decreased because the heat collecting water was forced to be drained more frequently than was planned due to unexpected power failures and pump troubles. The average concentration of the chemical in the collector water during the first year of operation was approximately 2,8000 ppm. Table 13 shows the results of analysis of the heat collecting water of four samples taken during the first year of operation. It can be seen that there was virtually no change in the total Fe content indicating an adequate anticorrosive effect for Fe. On the other hand, the Cu content tended to increase gradually as the concentration of the anticorrosive chemical drops. The thickness of the copper tubes corroded in the solar collector field was estimated at 0.001 mm/year[5]. Table 13. Chemical analysis of heat collecting water Sampling data
31 Jan. 85
27 Mar. 85
30 Jul. 85
21 Oct. 85
pH
8.6
8.5
7.9
8.2
Conductivity (μS/cm)
209
210
373
242
Temperature (oC)
-
20
28
18
M Alkalinity (ppm as CaCO3)
526
486
468
452
Total hardness (ppm as C(ppm)aCO3)
22
8
20
4
Chloride (ppm as Cl-)
37
21
44
33
Silica (ppm as SiO2)
1.3
2.0
1.9
2.8
Total iron (ppm as Fe)
1.6
1.82
1.1
1.4
Copper (ppm as Cu )
0.55
0.62
1.8
2.83
Total Nitrogen (ppm as N)
217
177
156
161
High-Clean CL-100
5,167
4,214
3,714
3,843
++
8.1.6. Measures Against Power Failure The original plant design was such that in the case of a power failure during the day, the heat collecting pump stops and the water in the collectors, subject to solar radiation, evaporates resulting in dangerous water hammer in the header pipes. In order to protect
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Ali M. El-Nashar
against such power failure, the solar field piping system was modified by installing three motorized valves (normally closed) on three 25 mmφ lines, one motorized valve (normally open) on the 125 mmφ on the outlet piping of the heat collecting pump and a check valve on the 125 mmφ on the return header pipe from the collector field to the accumulator. The modifications are shown in Figure 21. In the modified system, following a power failure, the three 25 mmφ motorized values will be open thus draining all the water in the collector field and the 125 mmφ motorized valve in the pump outlet will close thus preventing the collector water from flowing by gravity from the heat accumulator to the collector field. The modified system proved effective in protecting against the hazard of evaporation in the collector field. The collector field so not automatically restart following the restoration of power and the valves has to be rest manually by the operator.
Figure 21. Modifications to the solar collector field to protect against power failure.
8.2. Evaporating System 8.2.1. Evaporator Pump Maintenance Pump problems were one of the main causes of plant downtime. The plant had 12 pumps: seawater intake pump, seawater pump, seawater feed pump, brine blow-down pump, product water pump, vacuum pump, drain pump, heat collecting pump, heating water pump, drinking water pump, plant water pump and priming vacuum pump. All these pumps are motoroperated centrifugal pumps pumping seawater, brine or product water except the vacuum pump which is an oil ring-seal vacuum pump drawing in a mixture of vapor and noncondensable gas from the evaporator. Most of the pump problems were started by a highpitch noise and vibration which gets worse as time goes on. The pumps dealing with seawater
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or its brine were found to be more amenable to failure than the other pumps due to seawater corrosion problems that affect the pump bearings. Continuous operation of the evaporator had to be interrupted by pump trouble several times. The pumps which gave most of the problems were the drain pump, the seawater intake pump. Most of the problems were resolved by replacing the pump/motor bearings or replacing the mechanical seal (or packing material). Many emergency plant shutdowns happened because of “intake pit level low” signal due to air leakage through the shaft packing of the seawater intake pump because of a worn out packing material. The suction line of this pump operates at a vacuum due to the fact that the seawater suction point is below the pump level. The air leakage into the pump would break the vacuum and drastically reduces the pump flow. The drain pump gave a lot of trouble. All the drains from the evaporator was collected into a pit in which the pump suction line is immersed. A level switch is used to start and stop the operation of the pump. This pump was found to be easily clogged with debris which accumulates inside the pit and caused a relay trip due to motor over-current. To solve this problem, a fine screen was installed on the tip of the suction line inside the pit to prevent the trash from entering the pump. The screen has to be cleaned regularly and trash removed from it. The product water pump was another source of problems and was responsible for plant shutdown particularly in the first year of plant operation. Faulty bearings and a pump shaft were replaced.
8.2.2. Inspection of the Evaporator An overhaul was carried out at the end of one year of plant operation which consisted of: •
•
•
•
The first effect, which is subject to high temperature and hence high possibility of scaling was inspected after the first year of operation. An accumulation of silt (fine sand) approximately 1 cm thick was found on the bottom of the 1st effect and was removed. Blackened spots were seen on the outer surface of the first effect tube bundle but they remained the same as those at the start of plant operation and should cause no problems. Scale marks were seen on parts of the tube bundle of the first effect near the water chambers at the heater inlet and outlet, but they did not represent any advanced state. A re-inspection few months later revealed no advanced state. No abnormal conditions were seen on the 18th effect.
8.2.3. Change in Operating Sequence A modification was carried out in a part of the operating sequence so that the test plant could be safely operated. This change brought about the following improvements in plant operation: • •
If the intake strainer is clogged with foreign matter like seaweed, the seawater intake pump will be stopped temporarily. If the concentration of the discharged brine becomes too high, an alarm will be triggered and the plant shut down. This is to prevent scale formation on the heat
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Ali M. El-Nashar
•
•
transfer tubes if the flow of heating water increases more than necessary or if the feedwater quantity is reduced. If the product water quantity becomes too small, an alarm will be triggered and the plant shutdown. This is to prevent the product water pump fro running at no load if the temperature of the heating water drops enough to make water production too low. The manner of emergency plant shutdown will be either of the two types given below depending on the degree of emergency: o Immediate plant shutdown for motor relay tripping, too low seawater flow, or the like. o Gradual plant shutdown for too high first effect evaporator temperature, too high brine concentration, or the like.
8.2.4. Modification of the System for Injecting Anti-Scale Chemical The original plan called for a single system for injecting the scale preventing chemical “Belgard EV” into seawater feed. However, because the injection pump has failed during unmanned operation of the plant and it was feared that the plant could have been subjected to scaling, it was decided to modify the injection system to include the standby system as a secondary injection system. In case the primary injection system fails, the secondary system automatically turns on. 8.2.5. Modification of the Method of Feeding Sealing Water to the Priming Vacuum Pump Because the seawater level is lower than the level of the seawater intake pump, when the plant is not in operation, the seawater in the suction line of this pump drains back by gravity to the sea and the line is full of air. The priming vacuum pump, which is a water ring sealed vacuum pump, is used to prime (start) the seawater intake pump by insuring that this pump and its suction line is full of water. Seawater was initially used for the sealing water, but since the primary vacuum pump is operated at plant startup only, seawater inside the pump and sealing tank has caused considerable amount of rust and made the water brown. It was therefore decided that fresh water be used for the sealing water instead of seawater.
9. SIMULATION PROGRAM AND ITS VALIDATION 9.1. Simulation Program 9.1.1. Outline The performance of a solar desalination plant that uses solar energy as the heating source for a seawater evaporator is affected by the amount of solar radiation, ambient temperature and other climatic conditions. These conditions are extremely unstable and are subject to constant change. This means that computer-based simulation is indispensable if, to cope with these changes, the system operation states are to be grasped and the amount of product water annually is to be forecast. As shown with the basic design, computer simulation was used to investigate the operating characteristics even at the planning stage of the test plant. However, it was not possible to grasp with any accuracy the climatic conditions when design was commenced and
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forecasted values based on experience to date were used even for the performance of the various components. Subsequently, research operation was begun, actual climatic data were accumulated and the characteristics of the equipment started to become clear through the winter and summer component tests and the continuous operation tests. Thus, a new look was taken at the simulation program. As a result of comparing and examining the calculated values and th actually measured values, it was concluded that the program must be revised in order that the operation of the test plant was reproduced as faithfully as possible and more accurate forecasts were made to cope with different operating conditions and plants of different scales. The program was revised and manuals were prepared to use the program between October 1985 and January 1986.
9.1.2. Flow Chart of the SOLDES Program Evacuated glass tube-type of collectors are used and the absorber area can be varied from 500 m2 to 20,000 m2. The heat collecting system uses a bypass circuit. When the temperature of the heat collecting system drops below the set value, the bypass operation is performed, and once the temperature rises above the set value, operation is switched over to the accumulator side. Solar cell type control is excercised to start and stop the heat collecting water pump. The accumulator is treated as a thermal stratified type, and the temperature distribution inside the tank is determined while bearing in mind the inflow and outflow of the heat collecting water and heating water. The number of collectors used and the heating water flow rate are varied so that the maximum operating capacity of the evaporator is not exceeded. However, for the simulation, consideration was given to maximize the effective use of the collectors and a bypass circuit was installed between the accumulator and the evaporator. By this means, a system of control was adopted where some of the heating water returning from the evaporator is bypassed and forwarded to the evaporator so that the temperature of the heating water entering the evaporator is kept below the rating. This is particularly useful when the accumulator water temperature is excessively high. The evaporator capacity can be varied over the range of 100 to 2,000 m3/day, the maximum brine temperature can be varied from 60 – 80oC and the number of effects of the evaporator can be varied fro 13 to 32. The simulation program takes into consideration the influence of the heating water temperature, heating water flow rate, seawater temperature and seawater flow rate. Figure 21 is an abbreviated flow chart of the simulation program. The equipment specifications, calculation conditions and other data are input to the program and are divided into two groups: System data No. 1 and System data No. 2. The data input with the System data No. 1 group serve to output error messages and suspend the execusion of the calculations in cases where there are errors in the input data or where allowable ranges have been exceeded. Any calculation period ranging from one day to one year can be designated and a balance in the system is determined every 30 minutes in relation to the calculation loop. The calculation results can be output either by the day or by the month. The “SOLDES” simulation program for the solar desalination plant is composed of 22 subroutine programs, two sets of system data and four types of climatic data.
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Figure 22. Flow chart of Solar Desalination Plant computer simulation program.
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9.1.3. Program Input and Output Data In conducting a computer simulation of a solar desalination plant, input data need to be revised according to changes in plant specifications such as absorber area, accumulator capacity, or evaporator capacity. The items of data input that can be revised using program “SYDT1” are as follows: • • • • • • • • • • • • • • • • • • • • • • •
Title of simulation run Starting and finishing date of simulation Specifications of daily data print out for each month Correction coefficient of solar radiation by month Correction coefficient of ambient temperature by month Collector absorption area of field Azimuth angle of collector Collector support angle Tilt angle of absorber plate Heat collecting water flow rate Heat collection pump rated power consumption Heat accumulator capacity Heat accumulator initial temperature distribution Evaporator capacity Maximum brine temperature Number of effects of evaporator Heating water flow rate Seawater flow rate Power consumption of vacuum pump and other evaporator pumps By-pass valve open/close temperatures Evaporator start/stop temperatures Correction coefficient of dust influence Specification of collector cleaning days Table 14. Types of meteorological data which can be used in "SOLDES"
Data name
Solar radiation data
Ambient temperature data
MEDT1
Hourly ambient temperature Input of data obtained at the Abu Dhabi solar desalination plant Instantaneous ambient temperature by hour
MEDT3
Hourly total solar radiation on tilt surface Input of data obtained at Abu Dhabi solar desalination plant Instantaneous total solar radiation on horizontal surface by hour Daily total solar radiation on tilt surface
MEDT4
Daily total solar radiation on horizontal surface
Daily mean, daily maximum and daily minimum ambient temperature
MEDT2
Daily mean, daily maximum and daily minimum ambient temperature
Four types of meteorological data can be accommodated in the program (see table 14). The type MEDT1 is used in the solar desalination plant where the hourly global radiation and hourly ambient temperature were measured. The other types of meteorological data can accommodate hourly or daily global solar radiation on horizontal surface instead of tilt surface as well as hourly temperature or mean-max-min daily temperatures.
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9.1.4. Mathematical Models Mathematical models were developed for the different components in preparation of the simulation program “SOLDES”. The following models were developed : 1. Numerical Method to Estimate Solar Radiation on a Tilted Surface This model calculates the beam and diffuse components of solar ration on a tilted surface having the same angle as the absorber plate of the solar collectors given as input the following information: • • • •
Measured hourly solar radiation on a tilted surface and measured hourly ambient temperature (MEDT1) as the case in the solar desalination plant. Measured hourly solar radiation on a horizontal surface and measured hourly ambient temperature (MEDT2), Estimated daily total solar radiation on tilted surface and estimated mean, maximum and minimum daily ambient temperatures (MEDT3) Estimated daily total solar radiation on horizontal surface and estimated mean, maximum and minimum daily ambient temperatures (MEDT4)
The solar radiation on tilted surface, It is estimated from the following equation:
It = Ib + Id = I0 × P
1 sin( h )
1
1 + cos(α 0 ) 1 − P sin( h ) 1 × × cos(θ 0 ) + × I 0 × sin( h) × 1 − 1.4 × ln( P ) 2 2
(27)
If the atmospheric transmittance, P, is given as known data, hourly solar radiation on a tilted surface can be calculated from the above equation. However, the only data available is the hourly global radiation or the daily global radiation. Therefore, to proceed with the computer simulation, it is necessary to convert global radiation to hourly bean and diffuse components. This is achieved by estimating the hourly P values from Eq. 23 knowing the global radiation, then calculating the beam and diffuse components from the following the following equations:
Ib = I0 × P
Id =
1 sin( h )
× cos(θ 0 )
(28) 1 sin( h )
1 + cos(α 0 ) 1 1− P × 0 × sin(h) × × 2 1 − 1.4 × ln( P ) 2
(29)
When daily global radiation is available instead of the measured hourly values, the hourly solar radiation is first estimated using an iterative procedure then the beam and diffuse components are estimated from Eqs. 28 and 29[5].
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2. Effect of Shade on Solar Radiation on Absorber Plate The amount of solar radiation on the absorber plate is less than the amount falling on a tilted surface having the same angle as the absorber plate but situated in the open. This is due to the shading cast on the absorber plate by several collector components: • • •
Shade by the neighboring absorber plates (shade length = s1) Shade by the neighboring glass tubes (shade length = s2) Shade by the header box of the collector (shade length = s3)
Figure 23 shows the shadow length due to adjacent absorber plate (s1) and adjacent glass tube (s2). Figure 24 shows the shadow length due to collector header box (s3). The three shadow areas are shown in a plan view in Figure 25. Note that the area marked #1 represe
Figure 23. Shadow effect due to adjacent plate and adjacent glass tube.
These shadow effects are particularly evident in early morning and late afternoon but have a minimal effect throughout the rest of the time. Based on the solar angles (solar altitude and solar azimuth), absorber plate dimensions and tilt angle, pitch of absorber plates, glass tube diameter and collector header box height, a model was developed to estimate the hourly value of the length of the shade cast by each of the above three effects. We present here the results of this model.
l × [cos(α c ) × tan(hN' ) + sin(α c )] − L × tan(hN' ) Morning: s1 = cos(α c ) × tan(hN' ) + sin(α c )
(30)
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Figure 24. Shadow effect due collector header box.
Figure 25. Different shadow areas in a plan view.
Afternoon: s1 =
l × [cos(α c ) × tan(hN' ) − sin(α c )] + L × tan(hN' ) cos(α c ) × tan(hN' ) − sin(α c )
(31)
Multiple Effect Distillation of Seawater Water Using Solar Energy …
l l γ × sin(α c ) + − tan(hN' ) × [ L − × cos(α c )] ' 2 2 cos(hN ) Morning: s 2 = ' cos(α c ) × tan(hN ) + sin(α c ) l l γ − × sin(α c ) + − tan(hN' ) × [( L − × cos(α c )] ' 2 2 cos(hN ) Afternoon: s 2 = ' cos(α c ) × tan(hN ) − sin(α c )
s3 =
H × sin(γ N ) tan(hN )
125
(32)
(33)
(34)
With reference to Figure 25 we can write: Total area of absorber plate…………A = LT × l
(35)
Shadow area #1……………………...A1 = s3 × l
(36)
Shadow area #2………………………A2 = s1 × (LT – s3)
(37)
Shadow area #3……………………….A3 = (s2 – s1) × (LT – s3)
(38)
The area exposed to direct solar radiation is therefore the difference between the total area of the absorber plate, A, and the three shadow area, i.e. A4 = A – (A1 + A2 + A3)
(39)
It is convenient to introduce the ratios R1, R2, R3 and R4 such that
s3 × l A s × ( LT − s3 ) R2 = 1 A ( s 2 − s1 ) × ( LT − s3 ) R3 = A (l − s 2 ) × ( LT − s3 ) R4 = A R1 =
(40)
It is to be noted that areas #1 and #2 are completely shadowed by solid obstacles which does not transmit any radiation whereas area #3 (shadow due to adjacent glass tube) has an attenuated solar radiation due to the transmittance of three laters of glass through which each
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solar ray has to travel (see Figure 23). It is assumed that the daily average transmittance of the three glass layers is equal to 0.7. This assumption is suggested by the manufacturer (Sanyo) and is based on detailed hourly computer simulation. Consequently, the net beam radiation on the absorber plate can be expressed by the equation:
I b' = I b × ( R4 + 0.7 × R3 )
(41)
The net total radiation on the absorber plate is obtained by adding the diffuse component to the beam component
I t' = I b' + I d
(42)
Ambient temperature model When hourly ambient temperature data is not available, hourly data can obtained from knowledge of the daily mean, maximum and minimum values using a model developed for this purpose. 3. Effect of Dust on Transmittance of Glass Tubes The effect of dust on the transmittance of the glass tubes varies with the season. The heat collection amount drops sharply especially when there is a sandstorm and dust accumulates rapidly. This causes the transmittance of the glass tubes to drop. When it rains, on the other hand, the transmittance is restored because the rainfall washes away the dust. Climatic conditions in the UAE are such that there is little rainfall, but nevertheless, the cleaning effect of rainfall appears in the collector measurements. In the UAE, moreover, the temperature differences between day and night are relatively large; in the mornings, dew accumulates on glass tube surface and they become damp, so mucu so that water droplets sometimes fall from them. If the level of dew accumulation is slight, dust can easily adhere to the tube surface, but if the extent of dew is great enough, it will serve to wash away dust from the tube. The relationship between the cumulative level of dust affecting the transmittance of the glass tube and the cleansing effect of various natural climatic conditions is extremely complex. In order to develop a model of the effect of dust accumulation on the transmittance of the glass tube, it was assumed that the clean glass tube transmittance of 98% is restored after each tube cleaning and that following a tube cleaning the transmittance drops exponentially due to dust effect according to the equation (see Sayigh et al. [..]):
τ −τ m = exp(−0.055 × N ) τ 0 −τ m
(43)
Where τ is the transmittance after N days has elapsed since cleaning, τm is the transmittance after one month has elapsed since cleaning, τ0 is the transmittance immediately measured after cleaning (= 98%). The monthly drop in transmittance (τ0–τm) is dependent on the month with summer months experiencing larger drops than winter months due to the sandstorm prevailing mainly in summer months.
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4. Control of Heat Collecting Operation The solar collector field is operated by the solar controller which uses a solar cell to switch the heat collecting pump on and off depending on the solar radiation. The solar radiation condition for pump startup, Ion (kcal/hm2), and shutdown, Ioff (kcal/hm2), are determined from the measured values of the heat accumulator outlet temperature, Tw1 (oC) and the ambient temperature, Ta (oC) according to the relations:
I on ≥ 5 × (Tw1 − Ta ) − 25 I off < 5 × (Tw1 − Ta ) − 10
(44)
5. Heat Collection Amount from Solar Collector Field The heat collection efficiency is defined as the amount of heat collected divided by the amount of solar radiation falling on the absorber plates of the solar collector field and is expressed by the following formula:
η c = α + β .x + γ . x 2
(45)
where ηc is the collector efficiency, α,β,γ are constant parameters and x is a variable defined
1 − (Tc1 + Tc 2 ) − Ta , Tc1 and Tc2 are the collector field inlet and outlet water as: x = 2 I t' temperature and I’t is the solar radiation on the absorber plate. The rate of heat collected, Qc, from the solar field is obtained from the equation:
Qc = Ac .η c .I t' = mc .C p .(Tc 2 − Tc1 ) (46) Using Eqs. 34 and 35 the collector outlet temperature can be obtained as follows:
Tc 2 =
− C 2 − C 22 − C1C 3 C1
(47)
Where C1, C2 and C3 are given by the following equations:
C1 = γ . Ac C 2 = γ . Ac (Tc1 − 2Ta ) + β . Ac .I t' − 2mc .C p .I t' C 3 = γ . Ac .(Tc1 − 2Ta ) 2 + 2 βAc .I t' (Tc1 − 2Ta ) + 4α . Ac .I t'2 + 4mc .C p .I t' .Tc1
(48)
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With this equation the collector outlet water temperature can be obtained at each hour of the day given the inlet water temperature, the solar radiation, water flow rate, and the collector parameters αi,β and γ.
6. Evaporator Performance A simple model is used for predicting the performance of the MED evaporator at part load given the evaporator’s capacity, maximum brine temperature, number of effects, heating water flow rate, heating water temperature and seawater temperature. The aim is to calculate the hourly distillate production, the hourly heating water outlet temperature and the hourly pumping power requirement. The performance ratio and specific heat consumption of the evaporator depends on the number of effect and was estimated from the following equations provided by the manufacturer (Sasakura): Number of effects N ≤ 13:
PR = −1.875 × 10 −2 × N 2 + 1.15 × N − 1.625
(49)
Number of effects N > 13:
PR = −2.500 × 10 −3 × N 2 + 0.625 × N + 2.56
(50)
Specific heat consumption, SPC (kcal/kg):
SHC =
526 PR
(51)
The effective temperature difference per single effect δT at the design condition was estimated from the equation:
δT =
(T2 d − T1d − BPE av × N ) N
(52)
where T2d is the design brine maximum temperature in the first effect (top effect), T1d is the design brine temperature in the last effect (bottom effect), BPEav is the average boiling point elevation in the N effects. For the evaporator in the solar desalination plant the following values are used: T2d = 68oC, T1d = 40.7oC, BPEav = 0.71oC. The average heat transfer coefficient for the N effects, U (kcal/h m2oC) was estimated from:
U = (1888 × L + 1313) ×
C (T1 ) + C (T2 ) 2
(53)
where C is a correction coefficient which is dependent on the brine temperature, L is the load. The design value is that when L = 1.0, i.,.
Multiple Effect Distillation of Seawater Water Using Solar Energy …
U d = (1888 + 1313) ×
C (T1 ) + C (T2 ) 2
129
(54)
The correction coefficient can be expressed by the equation:
C (Tb ) = −0.4678 + 0.050 × Tb − 0.0005 × Tb2 + 0.17 × 10 −5 × Tb3
(55)
The operating condition of the evaporator depends on the load parameter L =(Md/Md100%). The operating temperatures for each load are evaluated as follows: Calculate the brine temperature in the last effect from knowledge of the seawater temperature and the condenser load:
T2 = Tc 2 + 1.2 = Tc1 +
Qc + 1.2 m sw × C p
= Tc1 +
0.9Qh + 1.2 m sw × C p
(56)
In this equation the assumption is made that the condenser load, Qc, is 90% of the heating load, Qh due to heat loss to the environment. It is also assumed that the last effect brine temperature is smaller than the condenser outlet temperature by 1.2oC. These assumptions are verified by actual measurements at the evaporator of the solar plant. Calculate an approximate value for the first effect temperature, T1,
T1 = T2 + ( L × δT + BPE ) × N
(57)
Calculate an average overall heat transfer coefficient for the N effects,
U = (1888 × L + 1313) × •
(58)
Calculate an improved value for the first effect temperature, T1,
T1 = T2 + ( L × δT × •
C (T1 ) + C (T2 ) 2
U + BPE ) × N Ud
Iterate to get improved values for T1.
The heating water outlet temperature was assumed to be equal to the first effect temperature: Th2 = T1 and the heating water inlet temperature is calculated from a heat balance equation:
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Th1 = Th 2 +
Qh mh × C p
(59)
The power consumption (in kW) of the evaporator was assumed to depend mainly on its capacity and was estimated from the following equations provided by the manufacturer (Sasakura): Evaporator capacity md ≤ 500 m3/day:
P = −1.25 × 10 −5 × md2 + 9.0 × 10 −2 × md + 5.125 + Z
(60)
Evaporator capacity md ≥ 1000 m3/day:
P = −6.00 × 10 −6 × md2 + 5.1 × 10 −2 × md + 32.0 + Z
(61)
Evaporator capacity 500 m3/day < md < 1000 m3/day
P = −4.48 × 10 −5 × md2 + 0.1272 × md − 5.4 + Z
(62)
where Z is the pumping power (kW) of the vacuum pump and is given by:
Z = 0.050535 × md + 0.93045
(63)
9.2. Comparison of Simulation and Actually Measured Values In order to determine the accuracy of the simulation program, a comparison between the simulation results and the results from actual plant operation was conducted for January and June 1985. The operating condition of the test plant underwent various changes over the test period and are not constant. The plant had also experienced several power failures that caused complete shutdown and the plant had to be restarted manually after the restoration of power. The power failures that occurred during the test period (January and June 1985) are listed in table 15. Table 15. Power failures causing emergency shutdown Month January 1985
June 1985
Date 21 28 29 16 22 24
Time 11:10 16:30 14:30 0:41 9:35 13:15
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131
In order to account for the variation in the operating parameters occurring during the month as well as the emergency shutdowns that occurs during each month, each monthly period is divided into a number of smaller periods with the operating parameters maintained constant during each small period. The computer program is run for each small period using the prevailing operating condition of the test plant. The operating parameters which were input to the program are: • • • • • • •
Collector absorber area in service (January: 1543.5 m2 – 1837.5 m2, June: 1543.5 m2) Simulation start and end dates (January: 1st – 20th, June: 1st – 15th) Temperature of heat accumulator at the start of simulation period (bottom 64.0oC, top 76.5oC) Heating water flow rate (16.5 m3/hr) Monthly bypass valve open and close temperatures (open: 70.0oC, close: 73.0oC) Monthly evaporator start and stop temperatures (start: 72.0oC, stop: 66.0oC) Specification of collector cleaning days (January: 1st, 30th, June: 8th)
Figure 26 shows the measured and simulation results of the daily net amount of heat collected by the solar collector field and delivered to the heat accumulator during the month of January 1985. This amount is equivalent to the total heat collected minus the heat loss due to the collector piping system as well the heat loss due to dust effect on the glass tubes of the collectors. January is usually characterized by severe variations in the daily solar radiation and this variation is reflected on the daily amount of heat collected as shown in the figure. Figure 27 shows the measured and simulation results of the daily water production for January 1985. The simulation results appear to be in reasonable agreement with the measured values with the exception of January 6 for which there is a large discrepancy between measured and simulation values. This is because, while the operation of the evaporator was stopped at 11:30 due a drop in the temperature of the heating water in the actual plant, operation of the evaporator was continued in the simulation until 19:30 when it was stopped. This, in turn, was due to the fact that in the simulation the temperature of the heating water was slightly higher than the set level at which operation was to stop. Daily Heat Collected for January 1985
Daily heat collected (10 6 kcal/day)
6 5 4 3 2 1
Measured
0
Simulation 0
5
Pow er failure 10
15 Day
Figure 26. Daily heat collected for January 1985.
20
25
30
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Water production (m3/day)
Daily Wate r Production (m 3 /day) for Januar y 1985 140 120 100 80 60 40 20 0
Pow er 0
10
20
30 M e as ur e d
Day
Sim ulation
Figure 27. Daily water production for January 1985.
Figure 28 shows the simulation and measured values of the net amount of heat collected for June. The agreement seems to be quite good. Figure 29 shows the results of the daily water production for June. It is observed that the simulation result for the water production on June 1 is low. It appears that this happened because the initial temperature setting of the accumulator at the start of the calculations was lower than the actual temperatures. On June 24, the actual operation data are missing starting from 11:30 because of a power failure. To remove the dust on the glass tubes in June, blocks A and B were cleaned on June 4 and blocks D and E on June 8 while block F was cleaned regularly every 4 or 5 days. In the simulation, on the other hand, all blocks were presumed to have been cleaned on June 8. In June, the effect of the dust was significant and it appears that an error was produced due to the differences between the dust model and the actual dust accumulation. Nevertheless, the value for the amount of heat collected from June 10 through June 20 match relatively well since by this data the dust has been removed. As indicated here, there were areas where the simulation did not match the actual operation status exactly but, overall, the simulation was quite accurate even in cases where the evaporator was frequently started and stopped, as it was in January.
Daily heat collected (10 6 kcal/day)
Daily Heat Collected (106 kcal/day) for June 1985
7 6 5 4 3 2 1 0
Pow er
Measured Sim ulation 0
5
10
15 Day
Figure 28. Daily heat collected for June 1985.
20
25
30
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133
Daily production (m3/day)
Daily Water Production (m 3/day) for June 1985 150 100 Measured
50
Pow er
Simulation
0 0
5
10
15
20
25
30
Day
Figure 29. Daily water production for June 1985.
Table 16 shows a comparison between the actually measured values and the calculation values for January and June. Although the operation of the evaporator and the heat collection operation are greatly influenced by subtle changes in the set temperature conditions for operation and the ever-changing climatic conditions, it can be seen that the two sets of figures match relatively well. Consequently, it is assumed that this program will be quite serviceable for studying the optimum operating conditions of the test plant and also for designing a similar plant under different conditions. Table 16. Comparison between measured and simulation results for January and June 1985 Heat collection amount (kcal/month)
Product water amount (m3/month)
Simulation Measured Error (%) Simulation Measured Error (%)
Jan. 1985 120,100,000 115,100,000 4.3 2,290 2,340 -2.1
Jun. 1985 152,400,000 153,100,000 -0.45 3,340 3,430 -2.6
10. EVALUATION OF THE TEST PLANT 10.1. Optimum Operating Conditions The simulation program of the test plant was run after inputting the values for the following: • • • •
Performance of individual equipment of the plant obtained from the research operation (for example, the collector efficiency y= 0.84 – 2.46 x – 1.9 x2, and the maximum capacity of the evaporator = 6.0 m3/h). Weather conditions for January through December 1985 (average solar radiation over inclined surface = 5,589 kcal/m2day, average daily atmospheric temperature = 27.4 o C, and average seawater temperature = 27.5oC). Standard operating conditions of the test plant as shown in table 17. Heating water quantity (variables) = 12, 13.5, 15, 16.5, 18, 19.5 and 21 m3/h.
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Ali M. El-Nashar Table 17. Operating condition of test plant for simulation calculations Item Collector absorber area Heat collection water flow Frequency of solar collector cleaning Maximum brine temperature Seawater flow rate Feedwater flow rate Evaporator startup temperature Evaporator shutdown temp.
Value 1862 m2 83.6 m3/h Once a month 68oC 36.7 m3/h 17.5 m3/h Heating water temp. corresponding to 80% load Heating water temp. corresponding to 60% load
A summary of the results of the simulation is shown in table 18. As seen from this table, a heating water quantity of 16.5 m3/h results in the maximum water production: 43,400 m3/year or 118.9 m3/day. However, the plant should not be operated such that TME110 (i.e., the number of hours the plant is operated at above 110% load) exceeds 5% of any months total operating hours. The data in table 18 show the following in terms of TME110: • • •
TME110 for April is 7.6% even if the heating water flow rate is reduced to 12 m3/h. TME110 for the other months can be below 5% when the heating water flow rate is 16.5 m3/h or below. By increasing the heating water flow to 18.0 or 19.5 m3/h without allowing TME110 to exceed 5%, the water production for the month concerned can be increased over that for the heating water flow of 16.5 m3/h.
Table 18. Summary of simulation results for different heating water flow rates Month Jan.
Feb.
Mar.
H/W flow m3/h 21 19.5 18 16.5 13.5 12 21 19.5 18 16.5 15 13.5 12 21 19.5 18 16.5 15 13.5 12
Production m3/month 2360 2530 27600 2890 2830 2740 3680 3710 3700 3680 3640 3600 3560 3680 3860 3870 3850 3820 3780 3740
TME110 hrs 11 10 0 0 0 0 267 207 109 68 46 23 5 291 233 190 126 85 41 14
Startups 28 20 11 5 4 7 1 0 0 0 0 0 0 8 2 1 1 1 1 1
Multiple Effect Distillation of Seawater Water Using Solar Energy … Table 18. (Continued). Month Apr.
May
Jun.
Jul.
Aug.
Sep.
Oct.
H/W flow m3/h 21 19.5 18 16.5 15 13.5 12 21 19.5 18 16.5 15 13.5 12 21 19.5 18 16.5 15 13.5 12 21 19.5 18 16.5 15 13.5 12 21 19.5 18 16.5 15 13.5 12 21 19.5 18 16.5 15 13.5 12 21 19.5 18 16.5 15 13.5 12
Production m3/month 4030 4050 4040 4010 3990 3950 3900 3940 3980 3950 3940 3910 3850 3830 3940 3930 3900 3870 3840 3800 3750 3350 3440 3420 3400 3350 3340 3310 3850 3860 3860 3830 3790 3750 3700 4050 4050 4020 3990 3960 3920 3870 3800 4010 4000 3970 3930 3890 3850
TME110 hrs 428 385 355 317 227 140 55 224 89 53 21 2 0 0 212 163 72 33 18 4 0 16 10 4 2 0 0 0 70 60 19 8 2 0 0 350 291 131 74 42 12 0 149 85 58 30 11 4 1
Startups 1 0 0 0 0 0 0 3 1 1 0 0 1 0 0 0 0 0 0 0 0 6 1 1 1 2 1 1 3 1 1 1 1 1 1 0 0 0 0 0 0 0 9 0 0 0 0 0 0
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Ali M. El-Nashar Table 18. (Continued). Month
H/W flow m3/h 21 19.5 18 16.5 15 13.5 12 21 19.5 18 16.5 15 13.5 12 21 19.5 18 16.5 15 13.5 12
Nov.
Dec.
Total
Production m3/month 2830 3180 3300 3340 3320 3280 3190 2150 2170 2370 2600 2650 2580 2420 41700 42800 43200 43400 43000 42600 41900
TME110 hrs 3 0 0 0 0 0 0 0 0 0 0 0 0 0 2020 1532 989 677 421 223 74
Startups 24 9 4 1 1 1 1 28 27 18 7 4 4 12 111 61 37 16 10 13 23
Table 19. Optimum operating conditions for the Abu Dhabi solar desalination plant Month
Absorber area (m2)
H/C flow (m3/h)
Jan. Feb. Mar. Apr. May. Jun. Jul. Aug. Sep. Oct. Nov. Dec.
1862 1862 1862 1764 1862 1862 1862 1862 1862 1862 1862 1862
83.6 83.6 83.6 79.2 83.6 83.6 83.6 83.6 83.6 83.6 83.6 83.6
Bypass valve Open (oC) 63 65 68 69 70 71 70 72 74 69 67 65
Bypass valve Close (oC) 67 69 72 69 74 75 74 76 78 73 71 69
H/W flow (m3/h)
F/W flow (m3/h)
Evaporator Start (oC)
Evaporator Stop (oC)
16.5 13.5 12.0 13.5 16.5 16.5 19.5 18.0 13.5 16.5 16.5 15.0
17.5 17.5 17.5 17.5 17.5 17.5 17.5 17.5 17.5 17.5 17.5 17.5
67 70 73 73 73 75 74 76 78 73 71 69
62 64 67 68 69 70 69 71 73 68 66 64
Since it was found that the quantity of heat collected in April exceeds the allowable capacity of the evaporator, the collector absorber area for April needs to be reduced in order to protect the evaporator from scaling. In order to find the number of arrays that need to be taken out of service during April, the simulation program was run for different number of arrays in operation. It was found that 4 arrays of the 76 arrays available need to be drained making the available absorber area for this month 1,764 m2. The other operating conditions are as given in table 17. These results translate into the optimum operating conditions shown in table 19.
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10.2. Simulation Results Simulated operation of the test plant under the optimum operating conditions noted above was carried out using the solar radiation data of 1985. The results are shown in table 20. The effective annual water production is 42,900 m3, the annual operating rate of the evaporator is 97.6% (number of evaporator starts and stops = 13), and the specific power consumption is 5.1 kWh/m3 of product water. Table 20. Simulation results at optimum operating condition Item Total radiation on tilt surface Drop in solar radiation due to dust Heat collection amount Amount of heat supplied to heat accumulator Heat supplied to evaporator Heat effectively used by evaporator
Simulation output 3,780,000,000 kcal/year 195,000,000 kcal/year 2,212,000,000 kcal/year 1,950,000,000 kcal/year 1,808,000,000 kcal/year 1,796,000,000 kcal/year
Product water Collector cleaning water Effective product water Heat collecting pump running hours Evaporator operating hours Frequency of operator startup Power consumption per m3 Anti-scalant consumption (Belgard EV) Sodium hypochlorite consumption (NaClO)
43,000 m3/year 76 m3/year 42,900 m3/year 3,655 hr/year (10.0 hr/day) 8,546 hr/year (yearly average rate 97.6%) 13 times/year 5.1 kWh/m3 1,496 kg/year (0.035 kg/m3 product) 5,577 kg/year (0.13 kg/m3 product)
Ratio 1.0 0.052 0.585 0.516 0.478 0.475
10.3. Evaluation of the Solar Plant In this section we compare the planned values used in the design of the solar plant, the experimental results of the research operation obtained during the first year of plant operation and the values introduced in the simulation program which are based on the measured values. The results are summarized in table 21. Column one of this table shows the design values; column two the results of actual measured performance data and column three shows the introduced in the simulation program.
A. The Solar Collector Field The heat collection efficiency of the solar collectors was about 9% lower than that for the basic design under the same weather conditions. The efficiency of a clean single collector was measured at the manufacturer’s laboratory under ideal operating conditions and was reported as the catalog efficiency, ηoc, which can be represented by the following equation:
ηoc = 0.913 – 2.46 x – 1.92 x2
(64)
where x is a parameter defined as : x = {(To + Ti)/2 – Ta}/It and the unit of oC hr m2/kcal. When a number of collectors are connected together to form a block in the solar collector
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field, the efficiency of such a clean block was measured and found to fit the following equation:
ηm = 0.84 – 2.46 x – 1.92 x2
(65)
The measured efficiency is therefore lower than the catalog efficiency by about 8% for x = 0 and 9.3% for x = 0.05 oC hr m2/kcal. The drop in collector efficiency of a group of interconnected collectors can be attributed to the heat loss by internal piping and connectors. In the basic design, the influence of dust deposition on the solar collectors was assumed to cause a 10% loss of the incoming solar radiation. Measurements of the heat loss due to dust effect carried out during plant operation showed that the influence of dust deposition has a seasonal character with the loss in solar radiation varying from 4% during winter months to as much as 20% in the summer. To account for the monthly variation of the dust effect in the simulation program, a mathematical model was developed to estimate the dust effect from month to month. Heat loss from the collector piping system is another cause of heat loss that has to be accounted f-cor. The piping system consists of insulated pipes varying in diameter from 30 mm to 125 mm as well as valves, pipe supports, expansion joints and safety valves. In the basic design, heat loss from the piping system was estimated based only on heat loss from all the pipes with heat loss from valves, supports, etc. neglected. Measurements were made to estimate the total piping loss which takes into consideration all components of the piping system. For a single block, the measured heat loss from the piping system was correlated by the following formula:
Qloss-m = 66.6 (Tw – Ta)1.3 kcal/hr
(66)
The theoretical (calculated) value of the piping heat loss excluding valves, supports, etc. was estimated as:
Qloss-c = 93.5 (Tw – Ta) kcal/hr
(67)
For a (Tw – Ta) = 40oC , the measured heat loss is 2.15 times the theoretical value.
B. The Heat Accumulator The heat accumulator (HA) in the solar plant consists of 3 series-connected thermally stratified vertical cylinders. Heat loss from the accumulator tanks was estimated in the basic design as 1.05oC per day for a water temperature of 99oC and an ambient temperature of 30oC. For a storage capacity of 300 m3 of water, the estimated daily heat loss is 315,000 kcal/day. Heat loss measurements from plant heat balance indicates that daily temperature drop varies from month to month with the average yearly value of 2.61oC per day which is more than double the value used in basic design. This value is also based on a water temperature of 99oC and ambient temperature of 30oC.
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C. The MED Evaporator As seen from table 21, the evaporator is the only piece of equipment in which the performance in the basic design was upgraded in the simulation program: 20% up in water production capacity, and 0.2 to 7.5% less in specific heat consumption. In the basic design, the maximum evaporator capacity was 120 m3/day (5 m3/hr) and specific heat consumption is 43.8 kcal/kg- product at 35oC seawater temperature and 55,000 ppm salt concentration. This design maximum production was assumed to be achieved at a heating water (HW) temperature of 99oC and a HW flow rate of 18.4 m3/hr. Measured values of maximum production was 130 m3/day (5.42 m3/hr) at a corresponding specific heat consumption of 42.4 kcal/kg- product. Bas ic De s ign He at Balance incide nt s olar r adiation = 100%
us e ful he at to e vapor ator 36%
colle ctor he at los s 43%
e vapor ator los s 3% accum ulator colle ctor los s piping los s 3% 5%
los s by dus t de pos ition 10%
(a) Measured Heat Balance incident solar radiation = 100%
collector heat loss 36%
useful heat to evaporator 48%
loss by dust deposition 5% evaporator loss 0.3%
accum ulator loss 4%
collector piping loss 7%
(b) Figure 30. Total plant heat balance - comparison between design and simulation values.
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The design and measured annual plant heat balance are shown in pie chart form in figure 30. In this figure it is assumed that the incident solar radiation represent 100% and the percentage of this energy going to each of the different losses are specified along with the net amount of useful energy for desalination. The effective heat input to the evaporator increased a remarkable 11.5% from 36.0% for the basic design to 47.5% in terms of the ratio to the total solar radiation quantity on the collector tilted surfaces. This sharp increase combined with the improved heat efficiency of the evaporator to produce a synergistic effect: The water production increased from an annual average of 80 m3/day for the basic design to 117.8 m3/day, and the effective water production (after subtracting the quantity of water used for cleaning the collectors) was 117.5 m3/day, a dramatic 46.9% increase. In addition to using performance data from actual plant measurement, the simulation program incorporates various improvements, which include: • •
Adopting a heating water temperature control system based on a three-way proportional control valve for efficient use of the energy of the collected heat. Reducing power consumption by adopting pumps with appropriate capacity (several pumps used in the solar plant are oversized).
Table 21. Comparison between performance values used in basic design, measured values and simulation program Item Heat collection efficiency
Basic Design Catalog efficiency: η = 0.913 – 2.46 x – 1.92 x2 x={ (Ti + To)/2-Ta}/ It o C hr m2/kcal
Heat loss from piping
Dust influence
Heat collecting system
Calculated value ignores valves and piping supports. For a single block: Qloss = 93.5 (Tw – Ta) kcal/hr Tw = water temp., Ta=air temp. It is assumed that the solar radiation is reduced by 10% due to dust effect throughout the year Bypass operation is not considered. Water enters the accumulator immediately after pump start up.
Measured value Value of η when x=0 is: Winter = 0.83 ~ 0.84 Summer = 0.80 ~ 0.81 Average = 0.82 Slope of curve is: Winter = large Summer = small Efficiency of block F includes heat loss from internal piping and dust effect Value measured for a single block is: Qloss = 66.6 (Tw – Ta)1.3 kcal/hr
Dust effect varies seasonally. In winter about 4% and in summer reaches more than 20%. A heat collecting system using bypass operation and control valves are used.
Simulation * Efficiency used for simulation is: η = 0.84 – 2.46 –1.92 x2 * For completely clean condition, the value of η for x=0 has been increased by 0.2 to 0.84 because of the fact that dust isn’t completely removed after cleaning. Value used is: Qloss = 66.6 (Tw – Ta)1.3 kcal/hr
Based on measured values, a model was developed to estimate the monthly dust influence. Heat collection amount takes into consideration bypass operation.
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Table 21. (Continued). Item Heart accumulator
Basic Design * When calculated heat loss from accumulator is converted to ΔT = Tw – Ta = 69oC, the heat loss is Qloss = 312123 kcal/day. * Heat loss is based on complete mixing in the tank and no stratification considered
Measured value * Based on measured values the heat loss at ΔT = 69oC is Qloss = 765000 kcal/day. * Thermal stratification ratio was measured as 7.5% during daytime and 6.5% at night
Simulation * After heat loss is calculated, compensation is performed using (Qloss)measured/(Qloss)calc.=2.45 * Heat accumulator is divided into 1000 equal parts, mixing takes place at the top and bottom of tank. Mixing at top = 7.5% and mixing at bottom = 5.0%.
Operation of evaporator when excessive heat is collected
The evaporator can be operated up to a boiling temperature of 100oC.
Adjust the heat collecting area or the heating water flow rate so that the load of the evaporator does not exceed 110%.
Evaporator water production Evaporator operating flow rates
Max. capacity = 5 m3/hr
Max. capacity = 6.46 m3/hr
Install a 3-way proportional control valve between the heat accumulator and the evaporator in order to control the heating water temperature so that the load of the evaporator does not exceed 110%. Max. capacity = 6.0 m3/hr
* Heating water flow rate = 18.4 m3/hr * Feedwater to evaporator = 10.5 – 17.5 m3/hr * Seawater to evaporator = 39.4 m3/hr
* Heating water flow rate = 12 – 17 m3/hr * Feedwater flow rate = 17 – 21 m3/hr * Seawater flow rate = 36 –40 m3/hr
* Heating water flow rate = 11.2 – 22.4 m3/hr * Feedwater flow rate = 17.5 m3/hr * Seawater flow rate = 20.2 –40.3 m3/hr
Operating temp. at 5 m3/day load: H/W inlet temp. = 99oC H/W outlet temp. = 87oC 1st effect temp. = 83oC 18th effect temp. = 43oC SW temp.(design value) = 35oC SW concentration = 55,000 ppm
Operating temp. at 5 m3/day : Jan. Jul. 71oiC 79oC 58oC 66oC 66oC 58oC 28oC 39oC o 21.8 C 32.4oC
Operating temp. at 5 m3/day load 78.5oC 67.5oC 67.5oC 40.8oC 35oC
51,200
52,000
Evaporator operating temperatures
53,500
11. ECONOMIC CONSIDERATIONS AND COMPARISON WITH CONVENTIONAL MED PLANTS On the basis of data obtained from the research operation of the test plant, an economic study was made to estimate the cost of water from solar MED plants with a capacity in the range 100 – 1000 m3/day and compare the results with conventional MED plant. The pumping power of the solar and conventional MED plant is to be provided by a diesel generator of appropriate capacity. Steam for the conventional MED plant is to be provided by a steam generator. The product water costs of these practical plants were calculated and are
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shown below. Note that these trial designs incorporate improvements such as the inclusion of the three-way proportional control valve.
11.1. Basic Economic Parameters The product water cost was calculated using the following economic parameters: •
•
Expected life of plant components o Evaporator…………………..20 years o Heat accumulator……………20 years o Solar collectors………………20 years o Diesel generator……………..10 years Interest rate……………………………8% per annum
11.2. Capital Equipment Cost 11.2.1. Capital Cost of MED Evaporator The cost of MED evaporator is based on budget offers from different manufacturers and on cost information available in the open literature. The capital cost depends on the design capacity, number of effects and maximum brine temperature according to the correlation given by Fosselard et al.[6]:
C ev = 5,005,000( where Cev md PR Tbmax
md 0.7 PR 0.5 70 0.47 ) ( ) ( ) 2,500 8 Tb max
100 ≤ md ≤ 1000
(68)
= evaporator capital cost, $ = rated (design) capacity, m3 day–1 = performance ratio = design maximum brine temperature, °C.
The performance ratio (PR) of the evaporator (defined as the distillate output in kg per 1055 kJ of heat input) is related to the number of effects by the following equation[1]:
PR = −0.809 + 0.932N − 0.0091N 2
(69)
11.2.2. Capital Cost of Solar Thermal Collectors Solar collectors used for this application should be capable of producing hot water at a temperature ranging between 70 and 90°C. Evacuated tube collectors and high-efficiency flat plate collectors can be used to produce hot water at a temperature in excess of 80°C. The specific cost of the solar collectors are assumed to range 200 - 600 $ m–2 (flat plate and evacuated tube collectors). The cost is assumed to include both the solar collector proper as well as the support structure, piping, valves, etc.
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11.2.3. Capital Cost of Heat Accumulator The heat accumulator is assumed to be a vertical cylindrical tank made of mild steel with a thick layer of fiberglass insulation to reduce heat loss. The tank is designed to operate at atmospheric pressure and is provided with a pressure relief valve as a safety measure. Hot water from the collector field is supplied to the tank at the top via a special water distribution grid that ensures that hot water diffuses slowly through the surrounding water with causing too much turbulence in order to enhance thermal stratification through the tank. The capital cost of the heat accumulator as obtained from manufacturer’s data is obtained from the following relation
C st = 7803.9 × m st0.525 100 ≤ mst ≤ 600 where, Cst mst
(70)
= cost of heat accumulator, $ = storage capacity, m3
11.2.4. Capital Cost of Steam Generator for Conventional MED Systems Low pressure and low capacity steam generators are required to supply the MES evaporator with the low-temperature thermal energy necessary to drive the unit. The capacity of the steam generator depends on the capacity of the MES unit as well as its performance ratio. For a unit having a PR = 13 and having a capacity 200 m3 day–1 at design conditions, requires an estimated 0.6 ton h–1 of low-pressure steam. A fire-tube packaged steam generator producing steam at 10 bar and having an efficiency (LHV) of 86 per cent is considered appropriate. The capital cost of such unit, Cb ($) is obtained from [7] and adjusted to the current cost level using the Marshall and Swift Equipment Cost Index. The resulting correlation is shown below:
C b = 115,700 + 18,200 × where, Cb ms
ms 12
0.15 ≤ ms ≤ 12
(71)
= capital cost of steam generator, $ = steam generating capacity, ton h–1
11.2.5. Capital Cost of Diesel Generator A diesel generator whose capacity will obviously depend on the capacity of the plant itself can supply the electrical demand of the desalination plant. The capital cost of such diesel generator is obtained from the following relation:
C dg = 50 800 (
P 0 .5494 ) 40
where Cdg is the cost in $ and P is the rated power in kW.
(72)
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11.3. Operation and Maintenance Expenses 11.3.1. Consumable Chemical Expenses The cost of consumable items is as follows: •
Cost of chemicals o Scale preventive (Belgard EV) o Anti-corrosive (Nalco 2000) o Seawater disinfection (NaClO) o Caustic soda o Sodiun bisulfite o Coagulant o Calcium chloride
3.42 $/kg 9 $/kg 0.40 $/kg 1.78 $/kg 0.97 $/kg 3.4 $/kg 0.81 $/kg
Chemical consumption for the solar MED plant were estimated from the following assumptions: o o o o o o
Belgard EV to be added to the feed water at 10 ppm Nalco 2000 to be added at 7,000 ppm to the makeup water, amounting to 30% of the accumulator capacity per year. Sodium hypochlorite (NaClO) to be added to intake seawater at 18 ppm Sodium hypochlorite (NaClO) to be added to product water at 2 ppm Sodium bicarbonate (NaHCO3) to be added to product water at 23 ppm Calcium chloride (CaCl2) to be added to product water at 18 ppm
11.3.2. Electrical Energy Consumption Electrical energy consumption by the solar-MED and conventional MED systems are provided by a diesel-generator of appropriate capacity. • • • • • • •
Fuel consumption of diesel generator Cost of one liter of diesel oil (cf) One barrel of oil = 167 liter Cost of one barrel of oil Cost of electricity Electricity consumption (solar MED) Electricity consumption (conv. MED)
3.0 kWh per liter of diesel oil cbarrel/167 $/liter 50 –120 $/barrel = cf/3.0 $/kWh kWh/m3 product water kWh/m3 product water
The electrical power required by the solar MED plant consists of the following components: •
Pumping power for the evaporator which is given by:
Pev = ( 4 . 805 + 0 . 094 × m d − 2 . 1 × 10
−5
m d2 ) × ( 2 . 1 + 0 . 06 × PR ) / 2 . 88
(73)
Multiple Effect Distillation of Seawater Water Using Solar Energy … •
Power of the vacuum pump
Pvac = −1.866 + 0.057 × md − 2.7 × 10 −6 × md2 •
(74)
Power of the heat collecting pump
Pc = [83.6 × ( •
145
Ac 1.13 )] × 2.691 × 10 − 2 1862
(75)
Power of the heating water pump
Phw = 1.5 × (
md ) 130
(76)
Thus, the total pumping power, kW, can be expressed as
P1 = Pev + Pvac + Pc + Phw
(77)
The electrical power required by the conventional MED plant consists of the following components: • •
Pumping power of the evaporator as before Pumping power for the steam generator
The pumping power of the steam generator was estimated from the relation:
Pb = 65.0 ×
ms 15.0
(78)
where ms is the design capacity of the steam generator, ton/hr. The steam generator is capable of providing low-pressure heating steam for the MED evaporator and medium pressure steam to a steam ejector to create the operating vacuum inside the evaporator. The total electrical power required by the conventional MED plant is:
P2 = Pev + Pb
(79)
11.3.3. Spare Parts Cost An amount of 2% of the direct capital investment has been estimated as yearly cost of spare parts.
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11.3.4. Personnel Cost The staff required for operation and preventive maintenance (for 3 shift operation) are assumed as follows: Plant capacity
Supervisor
Mechanic
Electrician
Chemist
helper
100 – 300 m3/day
1
2
1
0.5
2
300 – 1000 m3/day
1
4
2
1
4
Monthly salary $
1000
600
600
600
400
The above estimates results in a cost of water due to personnel of 1.5 $/m3 for a 100 m /day plant and 0.27 $/m3 for a 1000 m3/day plant. 3
11.4. Estimating the Cost of Water Produced The estimates of the cost of water that are given below are based on the life-cycle cost analysis of the plant which includes capital, OandM and fuel costs. The total life-cycle cost, TLC, is the sum total of the capitals cost plus the present value of all future OandM annual expenses:
TLC = Ctot + PW (F) + PW (OM)
(80)
where, Ctot = total capital cost including engineering, installation and management costs, PW (F) = present worth of all annual fuel costs incurred throughout the lifetime of the plant (for conventional plants), PW (OM) = present worth of all annual OandM expenses incurred throughout plant lifetime. The present worth of the annual fuel and OandM expenses are calculated from the following expressions [5]
PW ( F ) = F0 (
1+ g f k − gf
)[1 − (
1+ g f 1+ k
)N ]
1 + g om 1 + g om N )[1 − ( ) ] PW (OM ) = OM 0 ( 1+ k k − g om where F0 OMo gf gom k
= fuel cost in the first year of operation, $ = OandM cost in the first year of operation, $ = annual fuel escalation rate (assumed 0.03) = annual OandM cost escalation rate (assumed 0.03) = interest rate (assumed 0.08)
(81)
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147
= plant lifetime, years (N = 20 years)
The cost of water, cw, ($/m3) was calculated as follows
cw =
where, md PF
TLC md (365) N ( PF )
(82)
= desalination plant rated capacity, m3/day = plant factor (assumed 0.85)
It should be noted that all water costs given in this section do not include seawater intake and outfall costs or cost of land. These additional costs are very much site dependent and has to be added to the cost estimates given here.
12. RESULTS OF THE ECONOMIC STUDY Figure 31 shows how the cost of water varies with the number of effects and cost of collector (in $/m2) for a solar MED plant having a capacity of 130 m3/day which is identical to that of the test plant. The design maximum temperature Tb = 90oC and the fuel cost is assumed to be cb = 50 $/barrel. The cost of water is seen to be quite sensitive to the number of effects and to a lesser degree on the cost of collector with the cost of water varying between 8 $/m3 and 4 $/m3. The water cost tends to decrease with increasing the number of effects and reducing the cost of collector. The increase in the number of effects results in an increase in the performance ratio and thus leads to a reduction in the heat demand of the evaporator for a given water production. Since this heat demand is produced by a field of solar collectors, the reduction in this demand is expected to cause a similar reduction in the area of the collector field and thus in its corresponding capital cost. On the other hand, the increase in the number of effects results also in an increase of the capital cost of the evaporator due to the increased structural complexity of the evaporator but this increase in capital cost is usually small compared to the benefits of larger number of effects. Figure 32 shows the influence of the number of effects and cost of fuel (expressed in $/barrel) on the resulting cost of water for a solar MED plant having a capacity of 130 m3/day. The evaporator is assumed to have a maximum brine temperature, Tb = 90oC and the collector cost is assumed to be ccol = 300 $/m2. It can be seen that increasing the cost of fuel to the diesel generator results in an increase in the water cost due to the increase of the cost of electricity produced by the diesel generator. Figure 33 demonstrates how the plant capacity and fuel cost affect the cost of water. As expected, higher plant capacity results in a lower water cost and higher fuel cost results in a higher water cost. Figure 34 shows the effect of the cost of collector on the resulting water cost for solar MED plant capacity ranging from 100 m3/day to 1000 m3/day. It can be seen that the collector cost has a vital contribution to the cost of water. For a plant capacity of 1000 m3/day, the cost
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of water is 2.24 $/m3 for a collector cost of 200 $/m2 and is 3.35 $/m3 for a collector cost of 600 $/m2. The effect of the cost of fuel on the water cost is displayed in Figure 35.
Figure 31. Effect of the number of effects and the collector cost on the resulting water cost – fuel cost, cbarrel = 50 $/barrel, max. brine temp. , Tb = 90oC (solar MED plant capacity = 130 m3/day).
Figure 32. Effect of the number of effects and the fuel cost on the resulting cost of water – collector cost, ccol = 300 $/m2, max. brine temp., Tb = 90oC (solar MED plant capacity = 130 m3/day).
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Figure 33. Cost of water as a function of plant capacity and fuel cost, Neff = 25, Tb = 70oC, ccol =300 $/m2 (solar MED plant).
Figure 34. Cost of water as a function of plant capacity and collector cost, Neff = 25, Tb = 90oC, cbarrel = 50 $/barrel (solar MED plant).
Figure 35. for different conventional MED plants of different capacities. For a plant capacity of 1000 m3/day and a fuel cost of 60 $/barrel (close to the current oil price), the cost of water is 2.68 $/m3
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Figure 36. Cost of water as a function of plant capacity and cost of fuel, Neff = 25, Tb = 70oC (conventional MED plant).
Figure 37 is 3-dimentional plot of the cost of water versus the number of effects and cost of fuel for a conventional MED plant having a capacity of 130 m3/day. A conventional MED plant with this capacity produces water at a cost of 3.92 $/m3 assuming an oil price of 60 $/barrel. As the oil price doubles to 120 $/barrel, the cost of water is expected to reach 4.99 $/m3. The corresponding water cost from a solar MED plant is 4.58 $/m3 at a collector cost of 300 $/m2.
Figure 37. Effect of the number of effects and the cost of fuel on the resulting cost of water – max. brine temp., Tb = 90oC (conventional MED plant capacity = 130 m3/day).
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The difference between the cost of water of a solar MED plant (cw1) and the corresponding cost of a conventional MED plant (cw2) is shown in Figure 38 for a capacity of 130 m3/day and for different collector and fuel costs. It can be seen that for higher fuel costs and lower collector costs the difference (cw1 – cw2) is negative indicating that the cost of water from a solar MED plant is cheaper than that of a conventional MED plant having the same capacity.
Figure 38. Difference in cost of water between solar MED plant, cw1, and conventional MED plant, cw2 , (cw1 - cw2) ,$/m3.
13. CONCLUSION The research operation of the test plant, conducted jointly between ENAA and WED, ended successfully at the end of October 1985, as scheduled, giving many useful results that are summarized below.
1. System Reliability The reliability of the automated continuous operation of the test plant for its first year of operation has been successfully demonstrated. However, the plant has suffered from pump trouble, etc. associated with plants of the same type in the early stage of development. The plant’s heat collecting subsystem, the heat accumulator subsystem and evaporator subsystem have also proved to have no particular problems:
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•
Corrosion of the heat collectors and heat accumulators was prevented by the use of corrosion prevention chemical additive; Scaling in the evaporator was prevented by using a scale inhibitor which maintained a good evaporator performance throughout the first year without any need for an acid cleaning; Experimental results showed that there was no problem with the vacuum in the evacuated glass tube collectors, despite early worries that the vacuum might deteriorate if the collectors were left at no load (drained condition) without operation under conditions of high solar radiation typical of the Middle East. The collector joints were found to pose no problems in the first year of operation.
The above results have led to estimating the life expectancy of the solar collectors, accumulators and evaporator at 20 years. The reliability of the plant has been further demonstrated during its succeeding years of operation.
2. Response to Varying Weather Condition Weather conditions, including solar radiation, ambient temperature, seawater temperature and humidity varies widely according to the time of day and season. For example, the solar radiation on a horizontal surface varied from 2,150 kcal/m2 day to 7,080 kcal/m2 and the daily average temperature varied between 16.7oC and 38.0oC for 1985 in Abu Dhabi. Despite such wide fluctuations, the results of the simulation program call for the evaporator of the test plant to be shutdown only 13 times a year for lack of thermal charge in the accumulator. Based on the simulation results also, the plant’s annual operating time is 8,546 hours which translate into an availability of 97.6%. Thus, the test plant has a very good adaptability to weather conditions.
3. Establishment of a Method for Cleaning of Solar Collectors One of the early worries about the test plant was whether there was an easy and economical method for removing fouling material (dust) due to sandstorms and polluted air. In an effort to solve this problem, an investigation was made of solar installations in the Middle East, and based on the results of this investigation, a preliminary test was made for collector cleaning. As a result, high-pressure water spray gun was adopted as the method of cleaning the solar collectors. This method worked very well. A cleaning once a month reduced the heat loss from the solar collectors from the planned 10% to 5.2%. The annual amount of water used for this purpose was about 0.2% of the total water production. The applicability of this cleaning method to practical plants was therefore demonstrated.
4. Comparison of the Test Plant Results with that of the Basic Design A. Improved Effective Use of Solar Radiation It was difficult to make an accurate comparison of the effective use of solar radiation between the test plant and the basic design because the weather conditions were different.
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Nevertheless, the table below shows that the ratio of solar radiation used for water production to the total solar radiation obtained using the simulation program (47.5%) increased markedly over the value that was predicted by the basic design (36.0%). Table 22. Plant energy balance Energy quantity Total solar radiation on tilted surface Heat loss due to fouling Heat loss from solar collectors Quantity of Heat loss from collector piping collected heat Heat loss from heat accumulators Heat loss from evaporator Heat quantity used for desalination
Basic design 100% 10% 42.7% 5.3% 2.4% 2.6% 36.0%
Simulation 100% 5.2% 36.3% 6.9% 3.8% 0.3% 47.5%
The reasons for this marked increase are: •
• • •
The heat loss due to dust deposition was reduced by almost half, although the heat loss from the solar collectors was actually larger than was planned in the basic design. The quantity of collected heat was larger than was planned in the basic design because it was possible to collect heat at lower temperature. The number of evaporator starts and stops was considerably reduced over the planned number, which in turn reduced the heat loss from the evaporator. Improvements made on the test plant: Motor-operated valves, check valves, etc. were installed at the inlet and outlet of the solar collectors to make provision for power failure during the day. If a power failure occurs, this installation automatically drains out the solar collector water, preventing water hammer due to overheated collector water.
For the test plant, there was no choice but to reduce the collector absorber area when dealing with peak radiation intensity during summer time. If all the collectors installed are to be fully used, however, it is suggested that a three-way proportional control valve is to be added between the evaporator and the heat accumulators and to mix some of the return heating water from the evaporator with the hot water from the accumulator to prevent the evaporator from overloading.
B. Development of Computer Simulation Program A simulation program was prepared based on the results of the research operation of the test plant. It is a substantially improved version of the simulation program over that used in the basic design. The results of running this new program showed water productions of 102% and 97.4% of the test plant’s actual performance for January and June 1985, respectively, and there was good agreement. The simulation program is used to calculate the water production for data input into it, and involves the weather conditions at the plant concerned, such as solar radiation, ambient temperature and seawater temperature; and the specifications and capacities of the major individual plant components – capacity (100 to 2,000 m3/day), maximum brine temperature
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(60 to 80oC), number of effects (13 to 32) for the evaporator, for example; and the operating conditions of the plant (eg. Flow rate and temperature of the heating water). If this simulation calculation is repeated for various sets of data, the optimum combination for the geographical area concerned, including the specifications and capacities of solar collectors, heat accumulator and evaporator, can be determined. Other data can also be obtained that may be useful in the selection of pump capacities, piping lengths, angles of absorber plates of solar collectors, etc. Therefore, the simulation program can be used to facilitate precise conceptual design of solar plants of similar design.
C. Water Production Costs • The collector cost has a vital contribution to the cost of water. For a plant capacity of 1000 m3/day, the cost of water is 2.24 $/m3 for a collector cost of 200 $/m2 and is 3.35 $/m3 for a collector cost of 600 $/m2. • For a plant capacity of 130 m3/day which is identical to that of the test plant, the cost of water is quite sensitive to the number of effects and to a lesser degree on the cost of collector with the cost of water varying between 8 $/m3 and 4 $/m3. • The difference between the cost of water from a solar MED plant and the corresponding cost from a conventional MED plant can be in favor for high fuel cost and low collector cost situation indicating that the cost of water from a solar MED plant can be cheaper than that of a conventional MED plant under these conditions.
14. NOMENCLATURE Ac BPE Cb cbarrel ccol Cdg Cev Cst Ctot cf cw1 cw2 di Fo gf gom H h hN I I0 Ib
collector absorber area (m2) boiling point elevation, oC capital cost of steam generator, $ cost of 1 barrel of oil, $ specific collector cost, $/m2 capital cost of diesel generator, $ capital cost of evaporator, $ capital cost of heat storage tank, $ total capital cost of plant, $ cost of 1 liter of fuel, $ cost of water from a solar MED plant cost of water from a conventional MED plant insulation thickness of pipe i fuel cost in the first year of plant operation, $ fuel cost annual escalation rate annual escalation rate for OandM expenses height of collector header box (m) solar altitude (rad) solar altitude measured with respect to collector plane (rad) solar radiation on horizontal surface (kcal/h m2) solar radiation at the outer limit of the atmosphere (kcal/h m2) beam component of solar radiation (kcal/h m2)
Multiple Effect Distillation of Seawater Water Using Solar Energy … Id It k L l li m md mst ms N OMo P Pev Pvac Pc Phw Pb P1 P2 PF PW(Fo) PW(OMo) Qa Qc Qev Qph ri s1 s2 s3 T Tb Tbmax TLC U Va x
diffuse component of solar radiation (kcal/h m2) solar radiation on tilted surface (kcal/h m2) interest rate pitch of absorber plate (m), also latent heat of vaporization (kcal/kg) width of absorber plate (m) length of pipe i, m mass flow rate (kg /s) product flow rate ((kg/ s) heat storage capacity, m3 steam flow rate, ton/hr No. of effects; also lifetime in years OandM cost in the first year of plant operation, $ pump power (kW), atmospheric transmittance pumping power of MED evaporator, kW pumping power of vacuum pump, kW power of heat collecting pump, kW power of heating water pump, kW power of steam generator pump, kW total power of solar MED plant, kW total power of conventional MED plant, kW plant factor present worth of fuel cost, $ present worth of OandM cost, $ rate of heat supplied to accumulator, kcal/ h rate of heat collected by solar field and evaporator condenser, kcal/ h rate of heat supplied to evaporator, kcal/ h rate of heat transfer in preheaters, kcal/ h radius of pipe i, m shadow length by neighboring absorber plate, m shadow length of neighboring glass tube, m shadow length of collector header box, m temperature, oC brine temperature, oC maximum brine temperature, oC total life cycle cost, $ overall heat transfer coefficient, kcal/ h m2 oC wind speed, m/s collector parameter, oC h m2/kcal
Greek Symbols λ θ γ α
heat conductivity of insulation material (kcal/h moC) incidence angle on collector plane (rad) solar azimuth angle (rad) support angle of collector (rad)
155
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Ali M. El-Nashar τ α0 ηc αc γN
transmittance of glass tube heat trasnsfer coefficient at air side, (kcal/h m2oC) collector efficiency tilt angle of absorber plate with respect to collector (rad) solar azimuth angle measured from tilted collector plane (rad)
Subscripts a av c c1 c2 F in m out w
ambient average collector or condenser inlet to condenser outlet from condenser block F inlet measured outlet water
ACKNOWLEDGMENT The author would like to thank Dr. Darwish Al Qubaisi for his continued support and encouragement throughout this project.
REFERENCES [1] [2]
[3] [4] [5] [6]
El-Nashar, A.M., “Economics of small solar-assisted multiple-effect stack distillation plants”, Desalination. 130 (2000) 201-215 El-Nashar, A.M., “Predicting part-load performance of small MED evaporators- a simple simulation program and its experimental verification”, Desalination. 130 (2000) 217-234 El-Nashar, A.M., “The economic feasibility of small solar MED seawater desalination plants for remote arid areas”, Desalination. 134 (2001) 173-186 El-Nashar, A.M., “Validating the performance simulation program “SOLDES” using data from an operating solar desalination plant”, Desalination. 130 (2000) 235-253 ENAA and WED, Research and development cooperation on a solar energy desalination plant, Final Report, 1986. Fosselard, G. and Wangnick, K. “Comprehensive study on capital and operational expenditures for different types of seawater desalting plants (RO, MVC, ME, METVC, MSF) rated between 200 m3/day and 3000 m3/day”, Proceeding Fourth World Congress on Desalination and Water Reuse, Vol. IV, Kuwait 4-8, 1989
Multiple Effect Distillation of Seawater Water Using Solar Energy … [7]
[8]
[9]
[10]
[11]
[12]
[13] [14]
[15]
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Garcia-Rodriguez and Gomez-Camacho, C., “Design parameter selection for a distillation system coupled to a solar parabolic trough collector”, Desalination. 122 (1999) 195-204 Garcia-Rodriguez, L. and Gomez-Camacho, C., “Conditions for economical benefirs of the use of solar energy in multi-stage flash distillation”, Desalination. 125 (1999) 133-138 Garcia-Rodriguez, L. and Gomez-Camacho, C., “Thermo-economic analysis of a solar multi-effect plant installed at the Platforma Solare de Almeria (Spain)”, Desalination. 122 (1999) 205-214 Goosen, M. F.A.; Sablani, S.S.; Shayya, W.H.; Paton, C. and Al-Hinai, H., “Thermodynamic and economic considerations in solar desalination”, Desalination. 129 (2000) 63-89 Milow, B. and Zarza, E., “Advanced MED solar desalination plants. Configurations, costs, future – seven years of experience at the Platforma Solare de Almeria (Spain)”, Desalination. 108 (1996) 51-58 Sayigh, A. et al., “Dust effect on solar flat surface devices in Kuwait”, Proceedings of the international symposium on Thermal Applications of Solar Energy, April 7-10 (1985), 95. Tsilingiris, P.T., “The analysis and performance of large-scale stand-alone solar desalination plants”, Desalination. 100 (1995) 249-255 Voivontas, D.; Misirlis, K.; Manoli, E.; Arampatzis, G. and Assimacopoulos, D., “ A tool for the design of desalination plants powered by renewable energies”, Desalination. 133 (2001) 175-198 Voivontas, D.; Yannopoulos, K.; Rados, K.; Zervos, A. and Assimacopoulos, D., “Market potential of renewable energy powered desalination systems in Greece”, Desalination. 121 (1999) 159-172
APPENDIX: PHYSICAL PROPERTIES OF SEAWATER Density (kg/m3)
ρ (T , C ) = 1002.28 − 0.18302 × T + 703.13 × C − 0.32954 × C × T Boiling point elevation (oC)
BPE (T , C ) = −0.05 +
(0.9576 + 0.8189 × 10 −2 × T + 0.1647 × 10 −4 × T 2 ) × C 0.114
Latent heat of vaporization (kcal/kg)
L(T ) = 0.5976 × 10 3 − 0.565 × T + 0.7828 × 10 −4 × T 2 − 0.2859 × 10 −5 × T 3 Specific heat at constant pressure (kcal/kgoC)
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C p = 1.0022 − 0.6405 × 10 −4 × T − 1.14185 × C + 6.0118 × 10 −3 × T × C + 2.109 × 10 −6 × T 2 + 2.1753 × C 2 + 1.5937 × 10 − 2 × T × C 2 − 0.135 × 10 − 2 × T × C The temperature T is in oC and the salt concentration C is in kg /kg water.
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 159-200
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 4
SOLID STATE ORGANIC PHOTOELECTROCHEMICAL SOLAR ENERGY CONVERSION BASED ON CONJUGATED SUBSTITUTED POLYTHIOPHENES* Teketel Yohannes† Chemistry Department, Addis Ababa University, Addis Ababa, Ethiopia
ABSTRACT The utilization of organic materials for photovoltaic devices has been investigated intensely during the last couple of decades. Earlier studies concentrated on molecules that had high optical absorption in the visible region of the electromagnetic spectrum. Recent discovery of conjugated polymers having semiconductor-like behavior has started to stir excitement because such materials are not only able to function in a similar manner to the inorganic semiconductors but also have important advantages such as: low cost, light weight, ease of fabrication and the possibility of large area coatings. Their use as photoactive electrodes is of increasing interest, as the processing possibilities of conjugated polymer materials have become more developed. Furthermore, the high absorption coefficients of these materials and the possibility of varying the band gap by molecular engineering have opened up new options for solar energy conversion. Among the conjugated conducting polymers, neutral, substituted polythiophenes exhibit interesting properties as semiconducting photoactive materials and are used for conversion of optical energy into electrical energy. Investigation of the photoelectrochemistry of conducting polymers was mainly focused on their use as protective films against photocorrosion and as photoactive electrodes in liquid junction photoelectrochemical cells (PECs). Photocorrosion and side *
A version of this chapter was also published in Leading Edge Research in Solar Energy edited by P. N. Rivers published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research. † Chemistry Department, Addis Ababa University, P. O. Box, 1176, Addis Ababa, Ethiopia E-mail:
[email protected] or
[email protected], Tel: 251-91-1408839
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Teketel Yohannes reactions involving the electrolyte solution and the difficulty of packaging limit the working life of liquid electrolyte PECs. Solid-state PECs with the use of solid polymer electrolytes provide a means to eliminate this problem since they can easily be processed into thin films over large areas and are easier to encapsulate. The solvent-free ion conducting polymer electrolytes eliminated handling, portability, and packaging problems encountered in liquid junction photoelectrochemical cells. Basically, the photoelectrochemical properties occurring in these systems are the same as those occurring in systems based on semiconductor photoelectrodes in contact with liquid electrolytes. In this chapter an overview of the studies made on solid-state photoelectrochemical solar energy conversion devices using standard photoelectrochemical and photoelectrical characterization techniques is presented. The photoelectrochemical cells contain a thin film of semiconducting conjugated substituted polythiophenes as a light-harvesting unit, a redox couple complexed with an ion conducting polymer electrolyte, and a counter electrode.
1. INTRODUCTION An enormous amount of radiant energy is received from the sun. The solar energy falling on the Earth's surface in a fortnight is estimated to be equivalent to the energy contained in the world's supply of fossil fuels [1, 2]. About 23% of the incident solar energy is consumed in the evaporation, convection, and precipitation of water in the hydrological cycle, about 47% goes to heat the atmosphere, the land surface, and the oceans, and about 30% is reflected and scattered back into space. Approximately 0.03% of the solar input is stored as chemical energy by the photosynthetic growth of green plants, yet this process provides all our food and has generated the fossil fuels. Solar energy is one of the most promising renewable energy sources for our future energy needs when the supply of the conventional energy sources, such as coal, petroleum, and natural gas, gets depleted. Energy from the sun is not only available in plentiful supply, but also introduces no direct contamination of the environment. As a result considerable research work has been aimed at harnessing solar energy. The first experiment on conversion of solar energy to electrical energy was performed in 1839 by the French physicist Edmond Becquerel [3], who demonstrated that a photovoltage and a photocurrent are produced when a silver chloride electrode in an electrolyte solution is illuminated. The modern era of photovoltaic solar energy conversion began in 1954 at Bell Laboratories (USA) when Chapin and his co-workers reported a solar energy conversion efficiency of 6% for a single-crystal silicon cell [4]. With improved technology, the silicon cell efficiency under terrestrial sunlight had reached 14% by 1958. The first satellite powered with silicon solar cells was launched in the same year. A large amount of continued research effort has improved the efficiency to 25% at the moment [5, 6]. Although these devices are used for various optoelectronic applications, the high manufacturing cost of the cells has created a stumbling block for large-scale use. An alternative technology that might offer comparable efficiency and reduced cost is photoelectrochemical solar energy conversion. Photoelectrochemical cells (PECs) are based on the junction between a semiconductor photoelectrode and an electrolyte containing a redox couple. The semiconductor is responsible for the absorption of the incident light, while the
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interface between the semiconductor and the electrolyte is the key factor in the subsequent chemical steps that lead to energy conversion. Less expensive polycrystalline or nanocrystalline semiconductors are used in PECs, which have low efficiency when used in photovoltaic devices. PECs combine photosynthetic and photovoltaic aspects in that they can be constructed either to produce and store chemical fuel, or to produce electricity, or both. Such devices based on dye sensitized nanocrystalline semiconductors have demonstrated solar energy conversion efficiencies exceeding 15% [7-10]. These cells are attractive because they (a) are less expensive, (b) can be used to store energy in the form of conventional fuels in addition to converting light to electrical energy, and, (c) can be fabricated with considerable ease since there are no solid-solid junctions unlike the case of photovoltaic devices. In addition, (d) the band-bending characteristics of the semiconductor can be conveniently varied by suitable choice of electrolyte, (e) they do not have problems associated with different thermal expansion of solid-solid junctions, and, (f) no anti-reflection coating is required. The potential application of PECs for storage of chemical fuels appeared for the first time in Japan in 1972 when Fujishima and Honda [11] studied the photoelectrolysis of water to oxygen and hydrogen at illuminated semiconducting titanium dioxide electrodes. They suggested that such a system would be applicable to the problem of using sunlight to photoelectrolyze water, a process that results in the conversion of sunlight to stored chemical energy. The first follow-up work did not appear until 1975 [12-15]. Since 1975 the main research efforts, which have been pursued by an increasing number of researchers, have been to study smaller band gap semiconductors (silicon, gallium arsenide, cadmium sulphide, etc.), which have acceptable solar energy conversion efficiency due to their good match to the solar spectrum. The main challenge is that these materials tend to be unstable when illuminated because of unwanted chemical reactions between the illuminated semiconductor and some components of the electrolyte solvent. On the other hand, the use of large band gap semiconductors is hampered by the fact that these materials utilize only a small portion of the solar spectrum for efficient energy conversion. Attempts to achieve good visible light response with these stable materials suffer principally from low efficiency. While inorganic semiconductor photovoltaic cells have high efficiency and inorganic semiconductor PECs have the advantage of a storable chemical fuel, both suffer from high cost. One possibility for circumventing this problem is to use inexpensive organic molecules. Earlier studies concentrated on molecules that had high optical absorption in the visible region of the electromagnetic spectrum, such as chlorophyll, cyanine, merocyanines, phthalocyanines, porphyrins, and tetracenes [16, 17]. Recent discovery of conjugated polymers having semiconductor-like behavior have started to stir excitement because they are able to function in a similar manner to the inorganic semiconductors but also have important advantages such as: low cost, light weight, ease of fabrication, and the possibility of large area coatings. Studies on the photoelectrochemistry of conducting polymers was mainly focused on their use as protective films to stabilize photocorrosion of small band gap inorganic semiconductors in liquid-junction PECs [18-23] and as photoactive electrodes in liquid junction PECs [24-43]. Their use as photoactive electrodes is of increasing interest, as the processing possibilities of conjugated polymer materials becomes more developed. Furthermore, the high absorption coefficients of these materials and the possibility of varying
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the band gap by molecular engineering have opened up new options for photoelectrochemical solar energy conversion. Although conducting polymers could be used as photoelectrodes in PECs, there are only relatively few reports in the literature, probably due to their low overall conversion efficiencies. Apart from the low conversion efficiency, liquid-junction PECs suffer from problems in handling, portability, and packaging. Such problems might be eliminated by the use of polymer electrolytes, which are solvent-free ion conducting polymers. Polymer electrolytes can easily be processed into thin films over large areas, and with these materials the rectifying contacts to semiconductors, be they inorganic or organic, can easily be made. Basically, the photoelectrochemical processes occurring in these systems are the same as those occurring in systems based on semiconductor photoelectrodes in contact with liquid electrolytes. The chapter is divided into four sections. Section 1 is a general introduction. Section 2 and 3 presents the general properties of electrically conducting conjugated polymers and the ion conducting polymer electrolytes, respectively. Section 4 discusses the fundamental principles of photoelectrochemical solar energy conversion. In section 5 the experimental methods used to characterize and the most important findings of the solid-state photoelectrochemical cells based on substituted polythiophenes will be described. The last section summarizes the chapter.
2. ELECTRONICALLY CONDUCTING POLYMERS 2.1. Introduction Polymers are macromolecules produced by the union of many (102-106) small repeating units called monomers. Many polymers are strong, elastic, plastic, tough, friction-resistant, and insulating. We encounter them in our day-to-day life in a wide range of products from most consumer goods to highly specialized applications. Starting in the late 1970s new materials having high electrical conductivity became available. In 1974 a graduate student in Shirakawa's laboratory at the Tokyo Institute of Technology was trying to make a black powder of polyacetylene following a modified Natta route [44] when he accidentally prepared a shiny, free-standing polyacetylene film [45]. Looking back over his chemical recipe, the student saw that he had mistakenly added 103 times more catalyst than the instructions called for. In 1977 Shirakawa, together with MacDiarmid and Heeger [46, 47], discovered that the conductivity of that insulating polyacetylene, which had a conductivity lower than 10-5 S cm-1, could be increased up to 103 S cm-1 at room temperature by chemical oxidation with iodine or AsF5. Further improvements in polymerization methods produced polymers containing fewer defects in their structure and having conductivity as high as 1.5 x 105 S cm-1 [48]. Another significant breakthrough occurred in 1980 with the discovery that polyparaphenylene could also be doped and have conductivity levels comparable to those of polyacetylene [49]. Thereafter the number of conjugated polymers has been enlarged to include a variety of aromatic and heterocyclic polymers as well as many derivatives of these parent materials. The chemical structures of some common conjugated polymers are shown in
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figure 1. All have an extended conjugated structure (alternating single and double bonds) along the main chain with the exception of polyaniline, which has instead an extra electron pair on the nitrogen atoms that gives it the behavior of a conjugated polymer. The main focus of the early research activity on conducting polymers was on their electrical conductivity. Neutral conjugated polymers are insulators or semiconductors. To make these polymers electrically conducting, one should introduce species, which are electron accepting (oxidizing agents) or electron donating (reducing agents). The oxidation and reduction reactions which induce high conductivity are termed, using the language of semiconductor physics, p-doping and n-doping, respectively. However, the process of doping in conducting polymers is different from that of semiconductors. In semiconductors doping involves replacing some of the atoms with atoms that have either more or less electrons while in conducting polymers the dopant molecules never replace any of the atoms of the polymer; rather they simply act as associates that accept or donate electrons. The doping process of conducting polymers can be represented by the following general scheme: For an oxidation process
Polymer + X
⇄
n+
n¯
+X
(Polymer)
and for a reduction process
Polymer + M
⇄
n¯
n+
(Polymer) + M n¯
n+
where X is the oxidizing agent and M is the reducing agent. X and M are the dopant counter anion and cation, respectively. By appropriately adjusting the doping level, conductivity anywhere between that of the undoped (insulating or semiconducting) and that of the fully doped (metallic) forms of the conjugated polymer may be obtained. The doping process may be achieved either electrochemically via application of a potential or chemically by using an oxidizing or a reducing agent. Oxidizing agents such as I2, Br2, Cl2, AsF5, FeCl3, and NOPF6, and reducing agents like Li, Na, and K, have been used. p-type doping is more common and gives higher conductivity and a better stability. Significant problems were apparent at an early stage: the materials were often unstable in air and were intractable, infusible, insoluble films or powders that, once synthesized, could not be further manipulated into forms with more ordered and controlled structures. A great deal of research has been directed to overcome these problems. Approaches include the use of a nonconducting solution processable precursor polymer that can be transformed by a simple thermal elimination reaction into an insoluble conjugated polymer [50-53]. Another is the substitution of flexible side chains onto the rigid conjugated main polymer chain to confer melt and solution processability [54-58].
164
Teketel Yohannes H N
n
N H
polypyrrole
n poly(p-phenylene)
S
n
n
polythiophene
n poly(p-phenylenevinylene)
polyaniline
n polyfluorene
Figure 1. Chemical structures of some conjugated polymers.
Because they had the important optical and electronic properties of semiconductors and metals, conducting polymers became potential materials for technological applications. Conducting polymers became so popular and they are now the main topic in international conferences and meetings on synthetic metals. Researchers from various disciplines that include chemistry, physics, electrical engineering, and material science are involved in studying them. Several reviews have been published covering many different aspects of these materials [59-66].
2.2. Synthesis of Substituted Polythiophenes In the following section the two main routes, i.e., chemical and electrochemical, for the synthesis of substituted polythiophenes will be presented in brief.
2.2.1.Chemical Synthesis Polythiophene is not melt or solution processable. It is obtained in the form of a powder or film. The delocalized electronic structure of π-conjugated polymers tends to yield relatively stiff chains and strong interchain attractions, which make them insoluble and nonprocessable. Modification of the chemical structure by addition of side groups to the thiophene ring has resulted in polymers with different degrees of stability, conductivity, solubility, and band gap. For instance, substitution onto the thiophene ring an alkyl group at the 3-position renders both solution and melt processable conjugated polymers [54-58]. Water-soluble derivatives of polythiophene have also been prepared by placing carboxylic, sulfonic, or amino acid groups attached to the alkyl chains [67-69]. Furthermore, substitution at the 3- and 4-positions by an electron donating group stabilizes the positive charges generated in the doped polymer and lower the relative band gap [70-72]. When monosubstituted thiophenes are polymerized three different couplings are possible: head-to-tail (HT), head-to-head (HH), or tail-to-tail (TT) (figure 2.). The standard synthesis of all substituted polythiophenes gives some proportion of HT linkages. The dihedral angle between two HT-coupled rings is smaller than between two HH-coupled rings. This difference in the dihedral angle affects the optical properties of the conjugated polymers. Generally, when the dihedral angle between the rings increases, the conjugation decreases and the absorption occurs at a shorter wavelength. Large substituents lead to a large dihedral angle between the rings and short conjugation along the polymer backbone. The co-planarity
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of the rings in the main chain also affects the optical absorption. If all the thiophene rings are co-planar, the conjugation along the main chain is extended and the absorption occurs at a longer wavelength. Among the substituted thiophenes, the highest electron mobility, highest conductivity, and narrowest band gap is found in the perfect HT linked isomers [73]. R
R
R
S
S
S
S
S R
HT
HH
S R
R
TT
Figure 2. Three different coupling modes for monosubstituted thiophenes.
The most commonly used method of preparing 3-substituted monomers of thiophene is the procedure of Tamao and co-workers [74], a nickel-catalyzed Grignard coupling (figure 3 (a)). The polymer is produced by diiodinating the substituted thiophene monomer [75] and Grignard coupling of the 2,5-diiodo-3-alkylthiophenes. The scheme for the polymerization is shown in figure 3 (b). This method gives a polymer with approximately 50-60% HT coupling [76], which is random. Br
R 1. RMgBr 2. Ni(dppp)Cl2, Et2O
S
S
(a) R
R I2 S
HNO3
R 1. Mg, THF
I
S
I
2. Ni(dppp)Cl2
S
n
(b) Figure 3. (a) Monomer synthesis and (b) polymerisation of 3-alkylthiophenes by nickel-catalyzed Grignard coupling. [Ni(dppp)Cl2 = [1,3-bis(diphenylphosphino)propane]nickel(II)chloride and THF = tetrahydrofuran].
Yoshino and his co-workers [77] used another polymerization method, which involved chemical oxidation of the monomers with transition metal halides such as FeCl3, MoCl5, and RuCl3. The most widely used method now is that with FeCl3 (figure 4.). FeCl3 acts as an oxidizing agent and is reduced to FeCl2 during the polymerization reaction. The polymerization gives irregular polymers with approximately 80% HT coupling [78].
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Teketel Yohannes
R
R FeCl3 CHCl3
S
S
n
Figure 4. Polymerization of 3-alkylthiophenes with FeCl3.
Recently, two new polymerization reactions have been developed. The one mostly used is a Grignard type of reaction (figure 5.) [79]. The regularity is high with 93-96% HT coupling. R LDA Br
S
R
R
THF
MgBr2-Et2O Li
S
BrMg
Br
Br
S
Ni(dppp)Cl2 R
S
n
Figure 5. Grignard type polymerization of 3-alkyl-2-bromothiophenes. [LDA = lithium diisopropylamide].
An alternative method of preparing 3-alkylthiophene uses zinc and a special catalyst [1,3with 3-alkyl-2,5bis(diphenylphosphino)ethane]nickel(II)chloride (Ni(dppe)Cl2), dibromothiophene (figure 6.) [80]. The HT content in this polymer is claimed to be 98.5 ± 1.5%. R
R
R
Zn Br
S
Br
THF
BrZn
S
Br
+
Br
S
ZnBr
Ni(dppe)Cl2 R
S
n
Figure 6. Polymerization of 3-alkyl-2,5-dibromothiophenes with Zn.
The stability of doped conducting polymers is important for applications. Unsubstituted, doped polythiophenes are relatively stable [81, 82], but when the thiophene rings are substituted the stability of the doped polymer severely decreases [83, 84]. Conducting polymers that have fewer, more regularly distributed side chains have better stability. The
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167
number of side chains along the polymer backbone can be reduced by polymerizing bithienyls or terthienyls with only one side chain [58]. Use of a phenyl ring between the flexible alkyl side chain and the polymer backbone also increases the stability of the doped polymer [85]. The stability therefore seems dependent on the rigidity of the polymer main chain and the availability of space for the counter ion. Synthesis of one such substituted thiophene is depicted in figure 7. The 3-alkylthiophenes are selectively brominated, using Nbromosuccinimide (NBS) in N, N-dimethylformamide (DMF) [86], and can then be coupled with 2-thiopheneboronic acid according to the method described by Gronowitz [87]. (The 2thiopheneboronic acid is prepared by treating lithiated thiophene with trimethylborate [88].) The polymerization is performed using FeCl3 in chloroform (figure 7.).
R
R NBS DMF
S
Br
S
(a) R R
Pd0(PPh3)4
HO Br
+ S
B
NaHCO3, DMF
S
HO
S S
(b) Figure 7. (a) Selective bromination of 3-alkylthiophene and (b) coupling of two different substituted thiophenes. [Pd0(PPh3)4 = tetrakis(triphenylphosphine)palladium(0)].
2.2.2. Electrochemical Synthesis Electrochemical polymerization has been used to synthesize substituted polythiophenes from their monomers using both cathodic and anodic routes. The anodic route is the most convenient and widely used. The electrochemical polymerization may be carried out with a classical three-electrode electrochemical cell, consisting of a working electrode, a reference electrode, and a counter electrode, in a solution containing the monomer and a supporting electrolyte. The nature of the working electrode is critical for the preparation of these films and depends on the type of polymer to be synthesized and on the electrolytic medium. Since an oxidative or reductive process produces the films, it is important that the electrode does not oxidize or reduce concurrently with the monomer. Working electrodes such as gold, platinum, and transparent indium doped tin-oxide (ITO) coated glass can be used. The ITO-coated glass electrode is particularly suitable for spectroscopic studies. For the synthesis, potentiostatic (fixed polymerization potential), galvanostatic (fixed current), or potentiodynamic (varying potential) methods can be used. A preliminary study is necessary in order to find a solvent in which the monomer is soluble and to determine the
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potential at which the polymerization may be performed. Very often, cyclic voltammetry is a good tool to determine the best polymerization conditions. The polymerization potential should not be too low, since this causes the polymerization process to be very slow and to form soluble oligomers, nor too high in order to avoid a material having lower conductivity due to overoxidation. In general, the polymerization potential must be chosen not too far (± 0.1 V) from the corresponding oxidation peak potential of the monomer. The electrodeposition potential is specific for any given electropolymerization process. As the potential needed for monomer oxidation is always higher than the charging of the existing polymer, both polymerization and doping processes may be driven by a single electrochemical operation which, starting from the monomer, first forms the polymeric chain and then induces its oxidation and deposition on the working electrode. The polymeric film coating the working electrode can be studied afterwards in a monomer free solution. The general mechanism of the electrochemical polymerization reaction is as shown in figure 8. The first step consists of the irreversible electrochemical oxidation of the neutral monomer to form delocalized radical cations. The radical cations are unstable and reactive. Since the electron transfer reaction is much faster than the diffusion of the monomer from the bulk solution, a high concentration of radicals is continuously maintained at the electrode/solution interface. The next step in the polymerization sequence involves the radical cation-radical cation coupling with dimer formation followed by a deprotonation and rearomatization. As the dimer is more easily oxidized than the monomer, under the given experimental conditions it is immediately reoxidized to the cation. Chain growth proceeds between the radical cations of the monomer and those of the continuously forming oligomers. This in turn is followed by another proton elimination and oxidation of the propagated oligomeric unit to a cation. For the polymerization to continue, radical cations must be present in the vicinity of the working electrode and therefore, the electrode potential should be kept at the oxidation potential of the monomer. In the terminology of electrochemical reaction mechanisms, the electrochemical polymerization proceeds through successive electrochemical and chemical steps according to a general E(CE)n scheme, until the oligomer becomes insoluble in the electrolytic medium and precipitates onto the electrode surface. Once deposited as conductive films, the polymers can be repeatedly cycled from the undoped to the doped forms (and vice versa) in an electrochemical cell similar to that used for the electropolymerization reactions in the absence of the monomer. The doping-undoping process involves transport of the counter ions from the electrolyte solution into the polymer matrix (between chains) during charging and out of the polymer matrix during discharging to neutralize the electronic charge on the polymer chain. Although electrochemical synthesis gives rise to cross-linked, insoluble materials that are not dense or of high quality, it is widely used because of the following advantages over chemical synthesis. (a) The polymeric material, directly grafted onto the electrode surface is produced in one step. (b) There is no need for a catalyst; therefore, the electrodeposited polymer is pure. (c) By controlling the amount of charge supplied, the thickness of the polymer film may be controlled from a few Angstroms to many micrometers. (d) By changing the nature of the counter ions in solution, the electrical and physico-chemical properties of the polymer may be changed for a particular purpose. (e) There is the possibility of performing in situ characterization of the growth process or of the polymer by electrochemical and/or spectroscopic techniques.
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Electrochemistry is an excellent tool for conducting polymer synthesis and can also be used to study the polymerization and the doping-undoping processes. Furthermore, electrochemistry can be considered as excellent means to study processes involving the doping-undoping processes that occur in batteries, electrochromic devices, sensors, and electromechanical devices [60, 89, 90]. - eS
S
Monomer oxidation H
S
S
-2H+
.
2
.
S
S
S
H
Radical cation-radical cation coupling -e-
S S
.
S
S
S
n
S n
. S
S
+
S
2H+
S n+1
Chain propagation Figure 8. Mechanism of electropolymerization of thiophenes.
2.3. Electronic Properties Polyacetylene is the most extensively studied conducting polymer. It has served as a model for understanding the electronic and physical properties of conducting polymers. The electronic band structure of polyacetylene developed from the smallest unsaturated hydrocarbon ethene. The carbon atoms in the ethene molecule are sp2 hybridized and are connected to each other and to hydrogen atoms by σ-bonds. The remaining carbon pz orbitals interact with each other to produce two orbitals of π symmetry, one of which is bonding (π) and the other, antibonding (π*). Each of the pz orbitals contributes one electron, and in the ground state, two electrons occupy the bonding π orbital. A discrete optical transition exists between the two molecular orbitals (MOs), the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO).
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As the basic ethene units are coupled together to form a larger molecule, the π-bonding will become more delocalized and more atomic orbitals must be included in the overall MO description. In the simplest conjugated hydrocarbon 1,3-butadiene, the four valence p orbitals will produce four π-type MOs. Two of these orbitals are bonding in character and are occupied by electron pairs, while the other two are antibonding and are empty. Addition of another ethene unit to 1,3-butadiene creates 1,3,5-hexatriene, a molecule with three fully occupied π-bonding orbitals and three empty π-antibonding orbitals. As this process of adding is continued, longer conjugated systems will be created until an infinite one-dimensional polyacetylene chain is formed. This chain will contain an infinite number of bonding and antibonding MOs. In this infinite chain, the orbitals will tend to cluster together into tightly packed groups. Because the fully developed polyacetylene has an extremely large number of MOs, a description of the π-bonding in this molecule can be simplified by considering groups of orbitals together as sets. Even though each of the MOs consists of a large number of orbitals that are packed tightly together into a finite energy interval, for most purposes we can ignore the energy spacing between the individual orbitals. We can therefore consider the orbitals as forming continuous bands of energy levels clustered together. The cluster of fully occupied bonding orbitals (π-band) is referred to as the valence band (VB), and the cluster of vacant antibonding orbitals (π*-band) is called the conduction band (CB) of the polymer, and the difference between the bands is called the band gap or forbidden gap. Partially filled energy bands characterize metallic conductors. On the other hand, semiconductors and insulators are characterized by the presence of completely full VB and completely empty CB separated by an energy gap. Semiconductors have reasonably low band gaps, whereas the gap for insulators is rather large. Conjugated polymers have the electronic profile of insulators or semiconductors. The existence of the alternating single and double bonds allows polyacetylene to have a number of possible structures, as shown in figure 9. As can be seen from this figure, it has two trans and two cis structures. The two trans structures are energetically degenerate (the single and double bonds can be interchanged with no cost in energy) and are thermodynamically stable. On the other hand the two cis structures are not energetically equivalent and therefore have a non-degenerate ground state: the quinoid cis structure is of higher energy than the aromatic cis structure. As a consequence only the latter is thermodynamically stable.
Trans degenerate structures
Aromatic Cis non-degenerate structures Figure 9. Trans- and cis-polyacetylene.
Quinoid
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If all bond lengths along the polyacetylene backbone were equal, with each bond having a partial double bond character, then the polymer would have a half-filled band and behaves as a quasi-one-dimensional metal having good conductive properties. This is not the case, however. Analysis of the physics of one-dimensional metals has led to the conclusion that this type of configuration is unstable (Peierls theorem) [91], and so the one-dimensional system will undergo lattice distortion by alternating short (partial double) and long (partial single) bonds of the linear chain. The Peierls theorem states that a one-dimensional metal will be unstable against a metal-to-semiconductor transition and an energy gap will form due to the occurrence of the lattice distortion so that the material becomes either a semiconductor or an insulator [91]. Elastic energy is used during lattice distortion, which is compensated by a lowering in the electronic energy of the occupied states and the generation of a band gap. Hence in trans-polyacetylene there will be a periodic alternation of the carbon-carbon bond length along the polymer chain resulting in a stable structure of low energy. If the two degenerate structures of trans-polyacetylene are on the same chain, they will be separated by a defect in the bond alternation as shown in figure 10. The carbon atom between the conjugated segments will be sp3-hybridized and contains one unpaired electron although the overall charge remains zero. As a result, a new localized electronic state is created at the middle of the forbidden gap i.e., the unpaired electron resides in a non-bonding orbital. These conformational defects are called solitons and have a spin of 1/2 [92]. The soliton is often depicted as being localized at a certain position on the chain. However, this is not the case as noted from theoretical calculations; the defect is delocalized over 15 carbon atoms [93]. Figure 10. shows schematic band diagrams and the three classes of solitons. The soliton is positively charged with spin zero when the electron is removed and negatively charged with spin zero when electron is added. Furthermore, when charge is removed or added to the polymer chain it will be located in the midgap states.
+ Positive Soliton
Neutral Soliton
CB
CB
CB
VB
VB
VB
Charge = 0 Spin = 1/2
Negative soliton
Charge = +e Spin = 0
Charge = -e Spin = 0
Figure 10. Neutral, positive, and negative solitons and their corresponding energy band diagrams with the allowed interband (dashed arrow) and subgap (normal arrow) transitions. Dark circles indicate electrons.
All other conjugated polymers, including cis-polyacetylene, possess non-degenerate ground states and the formation of single solitons, as a result of inherent defects or doping, is energetically unfavorable. In such polymers, there are two different possible chemical structures, which are non-degenerate and are referred to as aromatic and quinoid (figure 11).
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The energy of the aromatic form is lower than the energy of the quinoid form and the ground state of a non-degenerate conjugated polymer corresponds to the aromatic structure. One therefore cannot utilize the concept of soliton transport since the two regions separated by a topological defect are not energetically degenerate.
S
S S
S S n
Aromatic
S
S S
S S n
Quinoid
Figure 11. The aromatic and quinoid forms of polythiophene.
If an electron is removed, a polaron (singly charged radical cation) will be generated (figure 12) accompanied by a geometrical relaxation (lattice distortion) from the aromatic structural geometry towards the quinoid form. Further removal of an electron from the already oxidized polymer containing the polaron results in the generation of a doubly charged state termed as bipolaron (figure 12). The formation of bipolaron is also supported by calculations which show that the formation of one bipolaron is thermodynamically more stable than that of two separated polarons, despite the coulombic repulsion between the two charges confined in the same site [94]. The increase of energy due to electrostatic interaction between the two charge units is compensated by the fact that the aromatic form surrounds the bipolaron. The polarons and bipolarons are self-localized to minimize the energy of the main chain and are assumed to extend over four or five rings along the chain.
S
S S
S S n
Polaron S
S S
S S
Bipolaron Figure 12. Polaron and bipolaron in polythiophene.
n
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The neutral non-degenerate conjugated polymer has full valence and empty conduction bands separated by a band gap. Generation of a polaron and a bipolaron creates two localized electronic levels which are energetically separated in the energy gap, a bonding polaron or bipolaron state above the valence band edge and an empty antibonding polaron or bipolaron state below the conduction band edge, unlike the single midgap state of soliton. The energy band picture of the polaron and bipolaron states is depicted in figure 13. For polarons the discrete level within the gap is singly charged while for bipolarons it is all empty (charge +2e) or all full (charge -2e). Bipolarons are spinless in contrast to polarons and neutral solitons. For polythiophenes at very high p-doping levels the transport properties become those of a metal [95]. Theoretically, this can be understood by considering that the broadening of the bipolaron states in the gap upon increasing the dopant concentration eventually leads to the merging of the lower and upper bipolaron bands with the valence band and conduction band respectively forming a bipolaronic band, thus approaching the metallic regime [96]. Optical absorption spectroscopy provides experimental evidence for the existence of the electronic states in the conjugated polymers [97]. CB
CB
VB
CB
VB Charge = +e Spin = 1/2
VB Charge = -e Spin = 1/2
Polarons
CB
VB Charge = +2e Spin = 0
Charge = -2e Spin = 0
Bipolarons
Figure 13. Energy band diagrams for polarons and bipolarons and possible allowed interband (dashed arrow) and subgap (normal arrow) transitions. Dark circles indicate electrons.
3. IONICALLY CONDUCTING POLYMERS 3.1. Introduction Electrolytes are materials that have high ionic but negligible electronic conductivity. Most electrolytes are liquids, either a molten salt or a salt dissolved in a liquid solvent. There are a number of advantages to be expected if the electrolyte could instead be a solid. The solids so far investigated have primarily been inorganic materials, most commonly β-alumina and silver salts. Recent discoveries in ion conducting polymer electrolytes have broadened the advantages of the solid electrolytes. Polymer electrolytes are complexes of metal salts with high molecular weight polymers containing electron donor atoms or groups of atoms that co-ordinate with the metal ion in the salt. To be successful as a host, a polymer should posses (a) electron donor atoms or groups of atoms (such as -O- ether, -S- sulphide, -N- amine, -P- phosphine, C=O carbonyl, and C≡N cyano) that form co-ordinate bonds with the cations, (b) low barriers to bond rotation for atoms in the main chain so that high flexibility and hence the segmental motion of the
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polymer chain can take place readily, and (c) a suitable distance between co-ordinating centres which ensures adequate jumping distance for charge carriers. Wright first reported this type of polymer in 1973 [98], and Armand proposed the potential of these materials for the development of electrochemical devices in 1978 [99]. Since then, a rapid growth in research and development appears to be devoted to fundamental understanding of the ionic conduction and to their technological applications. The flexibility, processability, ease of handling, and relatively low impact on the environment that polymers inherently possess make these materials suitable for use as solid electrolytes in batteries, electrochromic devices, photoelectrochemical cells, fuel cells, sensors, and media for electrochemical reactions in solid state voltammetry. The rapid progress in this field has led to publication of a number of reviews [100-110]. Most of the early work on polymer electrolytes concentrated on the simple linear homopolymer poly(ethylene oxide), PEO, as the host for a number of salt species. PEO is readily available and is a useful solvent for a wide range of salts while exhibiting acceptable chemical and electrochemical stability. Pure PEO is a semicrystalline polymer consisting of CH2CH2O repeating units; it possesses both an amorphous and a crystalline phase at room temperature. The ionic conductivity was initially thought to occur in the regular crystalline lattice [111]; however, it is now known that such phases are electrical insulators and significant ionic transport occurs only within the amorphous phase [102, 112]. The crystalline nature of PEO is a great hindrance to the ionic transport, and at room temperature the ionic conductivity is only in the order of 10-6 S cm-1 [113]. Although it exhibits excellent ion conductivity at temperatures greater than 60oC [106], the mechanical properties of the polymer at such high temperatures are significantly poorer. This loss of mechanical stability is largely the result of melting of the crystalline phases, giving the material too small a resistance to shear stress for practical applications. The linear homopolymers poly(methylene oxide) and poly(trimethylene oxide) do not act as polymer hosts [111] despite their similarity to PEO. On the other hand, low molecular weight poly(tetramethylene glycol) dissolves salts, but the resulting electrolytes are very poor ion conductors [114, 115]. These results imply that the repeating unit in PEO provides just the right spacing between co-ordinating ether oxygens for solvation of the cations. Similarly, the homopolymer poly(propylene oxide) (PPO), having a repeat unit CH2CH(CH3)O, is less effective in dissolving salts than PEO as a result of the steric hindrance of the methyl groups [104] and has lower conductivity [116]. Linear homopolymers are prone to crystallization and formation of crystalline phases with salts, both of which reduce the conductivity of the system. As the possibility of using polymer electrolytes as components in practical devices became clear, demands were made for materials with better mechanical stability and higher ionic conductivity. A wide variety of polymer structures have been designed and produced in an attempt to optimize these properties by chemical modification of the polymer structures based on formation of linear copolymers (random or block), branched (comb-shaped) polymers, or cross-linked network polymers. Examples of some polymer host structures are given in table 1. Random copolymers with fully amorphous morphology are obtained by interspersing ethylene oxide with methylene oxide units [117-121]. The methylene oxide units break up the regular helical pattern of PEO, and in doing so suppresses crystallization. Both the host polymers and the electrolytes derived from them are amorphous; sometimes they are referred to as amorphous PEO (aPEO). Electrolytes based on aPEO generally have conductivities
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around 10-4 S cm-1 [122, 123] at ambient temperature. Similarly, dimethyl siloxy units have been introduced between medium length PEO units to produce an amorphous polymer, dimethyl siloxy linked PEO [124]. Comb-branched polymers, with short-chain polyethers attached to a polyphosphazene [125-127] or polysiloxane backbone [128-129] have also been found to be excellent hosts with high conductivity (see examples in table 1). Unfortunately the mechanical strength of these materials is poor and it is necessary to develop more complex structures in order to optimize both mechanical and electrical properties. Polymer materials, which are mechanically stable and have reduced crystallinity have been produced by the formation of cross-linked network structures. Cross-linking can be introduced in a polymer or polymer-salt complex chemically or by exposure to intense gamma radiation. Many polymer electrolytes have been developed from network polymers [130-133], and example is given in table 1. Table 1. Chemical structures of some polymer hosts Linear Polymers Poly (ethylene oxide) (PEO)
CH2CH2O
Poly (propylene oxide) (PPO)
CH2CH(CH3)O n
Oxymethylene-linked poly (oxyethylene)
(CH2CH2O)m
n
CH2O
n
CH3
Poly(dimethyl siloxane-co-ethylene oxide) (DMS-n EO)
SiO (CH2CH2O)m CH3
n
Comb Polymers Poly[bis (methoxyethoxyethoxy) phosphazene] (MEEP)
N
(CH2CH2O)mCH3
O P
n (CH2CH2O)mCH3
O
CH3 Poly{[ω-methoxyoligo(oxyethylene)ethoxy]methyl siloxane} (PMMS-m)
SiO O
n (CH2CH2O)mCH3
CH3 Poly{[ω-methoxyoligo(oxyethylene)propyl]methyl siloxane} (PAGS-m)
SiO
n (CH2)3
O
Networks Cross-linked Siloxane
CH3
CH3 PEO
(CH2)3
Si
O
(CH2)3
Si CH3
(CH2)3
PEO
(CH2)3
PEO
O
O PEO
Si
O
Si CH3
(CH2CH2O)mCH3
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A wide variety of salts based on alkali, alkaline earth, transition metals, and lanthanides can be complexed with the polymers. The conductivity of multivalent cation salts in polymer electrolytes are generally lower than those based on monovalent salts. This might be due to the greater strength of the ion-ion interactions in the former, which play a significant role in lowering the conductivity. In general, the salts that most readily complex with the polymer host contain large, singly charged anions that have low lattice energies. The most common anions used are ClO4-, CF3SO3-, (CF3SO2)2N-, (CF3SO2)3C-, BPh4-, AsF6-, PF6-, and SCN-. Salts containing monatomic anions are also soluble, provided they are large and polarizable. Hence, iodide and bromide based salts dissolve, but only few chlorides are soluble and fluorides are insoluble.
3.2. Mechanism of Ion Transport The mechanism for ion transport in polymer electrolytes is distinct from the processes occurring in conventional liquid or solid electrolytes. In conventional liquid electrolytes, ions are solvated by low molecular weight polar molecules. The ions move with their solvent sheath intact, and transport is related to the macroscopic viscosity of the electrolyte. On the other hand, solvation does not arise in inorganic solid electrolytes. The ions can be visualized as hopping between fixed sites, the positions of which do not change significantly with time. During early investigations, cations were thought to move by hopping through a rigid polymer framework along channels within the polymer helices [111]. Such models were introduced for several reasons, partly because the earlier materials (such as PEO) were in fact partially crystalline. However, various experimental techniques have shown the key role of a dynamic polymer environment for ion transport. In polymer electrolytes the solvent molecules, which are part of the polymer chain surround each cations, which are also covalently linked to each other. Transport in polymer electrolytes is considered to take place by a combination of ion motion coupled to the local motion of polymer segments. The segmental motions are thought to promote ion motion by making and breaking the co-ordination sphere of the solvated ion and by providing space into which the ion may diffuse under the influence of the electrical field. In other words, the motion of ions appears to occur by a liquid-like mechanism in which the movement through the polymer matrix is assisted by the segmental motion of the polymer backbone. The liquidlike behavior of the polymer electrolytes dominate the transport process, although an ionhopping mechanism, characteristic of solids, may also contribute to ion transport. Polymer electrolytes could be considered to have macroscopic mechanical properties similar to those of conventional solids owing to chain entanglement and cross-linking of various types, but at a microscopic level they have properties similar to those of liquids. This combination of solid-like and liquid-like properties is what makes them so fascinating scientifically and technologically. A simplified schematic representation of cation movements in polymer electrolytes is given in figure 14. An individual cation is linked to several heteroatoms at any instant of time, old co-ordination links breaking and new links being formed as the ion moves along the polymer chains in its progress through a polymer electrolyte material. The heteroatoms to which the cations are co-ordinated may well belong to more than one polymer chain. Such chains are therefore temporarily linked together by their common bonding to an individual
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cation. Ion transport is therefore a dissociative process in which cations hop between ion coordinating sites on different polymer molecules or different parts of the same molecule. In contrast with the situation in conventional crystalline or vitreous solid electrolytes, these sites are not fixed in time or space but are created or destroyed on a continuous basis as a result of a segmental motion of the polymer chains [134]. Unlike classical solid electrolytes, both the anions and the cations are mobile in polymer electrolytes. A great deal of evidence indicates that anions are far more mobile than cations in these systems. The strong cation bonding to the polymer chain liberates anions from cation association and thus results in higher anion mobility and conductivity. Cation mobility depends on the strength of the cation-polymer interactions; if these are strong, cation transport is suppressed.
O
O M
O
M
+
O
O
O
O
O
O
O
+
O
O O
O
Figure 14. Schematic representation of a cation (M+) motion in a polymer.
4. PHOTOELECTROCHEMICAL SOLAR ENERGY CONVERSION 4.1. Introduction Photoelectrochemical solar energy conversion is based on the junction between a semiconductor and an electrolyte. A typical photoelectrochemical cell (PEC) is shown in figure 15. It consists of a semiconductor electrode, a counter electrode, and an electrolyte containing a redox couple. The PECs that convert light into electricity are termed "electrochemical photovoltaic" or "regenerative cells" and those that generate chemical fuels are "photoelectrosynthetic" or "non-regenerative cells". In regenerative PECs only one redox couple predominates in the electrolyte, so the electrochemical reaction at the semiconductor is exactly reversed at the counter electrode. Since no net chemical change occurs in the electrolyte, the light-induced current will result in electrical power in the circuit that can be used to drive a load. In non-regenerative PECs the electrolyte should contain two different redox reactions that proceed in opposite directions at both electrodes. The respective oxidation and reduction reactions occurring at the anode and cathode are different, leading to a net chemical change. Hence, the incident optical energy is converted into chemical energy by the light-induced current flow.
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Figure 15. Photoelectrochemical cell.
The semiconductors that most efficiently convert solar energy to electrical energy are those with small band gaps because they capture a large fraction of the incident energy. However, they also exhibit decomposition or passivation processes which compete with the desired energy conversion reactions [138-140]. This is a serious problem for liquid-junction PECs. Therefore, for small band gap n-type semiconductors to be used for the sustained conversion of light, the photoanodic decomposition of the electrode must be suppressed. Various strategies have been pursued to chemically control the properties of semiconductor/liquid junctions. These include (a) surface modifications by electrodeposition of an electrically conducting polymer films [18, 141-150], (b) use of redox reagents that can compete kinetically with photocorrosion and photodecomposition processes [151-154], (c) application of solvent-free ion conducting polymers as electrolytes [155-165], and (d) use of non-aqueous electrolyte solutions [166-169]. On the other hand, large band gap semiconductors are stable under illumination. However, they utilize only a small portion of the solar spectrum. Good visible light response was achieved by coating a dye onto the semiconductor [170-177]. By doing so, the location of the light absorption could be transferred to the dye, and a much broader range of the solar spectrum could be used while retaining the chemical stability of the semiconductor. PEC having photoelectrochemical parameters competitive with commercial solid-state photovoltaic devices were attained with semiconductor films consisting of nanometer-sized titanium dioxide particles sensitized with a dye [173]. In the following section, an overview of the fundamental principles of photoelectrochemical solar energy conversion based on inorganic semiconductors will be presented. Knowledge of these provides a starting point for understanding the behavior of conjugated polymer based solid-state PECs. Several detailed reviews covering the science and applications of inorganic semiconductor/liquid electrolyte junction PECs are available [178184].
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4.2. The Semiconductor/Electrolyte Interface Before examining the properties of the semiconductor/electrolyte interface, it is necessary to make a connection between the conventional way of representing the energy in a semiconductor and the electrochemical potential in an electrolyte. For semiconductors, the electrochemical potential of electrons is given by the Fermi level. Changes in the electrode potential corresponds to changes in the position of the Fermi level with respect to a reference energy, which in solids is the energy of an electron in a vacuum. For electrolytes containing a redox couple, the electrochemical potential (Eredox) of an electron is determined by the redox potential. For a reversible redox system (ox + ne- → red), this is given by the Nernst Equation [185] Eredox = Eoredox + RT/nF ln(aox/ared)
(1)
in which Eoredox is the standard electrochemical potential of the redox couple, aox and ared are the activities of the oxidized and reduced species of the redox system, and n is the number of electrons that are exchanged during the reaction. Usually, concentration instead of activity is employed given by a = f c, where f is the activity coefficient. The electrochemical potential of a redox system is given with respect to a reference, usually the normal hydrogen electrode (NHE). To treat the process occurring in PECs quantitatively, the Fermi level of the semiconductor and that of the electrolyte must be placed on a common energy scale. Using an absolute energy scale, the energy of a redox couple (EF, redox) is given by EF, redox = Eref - eEredox
(2)
in which Eredox is the redox potential versus NHE and Eref is the energy of the reference electrode versus the vacuum level. The usual value of Eref taken for the NHE is -4.5 eV, although measurements range from -4.5 to -4.7 eV [186-189]. Equation 2 can then be rewritten as EF, redox = -4.5 eV - eEredox
(3)
with respect to the vacuum level. The relationship between the energy in a semiconductor and the electrochemical potential in an electrolyte, using the solid-state scale and that of the electrochemical scale of a redox couple, are shown in figure 16. Most of the PECs are quite analogous to Schottky barrier solar cells, with the metal layer being replaced by an electrolyte containing a redox couple. When an n-type semiconductor is brought into contact with an electrolyte containing a redox species, rapid exchange of electrons between the redox species and the electrode occurs because of the difference in electrochemical potentials. If the initial Fermi level (or electrochemical potential) in a semiconductor is above the initial Fermi level in the electrolyte, then equilibration of the two Fermi levels occurs by transfer of electrons from the semiconductor to the electrolyte. The charge transfer process stops when the electrochemical potentials of both phases are equal, that is, when equilibrium has been reached. This produces a positive space charge layer in the semiconductor (also called a depletion layer since the region is depleted of majority charge
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carriers) and a negative charge in the electrolyte. As a result, the conduction and valence band edges are bent upward such that a potential barrier is established against further electron transfer into the electrolyte (figure 17). Like the situation in the Schottky barrier, the magnitude of the potential barrier is determined by the bulk properties of the semiconductor, the redox levels in the electrolyte, and by the interface properties of the junction.
Figure 16. Diagram showing the relationship between the energy in a semiconductor and the electrochemical potential in an electrolyte. EF is the energy Fermi level, EC the conduction band edge, EV the valence band edge, and Eg the energy band gap.
The inverse but analogous situation occurs with p-type semiconductors having an initial Fermi level below that of the electrolyte. A negative space charge or depletion layer is formed in the semiconductor, with the valence and conduction bands bending downward to produce a potential barrier against further hole transfer into the electrolyte. A charged layer, known as the Helmholtz layer, also exists in the electrolyte adjacent to the interface with the solid electrode. This layer consists of charged ions from the electrolyte adsorbed onto the solid electrode surface. These ions are of opposite sign to the charge induced on the solid electrode. The width of the Helmholtz layer is generally on the order of a few Angstroms. The potential drop across the Helmholtz layer depends upon the specific ionic equilibrium at the surface. A very important consequence of the presence of the Helmholtz layer is that it markedly affects the band bending that develops in the semiconductor when it equilibrates with the electrolyte. Without the Helmholtz layer, the band bending would simply be expected to be equal to the difference in initial Fermi levels between the two phases (i.e., the difference between their respective work functions). Because of the high charge density and small width of the Helmholtz layer, the potential drop across the Helmholtz layer does not vary with applied electrode potential or charge transfer across the semiconductor/electrolyte interface. Instead, all of any externally applied voltage appears across the depletion layer in the semiconductor. Consequently, at a given electrolyte composition the band edges of the semiconductor at the surface are fixed with respect to the redox potential of the electrolyte, and independent of an applied voltage across the semiconductor/electrolyte interface.
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Figure 17. Energy level diagram for the junction between an n-type semiconductor and an electrolyte in the dark. (a) Before contact. (b) After contact and equilibrium condition. φSC is the work function and χ the electron affinity.
4.3. Photoinduced Charge Transfer at the Interface To convert solar energy into electrical and/or chemical energy, current must flow across the semiconductor/electrolyte junction. When an n-type semiconductor/electrolyte junction is illuminated with light, photons having energies greater than the semiconductor band gap are absorbed. In the dark, no current flows in the cell. But when it is illuminated, electrons are freed in the valence band and move into the conduction band. The free charges can then be separated under the influence of the electric field present in the space charge region. The electric field at the space charge does not require a constant energy input from an external source; rather, it occurs spontaneously whenever two phases with different electrochemical potentials are brought into contact. Electron-hole pairs produced by absorption of photons beyond the depletion layer will separate if the minority carriers can diffuse to the depletion layer before recombining with majority carriers. If they do not disappear by recombination, either by direct coulombic interaction or by collision with other carriers in their path through the space charge layer, the minority carriers in the semiconductor are swept to the surface where they are subsequently injected into the electrolyte to drive a redox reaction. On the other hand, the majority carriers are swept towards the semiconductor bulk, where they subsequently leave the semiconductor via an ohmic contact and are then ejected at the counter electrode to drive a redox reaction opposite to that occurring at the semiconductor electrode. Since the electrons and holes travel in opposite directions, a continuous current will flow as long as the cell is illuminated and connected to an external load. The type of the redox species used is governed by the type of the semiconductor and the position of the energy bands. For n-type semiconductors, minority holes are injected to produce an oxidation reaction, while for p-type semiconductors, minority electrons are injected to produce a reduction reaction.
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Oxidations for n-type semiconductors will occur from holes in the valence band if the solution species Fermi level lies above the surface valence band level and reductions for ptype semiconductors will occur from electrons in the conduction band if the solution species Fermi level lies below the surface conduction band level. The photogeneration causes the Fermi level in the semiconductor to return towards its original position, before the semiconductor/electrolyte junction was established (see figure 18). Under open circuit conditions between an illuminated semiconductor electrode and a metal counter electrode, a photovoltage is produced. The photovoltage produced between the electrodes is equal to the difference between the Fermi level in the semiconductor and the redox potential of the electrolyte. Under closed circuit conditions, the Fermi level in the system is equalized and no photovoltages exist between the two electrodes.
Figure 18. Energy level diagram of a junction between a semiconductor and an electrolyte under illumination.
5. SOLID STATE PHOTOELECTROCHEMICAL SOLAR ENERGY CONVERSION BASED ON SUBSTITUTED POLYTHIOPHENES 5.1. Introduction As discussed in Section 2, conjugated polymers exhibit a range of interesting properties as semiconducting materials and have a band gap between 1 eV and 4 eV. In certain respects, their electrical properties are similar to those of inorganic semiconductors, which allow them to be used as photoelectrodes for solar energy conversion. They have advantages over conventional inorganic semiconductors such as low cost, lightweight, ease of fabrication, processability, and the possibilities of large area coating, and material design through molecular engineering. Most of the earlier studies on solar energy conversion using conjugated polymers focused on Schottky junction photovoltaic devices, in which the polymers were sandwiched between
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low work function metals such as aluminum or indium and high work function metals such as gold or silver. The optical absorption of conjugated polymers in the visible region of the electromagnetic spectrum was high, but the poor charge transport across the materials and the collection at the contacts kept the conversion efficiencies low. Current researches focus mainly on understanding the mechanism of operation in order to find a way to improve the performance of these devices. Understanding the mechanism of junction formation, dependence of photoactivity on molecular structure and device composition, and the sequence of events for carrier photogeneration, i.e., photon absorption, exciton generation, diffusion, recombination, and exciton dissociation, is necessary to increase the efficiency. Photoelectrochemical studies of conjugated polymers have mainly focused on their use as protective films against photocorrosion [18-23] and as photoactive electrodes in liquid junction PECs [24-43]. Liquid junction PECs suffers from handling, portability, and packaging problems. Solid-state PECs that use solvent-free ion conducting polymer electrolytes provide a means for eliminating these problems. As discussed in section 3, the ion conducting polymer electrolytes can easily be processed into thin films over large areas and are easier to encapsulate. The photoelectrochemical properties occurring in these systems are basically the same as those occurring in systems based on liquid junction PECs. Various studies on the use of polymer electrolytes in PECs have appeared in the literature in combination with inorganic semiconductors [155-165]. The properties that a solid polymer electrolyte should possess when used in PECs are: (a) it must be capable of dissolving the redox species, (b) it should have a high ionic conductivity, (c) it should be stable over a considerable period of time, (d) it should not allow unnecessary reactions at the interface between the polymer film and the semiconductor, (e) it should have a low optical absorption to prevent losses in conversion, and (f) its mechanical and electronic properties should be such that a semiconductor/electrolyte interface with the desired electronic properties can be formed. In the following section the materials, their properties, and methods used to investigate the physics and chemistry occurring in regenerative solid-state PECs based on substituted polythiophene photoactive electrode/polymer electrolyte junction will be discussed.
5.2. Materials, Device Structure, and Experimental Set-Up Among the conjugated polymers, substituted polythiophenes have attracted attention because of their chemical and environmental stability, reliable mechanical adhesion to different electrodes, solubility in common organic solvents, high conductivity, and variable band gap. They have been observed to be fairly stable under irradiation and to have high optical absorption in the visible range. Therefore, they are used as a photoelectrodes and the results obtained are presented in this section. The chemical structures of the conjugated polymers used in the construction of the solid state PECs studied in this work are shown in figure 19. Except for poly(3-methylthiophene) and poly(3,4-ethylenedioxythiophene) which were synthesized electrochemically, they were synthesized chemically and obtained in the neutral, semiconductive state. After dissolving polymers in a solvent, films were coated on ITO either by spin coating or solvent casting. The thickness of the film was controlled by the concentration of the polymer solution and/or the rotation speed. Electrochemical polymerization was done from a solution of the monomer dissolved in a solvent having an
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appropriate supporting electrolyte in a three-electrode one-compartment electrochemical cell. The film was obtained in its oxidized state directly on ITO and was then reduced to the semiconductive state in a monomer-free solution. The thickness of the film was controlled by the amount of charge supplied during polymerization. The thickness of the conjugated polymer films ranged between 10 nm and 2 μm. H3 C
C6H13
S
n
C8H17
S
(I)
n
(II)
O
O
S
S
n
n
(IV)
(III)
C8H17
C8H17
S S (V)
n
S
n (VI)
Figure 19. Chemical structures of substituted polythiophenes used in these studies. (I) poly[3methylthiophene], P3MT, [190] (II) poly(3-hexylthiophene), P3HT, [191] (III) poly[3-octylthiophene], P3OT, [192] (IV) poly[3, 4-ethylenedioxythiophene], PEDOT, [193] (V) poly[3-(4-octylphenyl) thiophene], POPT, [193] (VI) poly[3-(4-octylphenyl)-2,2'-bithiophene], PTOPT [194].
The polymer electrolyte was amorphous poly(ethylene oxide), from the poly[oxymethylene-oligo(oxyethylene)] family [117-121], with a repeating unit of CH2O(CH2CH2O)9, (POMOE). It has a melting point below room temperature and a glass transition temperature of 209 K. At room temperature it will not crystallize or form crystalline polymer-salt complexes with moderate salt concentrations [121]. Amounts with the desired stoichiometry of the redox couple and the polymer were dissolved separately or together in an appropriate solvent. After thorough mixing of the two solutions, the polymer electrolyte thin films were produced by solvent casting, in which the solvent is slowly evaporated from a homogeneous solution. The thickness of the polymer electrolyte films was in the range of 0.1 μm to 6 μm. The counter electrode was platinum, deposited by vacuum evaporation onto ITO-coated glass, or oxidized poly(3,4-ethylenedioxythiophene) coated electrochemically on ITO. Platinum or oxidized poly(3,4-ethylenedioxythiophene) were required on ITO because they improve charge transfer between ITO and the iodide/triiodide redox couple: it is known that bare ITO is irreversible for the iodide/triiodide oxidation/reduction reaction [193, 195]. The basic structure of the solid-state PECs used in this study is shown in figure 20. It contains electrically conducting conjugated polymer, substituted polythiophenes, an ionically conducting polymer electrolyte, POMOE complexed with iodide/triiodide redox couple, and a counter electrode, Pt or PEDOT coated on ITO.
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Figure 20. The basic structure of the solid-state PECs.
The general experimental set-up used for the photoelectrochemical measurements is as shown in figure 21. It contains a power supply, a lamp housing, a monochromator, a sample holder, and an output-measuring instrument. The cell is assembled and mounted inside a sample holder with light entrance window. The measurements to be taken to characterize the solar cells include current-voltage, stability towards light, spectral response, short-circuit current and open-circuit voltage dependence on incident light intensity, variation of opencircuit voltage with redox couple concentration, etc., using standard electrical, optical, photoelectrical and photoelectrochemical techniques.
Figure 21. General experimental set-up used for the photoelectrochemical measurements. (a) Power supply, (b) lamp housing, (c) monochromator, (d) sample holder, and (e) an output measuring instrument.
5.3. The Conjugated Polymer/Electrolyte Interface The property of a conjugated polymer/electrolyte interface is similar to that of an inorganic semiconductor/electrolyte interface. If a conjugated polymer is brought into contact with an electrolyte containing a redox couple with a different electrochemical potential, charge will flow across the interface and equilibrate by building up a space charge layer at the
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interface. The bands bend at the interface depending on the relative positions of the electrochemical potentials of the two media. This band bending results in the formation of a potential barrier, i.e., Schottky barrier, at the interface. The energy band diagram when they are in contact with an electrolyte is depicted in figure 22.
Figure 22. Energy band diagram for a conjugated polymer/electrolyte junction.
There is a difference between light absorption in conventional semiconductor and in conjugated polymeric semiconductors. Conventional semiconductors have a fairly rigid crystalline lattice. Polymeric semiconductors have a soft one-dimensional lattice and have inter- and intra-molecular interactions, local structural disorders, amorphous and crystalline regions, and chemical impurities. If we break one bond, the lattice will be severely distorted because in a one-dimensional lattice the atoms are kept in position by the two neighboring bonds, whereas in a three-dimensional lattice they are bound to the neighbors in all three directions. In conventional inorganic semiconductor, absorption of a photon produces electron and hole charge carriers, but in conjugated polymer-based PECs light absorption results in the generation of excitons. These excitons diffuse as uncharged particles until they dissociate into free charge carriers for the photocurrent generation. If they dissociate at the conjugated polymer/electrolyte interface, the majority carriers (holes) move into the conjugated polymer and the corresponding electrons travel towards the electrolyte. The Fermi levels shift due to this charging effect and a photovoltage is produced.
5.4. Steady State and Transient Properties The parameters that are used to describe solar cells are the short circuit current (Isc) and the open circuit voltage (Voc). The photovoltage developed during illumination is measured with a voltmeter having a very high internal resistance so that negligible current can flow through the cell. The photocurrent is measured using a very small load resistance. These parameters determine the efficiency and are the key parameters in experimental investigation of solar cells. Steady state and transient measurements of Isc and Voc, established during long and short period of irradiation, are used to characterize the stability of the PECs towards illumination. As an example, the transient photocurrent in the study of P3HT-based solid-state PECs is
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shown in figure 23. [191]. The transient photocurrent of the PEC is characterized by a rise to a steady state value when the light is switched on and decay at approximately the same rate when the light is switched off. The photocurrent obtained with a longer period of irradiation indicated that the stability of the P3HT towards light illumination is fairly good. Similar results were obtained for the other substituted polythiophenes based solid state PECs studied. Table 2 summarizes Isc and Voc of the various solid-state PECs studied.
Photocurrent [µ A/cm2]
0.6 on
off
on
off
200
300
400
500
0.4
0.2
0.0
Time [s] Figure 23. Transient photocurrent of P3HT-based solid-state PEC [191].
Table 2. Isc and Voc of a solid state PECs illuminated with light intensity of 100 mW/cm2 from the front side PEC
Isc (μA/cm2)
Voc (mV)
Ref.
ITO/P3MT/POMOE, I3/I¯/Pt/ITO
0.35
140
[190]
ITO/P3HT/POMOE, I3/I¯/PEDOT/ITO
0.47
130
[191]
ITO/P3OT/POMOE, I3/I¯/Pt/ITO
0.04
250
[192]
ITO/POPT/POMOE, I3/I¯/PEDOT/ITO
0.20
166
[193]
ITO/PTOPT/POMOE, I3/I¯/PEDOT/ITO
0.40
240
[194]
5.5. Current-Voltage Characteristics If an external field is applied with forward bias (negative voltage at the counter electrode relative to the working electrode), it acts to diminish the effects of the internal barrier field. Carriers can acquire sufficient energy to cross the barrier, and at high enough external voltages a large current will flow. On the other hand, if the bias is reversed, the external field enhances the barrier potential and only a small current flows. Thus, the junction acts as a rectifier since the current flowing for a given positive external voltage is quite different from
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the current flowing at the same negative voltage. Such a current-voltage characteristic is described mathematically as [196] I = Io [exp(qV/nkT) - 1]
(4)
where Io is the saturation current, q the electron charge, k the Boltzmann constant, T the absolute temperature, V the applied voltage, and n the ideality factor. The rectification characteristic is typical of diodes, and equations that have the form of Equation 4 are generally called diode equations. The conjugated polymer/electrolyte interface also obeys the diode equation. As example, the current-voltage characteristic of a junction between P3HT and a polymer electrolyte in the dark is shown in figure 24. [191]. The forward current corresponds to a positive bias where the barrier height is lowered, whereas in reverse polarization the increased barrier prevents the passage of a current. 3
Current [mA/cm2 ]
2
1
0
-1
-2 -0.4
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
Voltage [V]
Figure 24. Current versus voltage characteristics in dark (open circles) and under white light illumination (solid squares) from the front side of the P3HT based solid-state PEC with a light intensity of 100 mW/cm2 [191].
Under illumination, absorption of photons creates excitons, and later both the majority and the minority carriers. The concentration of photogenerated majority carriers are usually small. This implies that illumination does not significantly perturb the majority carrier behavior either in the semiconductor or at the semiconductor/electrolyte interface. Because the majority carrier concentrations are essentially unchanged, the majority charge flow is also unchanged. Majority carriers should thus exhibit the I-V characteristic that is well described by the diode equation, regardless of whether it is in the dark or under illumination. The current under illumination can generally be described by adding the current from photogenerated carriers to the dark current. From Equation 4 the I-V characteristic under illumination is given by
Solid State Organic Photoelectrochemical Solar Energy… I = Iph - Io [exp(qV/nkT) - 1]
189 (5)
where Iph is the component of the current that has been generated by illumination. The I-V curve obtained under illumination for a neutral P3HT-based solid-state PEC is depicted in figure 25. [191]. A cathodic photocurrent was observed at cathodic potentials, indicating that P3HT behaves as p-type semiconductor. The cathodic photocurrent is due to photoinduced minority carrier injection from the P3HT electrode into the electrolyte, where they react with the electron acceptor. The majority carriers go to the back contact and react with the electron donor at the counter electrode. The process is cyclic, and therefore there is no net chemical reaction and the PEC converts light to electricity in a regenerative mode. The possible operation mechanism is depicted in figure 25.
Figure 25. Operation principle of the solid-state PECs.
One of the new results from these studies is that the redox species may be diffusing inside the polymer photoelectrode. If this is the case, which is probable as conjugated polymers are mixed electronic-ionic conductors, novel possibilities arise. We do not necessarily have to move the excitons to the electrode/electrolyte boundary; we can position the redox species in many, many different geometries inside the polymer solid; we can collect excitons deep inside the polymer film. The utilization of these phenomena to bring about higher photocurrents is non-trivial, but some important avenues are already visible. First, we may use redox species that are effective acceptor (or donor) molecules. There are reports of very fast electron transfer from polymers onto fullerenes, which could be an inspiring example [197]. There is further the possibility of dynamic geometry with diffusing redox species, which could help in bringing about an effective charge separation. The possibility of movement by diffusion might also be of some importance, when it comes to preventing back electron transfer. And thirdly, the possibility of making mixed electronic-ionic conductors with enhanced ionic transport, such as in the main chain conjugated polymers decorated with side chains of oligo(ethylene oxide), is showing promise [198]. The thin films used in these devices will allow an effective absorption of light, but the photocurrents will be limited by the
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ionic transport. It has been shown that even with present day polymer electrolytes, the ionic transport can be sufficient for photovoltaic purposes [192].
5.6. Spectral Response Most substituted polythiophenes are coloured and absorb in the visible range of the electromagnetic spectrum. The transition between the π- and π *-orbitals can be seen in the UV-VIS optical absorption spectra. In general, the absorbance (A) and transmittance (T) of a material can be expressed by Beer's law A = ln(Ii/I) = εcl
and
T = I/Ii = exp(-εcl)
(6)
where I is the transmitted light intensity, Ii is the incident light intensity, ε is the molar extinction coefficient, l is the optical path length, and c is the concentration of the absorbing material. For solids, the concentration of the absorbing material is constant and Equation 6 can be rewritten as A = ln(Ii/I) = αl
and
T = I/Ii = exp(-αl)
(7)
where α = εc is the absorption coefficient of the material. A and α are functions of the wavelength at which the light absorption is measured. This latter equation is the form that is usually used for expressing light absorption in thin films of conjugated polymers. The photocurrent collected at different wavelength relative to the number of photons incident on the surface at that wavelength determines the spectral response of the device (sometimes known as the external quantum efficiency or collection efficiency at each wavelength). Light of different wavelengths is absorbed at different depths in the conjugated polymer film. The ability of a solar cell to generate photocurrent at a given wavelength of the incident light is measured by the incident monochromatic photon to current conversion efficiency (IPCE), defined as the number of electrons generated per number of incident photons. It can be obtained from the photocurrents by means of the following equation [175] IPCE% = (1240 Isc)/(λ Ii)
(8)
where Isc is the short circuit current (μA cm-2), λ the excitation wavelength (nm) and Ii the photon flux (W m-2). The quantum efficiencies obtained for the solid-state PECs studied was less than 1%. In general the quantum efficiency of the solid-state PECs when illuminated from the front side is greater than for backside illumination. This is due to the optical filtering effect of the conjugated polymer films. When light is illuminated from the backside only a small fraction of the excitons produced by light absorption reach the interface to dissociate into carriers. In addition, the presence of a high density of traps in the film reduces the number of carriers for the photocurrent generation. The greater the distance from the surface, the smaller is the probability for an exciton to reach the interface and dissociate into carriers. In conventional inorganic semiconductor solar cells, the absorption with a photon energy greater than the band gap leads to a direct generation of an electron-hole pair that is separated by the built-in electric field; the charges are transported to opposite electrodes and produce a
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photocurrent. However, in molecular semiconductors the absorption of a photon creates an exciton rather than free charge carriers. To generate photocurrent, these excitons must dissociate into free carriers either in the bulk or at the interface. Based on experimental results obtained from many molecular semiconductor solar cells [16, 199-203], only those excitons that reach the active junction produced free charge carriers. The excitons reach this interface by diffusion, then dissociate into carriers that are transported to opposite electrodes for collection. Several researchers working with different molecular semiconductors [16, 199203] have noticed a difference in the action spectra depending on which side of the cell is illuminated: front (rectifying contact) or back (ohmic contact). For front side illumination, the strongly absorbed light creates excited states in the barrier region. Under these conditions, the absorption spectrum is usually well matched to the action spectrum. For backside illumination the organic material itself acts as an optical filter for the strongly absorbed light in the fieldfree bulk region, and only weakly absorbed photons penetrate into the depletion region and make a major contribution to the photocurrent. The spectral response then does not match the optical absorption spectra. A comparison of the optical absorption spectrum and the spectral photoresponse can be used to identify the active junction responsible for the photoelectrochemical phenomena. If illumination through the front side of the PEC produces a spectral response, which corresponds to the absorption spectrum of the conjugated polymer, then the conjugated polymer/electrolyte junction is responsible; if illumination from the backside produces a matching spectrum, then it is the conjugated polymer/ITO junction, which is active. The photocurrent action spectra plotted in terms of IPCE versus wavelength for front side and backside illumination of the solid-state PEC with P3HT photoactive electrode, together with the optical absorption of the P3HT film coated on ITO, are shown in figure 26. [191]. Normalization was done to the peak values in order to facilitate the comparison between the photocurrent action spectra and the optical absorption spectrum.
Normalized to peak value
1.0
0.8
0.6
0.4
0.2
0.0 300
400
500
600
700
800
Wavelength [nm]
Figure 26. Optical absorption spectrum of P3HT coated on ITO (open triangles) and normalized photocurrent action spectrum of P3HT based solid-state PEC from the front side illumination (solid squares) and from the backside illumination (open circles) [191].
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The optical absorption spectrum and the action spectrum for front side illumination match. This indicates that the active junction responsible for the photoelectrochemical properties of the PEC is that between the conjugated polymer and the polymer electrolyte. Since the generation of charge carriers occurs close to the active interface rather than in the bulk of the polymer film, the kinetics of the interfacial electron transfer processes may determine the photoeffects. This hypothesis can thus explain why excitons, which are produced predominantly in the interior, yield a weaker photocurrent than those that are produced at the interface.
5.7. Dependence of Photovoltage on Redox Couple Concentration The formation of junction between the conjugated polymer and the electrolyte gives some means of varying the redox potentials of the electrons and holes in the conjugated polymer relative to the redox systems in solution. By changing the solution redox potential one can manipulate the properties of the semiconductor/electrolyte interface. There are two different methods of changing the solution redox potential: varying the concentration ratio of the reduced and oxidized species or holding the redox concentrations constant while varying the molecular species. One can therefore vary the ratio of the redox couple concentration or the molecular species to vary the photovoltage of the PEC. For p-type semiconductors, negative redox potentials produce highly rectifying contacts, while positive redox potentials produce poorly rectifying contacts. Therefore, high photovoltages are generated with comparatively large negative redox potential for p-type semiconductors. For a given photoactive electrode, the magnitude of the photovoltage is dependent on the concentration of the redox couple. Table 3 shows the effect of redox couple concentration on the open circuit voltage for a P3OT-based solid-state PEC [192]. As the concentration ratio between the oxidized and reduced form increases, the open circuit voltage decreases. On the other hand, as the concentration ratio increases, there will be a point at which the PEC does not produce a photovoltage at all. Chemical doping of the conjugated polymer, which changes the state of the conjugated polymer from semiconductive to the conductive, causes this. The effect of increasing the concentration of the redox couples causing doping of the conjugated polymer can be seen from the optical absorption of a P3OT-based solid-state PEC (curve a figure 27.) [192]. Two new optical transitions below the band gap transition appeared, together with a decrease of the band gap transition, indicating doping. Table 3. Variation of open circuit voltage with concentration ratio of I3- to I- [192] [I3-]/[I-] 10 1.0 0.1 0.01
Voc (mV) 223.0 250.0 523.3
Isc (nA) 53.3 31.0 32.3
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Figure 27. Optical absorption spectrum for P3OT-based solid-state PEC at different concentration ratios of I3- to I-: (a) 10, (b) 0.01, (c) 0.1, and (d) 1 [192].
5.8. Dependence of Photocurrent and Photovoltage on Light Intensity For organic and some inorganic solar cells, the short circuit current increases with increasing light intensity (Ii) and is proportional to Iiα [204]. Thus, a plot of log Isc versus log Ii yields a straight line whose slope is characteristic of the photoactive material. The Isc dependence on the incident light intensity for all solid-state PECs gave a linear plot with a slope less than unity. Such sublinear dependence implies bimolecular recombination of excitons and/or the presence of a high density of traps in the film [204-207]. The trapping could arise from structural defects on the materials that promote charge recombination and reduce the average lifetime of the charge carriers. For Schottky junction solar cells under open circuit, no net current will flow through the junction and Equation 5 can be rearranged to yield the following relationship: Voc = nkT/q ln[(Iph/Io) + 1] = nkT/q ln(Iph/Io)
for Iph >> Io
(9)
As can be seen from Equation 9, Voc increases logarithmically with the light intensity because Iph is linearly proportional to the incident light intensity. All of the solid-state PECs studied show an open circuit voltage which is logarithmically dependent on the light intensity, in agreement with the projected behavior of Schottky barrier solar cells.
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6. CONCLUSION Organic solar cells may provide a unique alternative to inorganic photovoltaics. They function in a similar manner to the inorganic semiconductors but also have important advantages such as: high absorption coefficient, low cost, light weight, ease of fabrication and the possibility of large area coatings. One such type of cells is solid-state PECs. In this chapter it is shown that solid-state PECs convert solar energy to electrical energy. The photoactive electrodes were electron conducting, neutral, substituted polythiophenes and the ion conducting polymer used as an electrolyte, was amorphous poly(ethylene oxide) complexed with the iodide/triiodide redox couple. In order to understand the physics and chemistry of the cell studies such as I-V characteristics, steady and transient properties, spectral response, dependence of photocurrent and photovoltage on light intensities, and dependence of photovoltage on the redox species concentration ratios were made.
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In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 201-218
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 5
A NEW APPROACH TO HYBRID SYSTEMS OF RENEWABLE ENERGY UTILIZATION* Yu.V. Vorobiev1, J. Gonzalez-Hernandez2†, P. Gorley3, P. Horley3 and L. Bulat3 1
CINVESTAV, Unidad Queretaro, Queretaro 76230, Mexico 2 CIMAV, Chihuahua 31109, Mexico Department of Electronic and Energy Engineering, Chernivtsi National University, Chernivtsi 58013, Ukraine 3 St. Petersburg State University of Refrigeration and Food Eng., St. Petersburg 191002, Russia
ABSTRACT A general analysis is given of hybrid systems consisting of different combinations of 4 devices frequently employed for renewable energy utilization: Photovoltaic Solar Panel (PV), Solar Thermal Plane Collector (ST), Wind Generator (WG) and Heat-toElectric/Mechanic Energy Convertor (HE); some of the combinations include radiation energy flux concentrators of different degrees. The main result of the consideration made is that the hybrid systems are more efficient than the sum of the constituents and more stable in relation to spontaneous variations of the renewable energy source potential (like wind velocity, insolation, etc.). However, to realize the possibilities mentioned, all the elements of a given hybrid system have to be especially designed and made for this specific system. For example, the PV panel for the hybrid PV/Thermal system ought to have a substrate with high thermal conductivity, to allow for heat extraction from the panel by the adjacent Solar Thermal Plane Collector, and practically no commercial panels with these characteristics are available. Besides, the PV panel as a part of the hybrid system will demand a special choice of semiconductor material and surface *
A version of this chapter was also published in Leading Edge Research in Solar Energy edited by P. N. Rivers published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research. † On sabbatical leave from CINVESTAV-Queretaro
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Yu.V. Vorobiev, J. Gonzalez-Hernandez, P. Gorley et al. treatment which could be different from those for conventional panels. The limiting efficencies for some hybrid systems are estimated; these efficiencies exceed the efficiencies of separate use of the devices discussed. The most promising hybrid system is the PV panel made as spectrum splitter in combination with HE converter, of which total efficency could be around 50 %.
INTRODUCTION Among many devices employed for the renewable energy generation, a special place is occupied by photovoltaic solar cells, for many reasons (like low maintenance, long lifetime, etc.). The key problem in solar cells science and engineering is the restricted efficiency of Solar Energy conversion resulting from the impossibility of efficient utilization of a wide solar spectrum with one semiconductor material. The possibilities of using more than one material (multijunction cells, spectral splitting with many cells [1-6]) or hypothetical materials with very specific parameters [7,8] do not give a simple solution to the problem because of technological problems and very high cost. On the other hand, the hybrid systems of a different kind recently became very popular (for example, [9-14]); some of them, like PV/Thermal, are developed up to commercial stage. It is evident that these hybrid systems a priori could provide a higher efficiency of utilization of renewable energy source resulting from the smaller total area than that of the sum of separate parts of a system, having at the same time a relatively low cost. In addition the hybrid systems have advantages compared to their elements, since each one of the separate devices forming the system has its own working conditions which quite often are contradictory (for example, the windy weather is profitable for wind generators, but it reduces efficiency of solar thermal collectors), therefore the hybrid system can be made almost independent upon the variation of these conditions, and thus more stable and reliable. The common way to build a hybrid system is to use a combination of existing devices, which is definitely the simplest and the cheapest approach. However, this way may not be the most efficient one. The present paper intends to show that to optimize the construction and performance of any hybrid system, one has to make a special analysis of the coupling conditions of the devices used, and, in the majority of cases, to design each device accordingly to the specific system’s demands. The result will be the highest efficiency and stability of the system.
THEORETICAL ANALYSIS Separate Performance of the System’s Elements Here we give the basic information necessary to discuss the different combinations of the elements (for the 4 elements, there are 10 possible combinations; we shall discuss only those which we consider are the most important). Photovoltaic Solar Panel (PV) with the sensitive area APV, efficiency ηPV is exposed to solar radiation of power W during Δt1 hours per day (the last parameter is the averaged
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considering the hourly changes in the solar position). Thus, the total energy generated by a PV per day is EPV = ηPV W APV Δt1
(1)
For a typical Si solar photovoltaic module with an efficiency of 12 % and area of 1 m2, under solar illumination corresponding to AM1.5 conditions (844 W/m2), the power generated will be approximately 100 W, and the energy corresponding to the average 5.5 sun hours per day (data taken for the state of Queretaro, Mexico, no Sun tracking is assumed), in agreement with (1) is 550 Wh. Solar Thermal Plane Collector (ST) is converting the sun radiation into heat stored in water or air circulating within the collector. Its efficiency ηΤ is usually 50 – 70 % ([9-11]), and is very dependent upon the working conditions like the temperature difference between input and output, cooling conditions, etc., so thermal energy generated by ST with area AT during the sun hours will be ET = ηT W AT Δt1
(2)
and for each square meter of area, the daily thermal energy produced is around 3 kWh. Wind Generator (WG) utilizes a secondary product of solar radiation – the wind, and its performance is determined, first of all, by the wind velocity v. For a WG “controlling” the area AA of air flux, the power WW converted to electricity is the part ηW (WG efficiency) of the corresponding air flux kinetic energy per unit time which is equal to 0.5 ρVv2, ρ being the air density and V – volume per second of the air flux controlled. For the latter we write V = AA v, and thus obtain WW = 0.5 ηE ρ ΑΑ v3,
(3)
so the total energy EW produced during the working time interval Δt2 will be EW = 0.5 ηE ρ ΑΑ v3 Δt2
(4)
Here the corresponding time interval can be 24 hours per day, although the wind velocity could vary considerably during the day. Taking the flux controlled area equal again to 1 m2, air density ρ = 1.29 kg/m3, wind velocity 8 m/s which is considered as the minimum for a good WG performance, and the effectivity 0.25 (some average value), we get from (3) the power 82.6 W; for 24 hours per day performance, according to (4) it gives approximately 2 kWh of energy. The estimations made show that each of the devices considered produces considerable amount of energy per day (from 0.55 to 3 kWh), which could be utilized for domestic or other applications. The analysis below will show the advantages in combining these elements in hybrid systems, and the specific demands related with the array. Heat-to-Electric/Mechanic Energy Convertor (HE). In this part, some heat engines could be considered (like Stirling Engine frequently used in the field discussed, with extensive literature). Here we present information about thermoelectric generators (TEG) which is less
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familiar to the general audience. The thermoelectric method is a direct method of energy conversion similar to the photovoltaic one, so it is natural to combine these two methods in a hybrid system. It is also important that thermoelectric devices (again, like the photovoltaic ones) are highly reliable and could work 10 – 30 years practically without any technical service (see [15-19]) which unfortunately could not be said in relation to heat engines. The TEG efficiency. The efficiency of a thermoelectric generator TEG is determined by so called thermoelectric figure of merit
Z=
α2 , ρκ
(5)
where ρ is the electric resistivity,
κ - the thermal conductivity and α - the thermo-emf
coefficient of a thermoelectric (semiconductor) used. A modern thermoelectric module (a unit thermoelectric converter) is a battery – a number of alternate n- and p-type semiconductor branches. They are connected electrically in series with metallic connection strips, sandwiched between two electrically insulating and thermally conducting ceramic plates to form a module. So, any TEG contains two different materials (corresponding indexes “1” and “2”), and the optimized figure of merit for a module can be presented in the form
Z0 =
(α1 − α 2 )2
( κ 1 ρ1 +
κ 2ρ2
)2
(6)
The efficiency of TEG can be characterized in two ways: [1]
Efficiency corresponding to the classic condition of the maximum power output R = r (the external electric resistance R equal to the TEG internal resistance r )
⎛ 4 T − Tc +2− h η1 = η 0 ⎜⎜ 2Th ⎝ Z 0Th [2]
⎞ ⎟⎟ ⎠
−1
(7)
Since the thermoelectric devices (the same as photovoltaic ones) are not characterized by a constant internal resistance, there exist another condition for the maximum TEG efficiency corresponding to the relation R = M = 1 + Z 0 T M , where TM is the average temperature r opt
( )
TM = 0.5 (Th + Tc). In this case
η max = η 0
M −1 . Tc M+ Th
(8)
A New Approach to Hybrid Systems of Renewable Energy Utilization
The coefficient
η0 =
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Th − Tc = ΔT/Th in (7) and (8) is the ideal thermodynamic Th
efficiency of a heat engine (the Carnot efficiency). Usually ηmax is a little higher than η1; as a rule, the difference between the values of the TEG efficiency given by the two expressions above does not exceed 4% [15]. Our purpose is to estimate the highest efficiency of the hybrid system, therefore we use for calculations the expression (8). Thermoelectric materials. To proceed, we have to specify value of the figure of merit Z . It is necessary to point out that the figure of merit of semiconductors depends on temperature, and different kinds of semiconductor materials should be selected for different operating temperatures. The industrial thermoelectric materials can be divided in dependence of operating temperature into the following groups [15-18]: -
for temperatures up to 500K - the solid solutions based on bismuth telluride (Bi2Te3, Bi2Te3-Bi2Se3) are used; for temperatures up to 800K - the PbTe; for space applications (T>900K) - the solid solutions based on Ge-Si.
The main problem of thermoelectric material research is how to increase the figure of merit Z . Despite the efforts of many research groups in different countries, during 1950 2000 years the increase achieved in the dimensionless thermoelectric coefficient ZT was only from 0.75 to 1.0 (the data refer to room temperature). But an essential progress in the field was made during the last few years. The remarkable successes have been achieved on different directions: 1. Usage of the new physical ideas in nano-scale microstructures. A high quality 2D quantum superlattice with nano-scale films based on p-Bi2Te3/Sb2Te3 having ZT = 2.4 at room temperature was obtained [19-21]. A nanomaterial with quantum dots (1D structure) based on PbSeTe has the value of ZT = 2.0 at room temperature [22]. The increase of the figure of merit was also obtained in a special structure with cold points (like contacts between a plate and edge of a cone). The measured figure of merit of the last structure based on p-Bi0.5Sb1.5Te3 and n- Bi2Te2.9Se0.1 corresponds to ZT = 1.7 at room temperature [23,24]. 2. Alongside with semiconductor TEG there exist thermionic devices that also can be used for direct generation of electricity. However, the traditional thermionic converters work only at very high temperatures, above 800 К, necessary for electrons to overcome the potential barrier. But recently a theory has been offered [25] of a thermionic converter with a nanometers barrier thickness; here electrons can overcome the potential barrier by quantum tunneling. Apparently such thermotunnel converter has been realized [26]. The parameter equivalent to thermoelectric figure of merit of this converter is ZT = 4. 3. Another option is the application of some new bulk materials as thermoelectrics – so called skutterrudites and clathrates. It was shown that the thermal conductivity can be reduced in such materials [27], therefore the figure of merit will increase. The examples of skutterrudites are CoSb3 (n-type) and Zn4Sb3 (p-type) and of the
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Yu.V. Vorobiev, J. Gonzalez-Hernandez, P. Gorley et al. clathrates - CoFe4Sb12. These materials have good figure of merit in a wide temperature range and therefore can be used for TEGs.
Thus, for calculation of the efficiency of hybrid system in the temperature range 300 – 600 K we can use the following thermoelectric parameters: ZT = 1, value that have modern industrial thermoelectrics; ZT = 2, this value has thermoelectrics received in laboratories (nano-scale microstructures), and ZT = 4, value for thermionic converter with quantum tunneling. Using the expression (8) to estimate the efficiency and taking the temperature difference between hot and cold TEG sides equal to 300 K, we obtained for the three cases mentioned the corresponding efficiency of 10, 15 and 20 %.
Hybrid Systems (Different Combinations of Elemental Devices) Thermal-Wind (ST+WG). This complex may be useful for thermic applications (for example, to stabilize the temperature regime of a greenhouse or small living house in case of great daily variations of temperature, which is typical for Mexico), the energy generated during the day by ST is collected by hot water which is stored in thermally insulated water tank, to be used at night for heating of a building. The electricity generated by the WG will be used also for heating (through an electric heater with an efficiency practically of 100 %, or in a heat pump system where the efficiency could be almost doubled). The efficiency of the ST decreases almost linearly with the wind velocity; this decrease ought to be compensated by the effect of wind generator WG: its power is never linear with the wind velocity, so the compensation will be within some limits; actually, for a strong wing, there could be overcompensation. We can introduce an average wind velocity va and find the conditions of energy stabilization in relation to relatively small deviations (± Δv) of this velocity, taking |Δv| < va. Thus, for the ST efficiency we write ηT = ηTo (1 − α v) = ηTo [1 − α( va ± αΔv)], so that ET = C [1 − α( va ± αΔv)], where C = W AT Δt1
(2A)
and for the WG EW = C* (va ± Δv)3 ≈ C* (va3 ± 3 va2Δv),
(4A)
C* = 0.5 ηE ρ ΑΑ Δt2. Then for the total energy produced by the system per day we have Etot = [C(1 − α va) + C* va3] ± (3 C* va2 − Cα) Δv
(9)
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Now we have the condition of stability of the system energy as (3 C* va2 − Cα) = (1.5ηE ρ ΑΑ Δt2 va2 − W AT α Δt1) = 0
(10)
We shall see below how this condition could be applied to a real system. However, one general remark could be made now. The wind generators most frequently used (HA, or Horisontal Axis devices) demand very high wind velocity for normal performance (8 m/s or more). At these conditions, the thermal collectors have very low efficiency, and their use is not practical; the supportable wind velocity for their application is 3 – 5 m/s. It means that for the hybrid system of the kind discussed, the HA WG is not a good choice; at relatively low wind velocities, the Vertical Axis (VA) devices are more efficient. Photovoltaic-Thermal (PV + ST) System. This system (so-called “combi-panel”) has an evident advantage compared to the performance of the separated devices. In that system the ST absorbs the excessive heat of the PV thus cooling it and therefore enhances the efficiency of the PV panel. It is also clear that the total amount of energy produced per unit area increases by this combination. The detailed analysis of thermal balance in this system was published in our previous paper [28]; the results of the present analysis support the main conclusion. All the previous papers on the subject have taken for granted that the systems elements have to be of the same area. However, it is evident that the presence of the PV panel above the solar collector reduces the heat flux to the collector and thus its efficiency; on the other hand, the collector ability to extract heat from the PV panel is reduced while the water (air) inside it is heated. Therefore, the optimal case would be to make PV panel of smaller area than that of the heat collector, and to place it above the initial collector’s part (i.e. that corresponding to the entrance of the cold water). Another point is that the conventional PV usually could not provide a good thermal contact with the ST heat collector, so, this hybrid system demands a special construction of the PV with a high thermal conductivity of the substrate used; one example is given in the paper mentioned [28]. Wind-Photovoltaic (WG + PV) System. These systems are already in use; they are unique among the hybrids discussed in a sense that there are no specific demands to the devices combined. The system generates and stores electric energy day and night; since the WG has more working hours per day than the PV, low-power WG could match the higher power PV. To guarantee the normal performance of the system at different conditions of weather, the excessive battery bank ought to be used. This system is more effective in places with very high wind velocity: in addition to the WG driving, the wind stabilizes the PV temperature and therefore the efficiency of its performance. Wind-Thermal-Photovoltaic (WG+ST+PV) System. Here we consider the PV/Thermal system discussed above in combination with the wind generator WG, the system provides electricity generated by PV panel (at daytime) and by the wind generator (day and night), as well as the hot water from the ST collector (ought to be stored in thermally insulated vessel to be used in absence of illumination by sun). The total energy (electric + thermal) produced by the system per day will be Etot = (ηPV APV + ηT AT)WΔt1 + 0.5 ηE ρ ΑΑ v3 Δt2.
(11)
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The specific demands to the PV based on the necessity of a good heat exchange between the PV and the ST were discussed above. Photovoltaic-Heat-to-Electric (PV+HE) system. The scheme of a hybrid system discussed is presented in figure 1, parts A and B refer to the two different options (see below). It is evident from the figure that the two versions are very similar and contain the same basic elements (the concentrator “CONC”, photovoltaic cell “PVC”, High Temperature Stage “HTS” which is the HE converter, and the 2-axis Solar Tracking System “STS2”), although the type and construction of the cell (and the concentrator) could be different in the two cases. Below we discuss the working principles and possible parameters of the system in each version. A. System with separation of “thermal solar radiation” and low temperature operation of solar cell. (figure 1 A). This system needs a solar cell which at the same time acts as a spectral filter (splitter) neither absorbing nor dissipating the solar radiation part with quantum energy hν < Eg (“thermal solar radiation”) where Eg is the cell absorbing material band gap. It is shown below that this part could be quite large, especially for semiconductor materials with relatively wide band gap. Thus, in case of a semiconductor with Eg = 1.75 eV, approximately 50 % of solar radiation energy corresponds to the condition hν > Eg and is suitable for photovoltaic conversion, and another 50 %, with hν < Eg, could be used as thermal energy. In our system, this “thermal solar radiation” should be concentrated on the hot side of the HTS (thus providing its high temperature), and is converted by it into electric energy when HTS is Thermoelectric Generator (TEG), or to mechanic energy by heat engine as the HTS (like Stirling Engine [29] which has efficiency very close to that of the Carnot cycle). It is known that mechanic energy could be converted into electricity with efficiency above 90 % which allows to have rather high total energy conversion coefficient of the hybrid system.
Figure 1. Schemes of hybrid system with High Temperature Stage.
To calculate the percentage of “thermal solar radiation” as a function of semiconductor band gap, we used the simple graphical analysis of solar radiation spectrum introduced by Henry [2] and included now in textbooks [30], with a numerical integration to determine the function nph (Eg), the solar flux absorbed by a semiconductor (as in Henry paper, we assume that the semiconductor is opaque for photon energies greater than Eg and transparent for energies less than Eg). This flux is given by
A New Approach to Hybrid Systems of Renewable Energy Utilization ∞
n ph ( E g ) = ∫ E
g
dn ph dhω dhω
209
(12)
The function obtained is shown in figure 2: the lower curve (squares) for AM1.5 spectrum, and upper one (circles) – for AM0. Following the graphical analysis procedure [2,30]), on the basis of these curves we found the percentage ξ of “thermal solar radiation”: in figure 2 it is shown by triangles (upper curve for AM0, lower for AM1.5; the corresponding values of the figure 2 ought to be multiplied by 10 to get ξ in %). One can see that ξ varies between 10 – 12 % for Eg = 0.8 eV and 78 – 80 % for Eg = 2.3 eV. The ξ vaues obtained for AM1.5 spectrum are also included in figure 3 (circles). This thermal part of solar radiation energy has to drive the HTS (heat engine or TEG); assuming that HTS efficiency is proportional to that of Carnot cycle, with a coefficient K < 1 (the difference between K and 1 shows how close the HTS is to the ideal engine; in general, K could be temperature dependent, in particular, in the TEG case). Thus, this part of solar energy conversion is characterized by the efficiency ηtherm = ξ⋅K ΔT/Th
(13)
nph (1017 cm-2 sec-1 eV-1), 0.1 ξtherm
where Th is the temperature of the hot side of the HTS, and ΔT the temperature difference between cold and hot sides.
8 6 4 2 0
0
1
2
3
ENERGY(eV)
Figure 2. Graphical analysis of the efficiency of an ideal solar cell, for AM1.5 and AM0 solar spectra, with the calculated percentage of “thermal” radiation.
The solar cells for hybrid system of this kind have yet to be designed and made, but we do not see any principal obstacles to that. To estimate the cell efficiency ηCA as a function of band gap, we took 0.75 of the corresponding cell’s ideal efficiency at non-concentrated radiation ηid [2,30]; since for all well developed cells (based on Ge, GaAs, CuInSe2) the best efficiency obtained is well above this value, we consider this approximation reasonable. The corresponding values (ηCA = 0.75 ηid) for the AM1.5 irradiation are shown in figure 3 by
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squares (lower curve). We may add that if a variety of these cells-filters will be available, the cells with decreasing band gaps could be connected optically in series to increase the total efficiency, as an alternative to the multijuncion cells. An additional note is that the cell for this system should not have any surface texturizing which is typical for conventinal solar cells. Using for the HTS efficiency the expression (13), we get the total system efficiency
Efficiency; "Thermal" radiation (%)
ηtotA = ηCA + ηtherm = ηCA + ξ⋅K ΔT/Th
(14)
80
60
40
20
0
1,0 1,2 1,4 1,6 1,8 2,0 2,2 2,4
Eg, eV
Figure 3. Percentage of “thermal” radiation in the AM1.5 spectrum, PV cell estimated efficiency and the total system efficiency as function of Eg..
The curves calculated according to (14) for K = 0.8, ΔT = 500 and 1000 K, are shown in figure 3 by up- and down-sided triangles. In this case, the total efficiency could exceed 50 55 %, without an employment of expensive high technologies. We must note that the temperature differences used for our calculations do not exceed those practically employed in Stirling engines (for example, Bernd Kammerich 1 kW Engine, Germany). B. System without the solar spectrum division, a PV cell operates at high temperature. This is more straitforward system (figure 1B) than the one discussed previously; the conditions of the PV cell performance are not quite favorable here, but the system, in principle, could be constructed on the basis of the elements which already exist (although the lifetime of the PV cell in question needs special study for this working regime). The cell is subjected to concentrated sunlight, which usually enhances its efficiency; the thermal flux through the cell is transfered into the HTS by direct thermal contact, thus the cell working temperature is equal to the Th parameter of the HTS.
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Efficiency, %
40 30 20 10 0 300
350
400
450
500
550
600
Th , K
Figure 4. Calculated temperature dependencies of the PV cells efficiency (squares, triangles) and of the total hybrid system efficiency, in case of the heat engine as HTS (circles, diamonds) and the TEG (three intermediate curves, ZT = 1, 2, 4).
For calculation of the expected system efficency, two types of cells with relatively high (but not record) efficiency are considered: a GaAs single junction cell [31] with room temperature efficiency (ηο) of 24 %, and multijunction GaAs-based cell with corresponding efficiency of 30 % [3]. Both values refer to radiation concentration of approximately 50 Suns which is sufficient to achieve cell temperature higher than 450 K. The temperature dependence of cell efficiency η(T) is assumed linear with the coefficient β = (dη/dT)/η equal to – 2.7X10-3 K-1 [32]; it gives for the temperature 450 K the efficiency values η∗ = 14.3 % for single junction (SJ) cell, and 17.8 % for multijunction (MJ) cell. Thus, practically 80 % (i.e. 1 – η∗) of solar radiation energy will be transformed to heat within a cell, and may be used for a heat-to-electric/mechanic energy conversion by the second stage of a hybrid system – a HTS. The total conversion efficiency of hybrid system could be written as ηtotB = η∗ + (1 – η∗) ηHTS
(15)
Here we have η∗ = ηο (1 − β ΔΤ), ΔΤ = Τh − Τroom ≈ Τh − Τc, (Τc is the temperature of the cold size of the HTs which is approximately equal to the ambient temperature Τroom), and for the HTS we take, as in part “A”, that it is proportional to the Carnot engine efficiency: ηHTS = K ΔT/Th, which gives for the total conversion efficiency ηtotB = ηο (1 − β ΔΤ) + [1 − ηο (1 − β ΔΤ)] K ΔT/Th.
(16)
Figure 4 shows the calculated results for the hybrid system with the two cells mentioned above; the temperature dependence of the cells efficiency is shown by squares (SJ) and triangles (MJ). The total efficiency with the heat engine acting as HTS is represented by the growing curves, (circles for single junction cell, diamonds for multijunction cell, K = 0.8).
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One could see that the second stage gives significant increase in the total efficency for relatively modest values of ΔT, and the total efficency could be as high as 35 – 40 %. For the system “B” having the thermoelectric generator TEG as the HTS, we present in figure 4 the results of calculations of the total efficiency for three ZT values given above, taking as a basis the equation (15) and using ηmax (8) instead of ηHTS. The PV cell is supposed to be of MJ type, with the room temperature efficiency of 30 %; the corresponding results for ZT = 1, 2 and 4 are shown in figure 4 by three descending curves starting from efficiency 30 % at 300 K (the larger ZT, the higher curve). It is seen that the TEG has considerable effect on the efficiency in all cases, although the total efficiency of the system with TEG is lower than with heat engine. Taking into account the extraordinary recent progress in the TEG field, we can expect further increase of the TEG efficency, and that of the hybrid system.
EXPERIMENTAL The basic elements employed in experimental study were the following. The solar heat collector ST used was of the model Powermat, with water as a heat collecting agent, having a surface area of 4 m2; approximately 90 % of the surface area is controlled by the internal tube system providing an efficient heat interchange. The black PVC absorber covering the collector is resistant to UV solar radiation (the guaranteed lifetime is 20 years) and provides a small weight of the panel (about 3 kg in empty state, and 7 kg when filled with water). The maximum heating efficiency at the absence of the wind estimated using the Hottel-Whillier model [11-13] was around 60 – 70 %, which corresponds to the best collectors known. This result is illustrated in figure 5, which gives the dependence of the ST efficiency upon the temperature difference between the water entering the collector and the ambient temperature Ta. 1.00
Efficiency (%)
0.75
0.50
0.25
0.00
0.008
0.016
0.024 o
0.032
2
(Ti-Ta)/G ( Cm /W) Figure 5. The temperature dependence of the thermal efficiency of the ST studied.
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The dependence is practically linear, in good agreement with the Hottel-Whillier model, and the maximal value is close to 70 % indicating a good performance of the collector. The expression used to find the ST efficiency from experimental data was: ηT = Mt Cc (To – Ti) / GS
(17)
where Mt is the water flux (mass per second), G – solar radiation intensity, Cc - the water specific heat capacity, To is the output water temperature, and Ti - its input temperature. The PV panels investigated and used in PV/Thermal systems were of crystalline Si type (c-Si; in particular, we used the panel made by Russian plant OKB “Krasnoe Znamya” OKBKZ M100/12 with an area of about 1 m2 and the power generated under AM1.5 solar radiation of 100 W, and the other one assembled in our laboratory from 85×85 mm2 cells made by the same company). Besides, in the experiments designed to achieve a good thermal contact with the collector, we used the panels made of amorphous Si (α-Si, ECD Company, Troy, Michigan, USA) and CuInSe2 (CIS) commercial panel made by Siemens, USA. The electric efficiency of all the PV panels used was between 10 and 18 %. The prototype panel which we constracted to achieve the best thermal contact was made of Al substrate (thickness 2 mm) covered with 1 μm thick insulating film of PMMA/silica composite dielectric coating, with OKBKZ-made six c-Si solar cells (85X85 mm2) area, and a glass cover. One option to increase the efficiency of conventional solar panels is the use of bifacial panels [33,34]; to take full advantage of the rear photosensitive face, the panel ought to be placed at some distance from the white diffuse reflecting surfaces [34], or small degree radiation concentrators might be used. We employed the latter option (see photo in figure 6), the concentrator made of 5 stainless steel plates collected solar radiation from an area twice as big as the panel. It resulted in considerable heating of the panel; to overcome this effect, we plan to develop the water-running plane heat collector transparent in visible (not to affect much the rear face photovoltaic performance) and put it in thermal contact with the panel rear face. This system will produce electric energy and hot water, as any PV/Thermal system; we expect it to be useful for future domestic applications.
Figure 6. Bifacial solar cell with radiation concentrator for rear face.
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The wind generator WG was developed and built in our laboratory (figure 7). The vertical axis (VA) model of Savonius type, 3 m high, with an active area ΑΑ = 1.5 m2, having an automobile alternator with a home made gear-box as generating unit, under conditions of moderate wind, typical for the region of application (state of Querétaro, Mexico, average wind velocity about 5 m/s) provides approximately 40 W of electric energy operating at 120 rpm (see figure 8).
Figure 7. The constructed Vertical Axis Wind Generator . 60
Power (W)
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30
20
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60
80
100
Rotation velocity (rpm) Figure 8. Characteristics of the experimental wind generator.
120
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The PV+ST+WG system made according to the discussion above, is schematically shown in figure 9 (construction scheme – left part, electric scheme – right one). The electric part of the system includes the battery bank (4 sealed lead-acid batteries “Prism” 12 V, capacity of 105 AH each), Solar Charge Controller of the model Steca (Germany) and the DC-AC Inverter Proam (China). The arrangement made to investigate the regime of the solar thermal collector ST included two home-made electrical digital thermometers (1, 2 in figure 9) based on the temperature sensors LM335, the water flux meter CICASA Delaunet MD-15 (3 in figure 9), all three devices mentioned were connected to the computerized data acquisition system. The electrical connections scheme is made according to the generally accepted rules and notations, and does not demand comments.
Figure 9. Construction and electric shemes of the PV/ST/WG hybrid system (see text).
The devices used for study of hybrid systems performance were capable of production per day at normal working conditions discussed above EPV = 0.55 kWh (PV panel M100/12) and EW = 0.96 kWh (home made WG) of electric energy, plus ET = 12 kWh of thermal energy (ST Powermatt; the value given refers to the absence of wind). From (3) we find that our WG generating 40 kW at wind velocity va = 5 m/s has an efficiency ηE = 0.3 which could be considered as a good parameter. At the wind velocity mentioned, the ST will produce, according to (2A), 10.1 kWh of thermal energy per day (to find this value, we determined experimentally the coefficient α in (2A), taking measurements of the ST efficiency depending on v. Thus we obtained α = 0.032 s/m). In Thermal-Wind Hybrid System (ST+WG) designed for building heating purposes, according to discussion above, at average wind velocity of 5 m/s (expression (9)) it will provide approximately 11 – 12 kWh of heat energy, depending on the way of transforming of electric-to-heat energy. To discuss the heat production stability of the system in relation to small variations of wind velocity, we have to calculate the variations in the energy generation by the system’s elements according to (10). For the parameters given, we obtain the first part of (10) describing the dependence of WG productivity upon the changes of v (1.5ηE ρ ΑΑ Δt2 va2) equal to 0.576 kWhs/m, and the second part (similar dependence of the ST productivity, − W AT α Δt1) equal to − 0.594 kWhs/m. Thus we see that their sum is reasonably close to zero, i.e. our system is well balanced. According to the values found, the daily variations in
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energy production caused by changes of wind velocity Δv = ± 3 m/s will be around 0.05 kWh, which is less than 0.5 % of the total energy generated per day. In PV/Thermal Hybrid System (PV+ST) discussed above we obtain, in first approximation, the above mentioned amount EPV of electric energy and ET of thermal energy, with the difference that now the whole energy is provided by the area AT, not the sum of areas AT + APV. To get an additional advantage caused by the PV cooling in thermal contact with the ST, a special PV construction is needed; we have shown [28] that the actual increase of the PVM efficiency could be as high as 10 %. Our Wind-Photovoltaic Hybrid System (WG+PV) produces daily approximately 1.5 kWh of electric energy at average conditions of state of Queretaro, Mexico (we should stress that our model of WG is good for moderate wind velocities; for more windy places, the HA models will be better). For actual utilization of this energy with conentional electrical devices, an energy storage, control and conversion appliances are necessary, as shown in figure 8. The Wind-Thermal-Photovoltaic System (WG+ST+PV) provides at average conditions of the state around 1.5 kWh of electric energy and 10 kWh of thermal energy. Depending on the necesities and the actual climatic conditions, any part of electric energy produced can be used for stabilization of thermal regime; on the other hand, this amount of energy is sufficient to operate one remote classroom equipped with receptor of educational satellite programs and TV-video set during 6 hours a day, which was proved experimentally in one of the rural schools of the state of Queretaro, Mexico (the classroom is in constant use since August 2002). In relation to hybrid systems with High Temperature Stage (PV+HE), the preliminary investigations were made of the performance of different solar cells (those of α-Si, CuInSe2, c-Si with p-n junction and with Schottky barrier) at high temperatures, using concentrated and non-concentrated solar radiation. For the former type of experiments, the concentrator with 2axial Sun tracking system was made (figure 10), the radiation concentration degree around 30, providing the temperature at focal plane up to 200 oC. The corresponding theory for high temperature cell performance was also developed. Figure 11 shows theoretical and experimental dependencies of parameters of the c-Si solar cells with p-n junction at the temperature interval 60 – 170 oC (the detailed description of theoretical model and experimental equipment is given in [35]). The results obtained are related to type “B” of the system discussed, and show the definite possibility of solar cell to be used at high temperatures. For the realization of all the advantages of the system (both “A” and “B” types), the new cells are necessary, and their design and construction are in process now.
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Figure 10. Sun-tracking radiation concentrator with c-Si solar cell in focal plane.
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Figure 11. Temperature dependence of c-Si solar cell parameters:theory (solid symbols) and experiment (hollow symbols).
CONCLUSION The recent development in solar photovoltaic cell technologies brought great progress to the field, but unfortunately, there are no clear prospects today to develop economic cells with efficiency higher than 20 %. Hybrid systems of different kinds promise much higher efficiency of utilization of solar (renewable) energy, which could be in total around 40 – 60 %, with a reasonable cost and some other advantages. However, hybrid systems, as a rule, are not efficiently working when made by a mechanical combination of the existing elemental devices. Some of them, if not all, have to be designed and constructed especially for a particlular hybrid system. Thus, a photovoltaic panel for applications in a PV/Thermal system has to be designed in an optimized way to provide a good thermal exchange with the heat collector, which needs specific materials and arrangements. The ideal for hybrid systems would be a photovoltaic panel transparent for part of the solar spectrum (infrared one) which is not absorbed by its semiconductor material, and having a good heat exchange with the heat collector. On the other hand, the solar heat collector could be made transparent in the visible region, to be able to use with bifacial panels and not affect greatly their performance. The experimental systems designed, built and studied confirm the conclusions made.
REFERENCES [1] [2] [3] [4]
Karam, N.H.; King, R.R., et al., Sol. En.Mat. Sol. Cells., 2001, vol. 66, pp. 453-466. Henry, C.H., J. Appl. Phys., 1980, vol. 51, pp. 4494-4500. Yamaguchi, M., Sol. En. Mat. Sol. Cells., 2003, vol. 75, pp. 261-269. Tobias, I; Luque, A., Progr. in Photovolt., 2002, vol. 10, pp. 323-329.
218 [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26]
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Yu.V. Vorobiev, J. Gonzalez-Hernandez, P. Gorley et al. Andreev, V.M.; Grilikhes, V.A., et al., Sol. En. Mat. Sol. Cells., 2004, vol. 84, pp. 3-17. Imenes, A.G.; Mills, D.R., Sol. En.Mat. Sol. Cells., 2004, vol.84, pp. 19-69. Luque, A.; Marti, A., Phys. Rev. Lett., 1997, vol. 78, pp. 5014-5017. Luque, A.; Marti, A., Progr. in Photovolt., 2001, vol. 9, pp. 73-86. Kern Jr., E.C.; Russel, M.C., Proc. 13 ISES PVSC, Washington D.C., USA, 1978, pp. 1153-1157. Huerta, J., et al., Proc. ANES/ISES, Mexico, 2000, pp. 529-533. Raghuraman, P., J. Sol. En. Eng., 1981, vol. 103, pp. 291-298. Takashima T., et al., Sol. En., 1994, vol.52, p.241-245. Florschuetz, L.W., Sol. En., 1979, vol. 22, pp. 361-366. Zondag, H.A., et al., Sol. En., 2002, vol. 72, pp. 113-128. Rowe, D.M., Ed.;CRC Handbook of Thermoelectrics, CRC Press, London, N.Y., 1995, 702 p. Anatychuk, L. I. Thermoelements and Thermoelectric Devices (Handbook), Naukova Dumka, Kiev, 1979, 768 p. Bulat, L.P., et al., Thermoelectric Cooling. St. Petersburg, SPbSURandFE, 2002, 47 p. L.P.Bulat, L.P., Kholodilnaya Tekhnika, 2004, No. 8, 7 p. Fleurial, J.-P., et al., Proc. of 23rd International Conference on Thermoelectrics, Book of Abstracts, Adelaide, Australia, 2004, p.70. Venkatasubramantan, R., et al., Nature, 2001, vol. 413, pp. 597-608. Venkatasubramantan, R., US Patent No.: 6,300,150,B1. Oct. 9, 2001. Harman, T.C., et al., Science, 2002 September 27; 297: 2229. Ghoshal, U., Ghoshal, S., McDowell, C., Shi, L., Appl. Phys. Letters, 2002, vol.80. pp. 3006-3008. Ghoshal, U., Proc. XXI International Conf. on Thermoelectrics, 2002. IEEE, p.540. Hishinuma Y., Geballe, T.H., Moyzhes, B.Y, Kenny T.W., Appl. Phys. Lett., 2001, vol.78, p.2572. Tavkhelidze, A., Skhiladze, G., Bibilashvili, A., Tsakadze, L., Jangadze, L., Taliashvili, Z., Cox, I., Berishvili, Z., Proc. XXI International Conf. on Thermoelectrics, 2002. IEEE. P.435. Caillat, T. et al., Proc. XX International Conf. on Thermoelectrics, 2001. IEEE, p.282. Zakharchenko, R., et al., Sol. En. Mater. Sol. Cells., 2004, vol. 82, pp. 253-261. Organ, A.J., The Regenerator and the Stirling Engine, Harvill Press, 1997, pp. 35-88. Sze, S.M., Physics of Semiconductor Devices, 2nd ed., John Wiley and Sons, N.Y., 1981, pp. 830-835. Algora, C., et al., IEEE Trans. Electron Devices, 2001, vol. 48, pp. 840-844. Nann, S.; Emery, K., Sol. En.Mat. Sol. Cells, 1992, vol. 27, pp. 189-216. Luque, A., et al., Sol. Cells, 1980, vol. 2. pp. 151-166. Luque, A., et al., Sol. Cells, 1984-85, vol. 13, pp. 277-292. Meneses-Rodriguez, D., et al., Sol. En. J., 2005, vol. 78, pp. 243-250.
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 219-229
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 6
DYE-SENSITIZED NANO SNO2:TIO2 SOLAR CELLS* Weon-Pil Tai Fine Chemical Industry Support Center, Ulsan Industry Promotion Techno Park; 2F Small and Medium Business Center, 758-2, Yeonamdong, Buggu, Ulsan 683-804, South Korea
ABSTRACT The nanostructured SnO2:TiO2 bilayered and composite solar cells sensitized by eosin Y and RuL2(NCS)2 dyes are prepared and the photoelectrochemical properties of the cells are investigated. The semiconductor films possess the grain size of nanometer order and have nanoporous structure. The bilayered cell shows higher IPCE (incident photon- to-current conversion efficiency) value than the single and composite cells. A maximum IPCE value of 88.1% was reached at 540 nm wavelength in the bilayered cell with 3.5μm-thick SnO2 and 7μm-thick TiO2 sensitized by RuL2(NCS)2 dye. The higher IPCE value in the bilayered cell is attributed to the promotion of the charge separation by fast electron transfer process from the excited dye to SnO2 in the SnO2/TiO2/dye system with different conduction band edge energy positions.
1. INTRODUCTION Nanostructured materials are, recently, an intensive research area with many potential applications. Dye-sensitized nanostructured TiO2 solar cells having a wide-band gap offer an alternative method for the fabrication of low-cost solar cells [1-5]. The interaction of carboxylic acid groups with a porous TiO2 film surface results in effective monolayer adsorption of the dye molecules onto porous TiO2 films. A monolayer of dye adsorbed onto the porous TiO2 surface is sufficient to collect a large part of the solar spectrum. Such solar cells possess the large surface area and high porosity of the nanostructured TiO2 film, *
A version of this chapter was also published in Leading Edge Research in Solar Energy edited by P. N. Rivers published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research.
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enhancing the light-harvesting capability of the dye adsorbed onto the film surface. The chemical and physical processes involved in the operation of these solar cells take place in a two-phase system consisting of a nanostructured porous TiO2 film interpenetrated by a I3-/Iredox electrolyte. Charge injection from the photoexcited dye and regeneration of the dye by electron transfer from I- lead to transport of electrons in the TiO2 as well as transport of I3and I- ions in the electrolyte. Electron transfer from I- to the oxidized dye and regeneration from I3- to I- at the counter electrode link the two transport processes. The nanostructured-bilayered (coupled) solar cells have shown an improved IPCE (incident photon-to-current conversion efficiency) value compared with single layered solar cells [6-9]. The charge recombination between the electrons injected in the conduction band of the semiconductor and the oxidized sensitizer could be suppressed by using two semiconductors with different energy levels, i.e., different conduction band edge energy positions. A better charge separation in the bilayered film electrode can be achieved by using two different oxide semiconductors e.g. SnO2 and TiO2 having different energy levels. This suppresses the charge recombination in the bilayered film. Namely, the electrons injected from the excited RuL2(NCS)2 dye molecule (E°= -0.66V vs NHE, in acetonitrile) [10] into the conduction band of TiO2 (ECB = -0.5V vs NHE) [11] could be transferred quickly into the lower lying conduction band of SnO2 (ECB = 0V vs NHE) [7]. Furthermore, Tennakone et al. [12] reported the suppression of charge recombination for the composite of SnO2 with a nanocrystalline size of 15 nm and ZnO with microcrystalline size of 2μm. Kiesewetter et al. [13] also tried to improve the photocurrent by embedding the large microcrystalline WSe2 and MoS2 (absorbers) into the nanocrystalline TiO2 without dye. In this paper, nanostructured SnO2:TiO2 thin films were prepared by the sol-gel process and the photoelectrochemical properties of SnO2/TiO2 bilayered solar cells sensitized by eosin Y and RuL2(NCS)2 dyes were investigated. The photoelectrochemical properties of RuL2(NCS)2 dye-sensitized TiO2-SnO2 composite cells were also investigated for the direct comparison in IPCE.
2. EXPERIMENTAL DETAILS 2.1. Synthesis TiO2 colloidal solution was prepared by the following procedure. 150 ml of Titanium tetra isopropoxide (Ti(C3H7O)4, Wako pure chemical, 95%) was rapidly added to 270 ml of deionized water. The resulting precipitate was washed with deionized water. The precipitate cake was transferred into a well-sealed autoclave vessel containing 0.5 M tetramethylammonium hydroxide ((CH3)4NOH), Aldrich). Peptization occurred after heating at 1100 for 6 h. The suspension which resulted from peptization was treated hydrothermally in the autoclave at 1900 for 6 h. SnO2 colloidal solution was prepared by the following procedure. Tin chloride pentahydrate (SnCl4·5H2O, Wako pure chemical) was dissolved in ethanol (0.4 M). The solution was well stirred and then refluxed for 3 h. An 5.5 M aqueous ammonia solution (Wako pure chemical, 25~27.9%) was added dropwise to a refluxed solution and the resulting
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precipitate was washed thoroughly with deionized water to remove NH4Cl. Finally, SnO2 colloidal solution was prepared by adding deionized water.
2.2. Preparation of ITO/SnO2:TiO2 Electrodes The colloidal TiO2 dispersions were prepared as follows. TiO2 colloidal solution of 6 g and commercial TiO2 (Nippon Aerosil, P25) of 0.08 g was ground in a mortar. A detergent (Triton X-100) of 20μL was added to facilitate the spreading of the colloid on the substrate. Polyethylene glycol (PEG 20000) of 0.35 g was added to facilitate the adsorption of dye molecules onto porous film. Finally, the colloid was diluted by the addition of ethanol (3 mL). The colloidal SnO2 dispersions were prepared by the same method as the colloidal TiO2 dispersions except the addition of commercial TiO2. The TiO2-SnO2 composite solution, a viscous dispersion of SnO2 and TiO2 mixed nanocrystallites, was prepared by adding SnO2 colloidal solution into TiO2 colloidal solution with different ratios. There were two types of electrodes, SnO2/TiO2 (a upper TiO2 layer on a lower SnO2 layer) bilayered electrode and TiO2-SnO2 composite electrode. In the bilayered electrode, nanostructured SnO2 film was prepared first by spreading a viscous dispersion of nanocrystalline SnO2 onto a conducting ITO (indium tin oxide)-coated glass substrate(14 ohm/□, Sanyo vacuum industries), and then coated by spreading a viscous dispersion of nanocrystalline TiO2 onto the nanostructured SnO2 film. In the composite electrode, nanostructured TiO2-SnO2 composite film was prepared by spreading a viscous composite solution onto a conducting ITO-coated glass. After air drying, the film electrodes were fired at 500°C for 30 min in air using an electric furnace, at an increasing rate of 50/min. The resulting film thickness was about 7~14.5μm. A dye molecule, cis-di(thiocyanato)-N,N'-bis(2,2'-bipyridyl-4,4'-dicarboxylic acid)ruthenium(II) dihydrate, referred to as a RuL2(NCS)2 dye, was synthesized in accordance with published procedures [2, 14]. IR spectra exhibited 2117, 1720, 1612, 1548, 1408/cm, similar to the infrared peaks of commercial RuL2(NCS)2 dye (Solaronix SA, Ruthenium 535). Also, commercial RuL2(NCS)2 (Ruthenium 535) and eosin Y dyes (Aldrich) were used. The adsorption of the RuL2(NCS)2 dye was done immediately after high-temperature firing in order to avoid rehydration of the porous thin films. The ITO/SnO2:TiO2 film electrodes were dipped into a 3 ×10-4 M RuL2(NCS)2 dye solution while it was 800 and the immersed electrode was refluxed at 800 for 1 h. After the adsorption treatment, the film electrode was dried by a stream of argon. The film electrodes were also dipped into a 3.2 ×104 M ethanol solution of eosin Y dye and the immersed electrode was refluxed at 800 for 30min.
2.3. Photoelectrochemical Measurements and Analyses Three electrode cells were used, comprising of a platinum wire counter electrode, an Ag/AgCl reference electrode, and a RuL2(NCS)2 dye-adsorbed nanocrystalline SnO2:TiO2 working electrode. A solution of 0.03 M I2 and 0.3 M LiI in acetonitrile was used as an electrolyte. A potentiostat (Toho Technical Research, 2020) and a programmed function generator were used to measure the photoelectrochemical response of the solar cell. The eosin Y and RuL2(NCS)2 dyes-adsorbed semiconductor film electrode was illuminated through the
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conductive glass support using a 500W xenon lamp served as a light source. The intensity of the illumination source was measured using a power meter. UV-visible absorption spectra of the eosin Y and RuL2(NCS)2 dyes onto semiconductor film were recorded by using spectrophotometer (V-550, Jasco) before and after the adsorption of the dye by refluxing at 800 for 30 min or 1 h. Surface area was measured by the nitrogen adsorption method using a Autosorb-1 (Qunta Chrome). The microstructure of the films was observed by scanning electron microscope (SEM, Hitachi S-4200). The thickness of the films was evaluated from SEM images of the cross section of the films.
3. RESULTS AND DISCUSSION 3.1. Characterization of Film Electrodes Figure 1 shows the SEM micrographs of the surfaces in the SnO2/TiO2 bilayered film and TiO2-5wt% SnO2 composite film. The films possess nanocrystalline and nanoporous structure, which is composed of interconnected nano-sized grains. It indicates that such nanostructured films can adsorb easily the dyes. The P25 TiO2 with larger nano-sized grain in the SnO2:TiO2 films was added 5 wt% to TiO2 colloidal solution to supply the photon scattering center of light. The phases formed in the SnO2/TiO2 bilayered films were anatase TiO2, containing a small amount of SnO2. The phases in the TiO2-SnO2 composite films were anatase TiO2 and SnO2. Further, no second phases formed in the TiO2:SnO2 films except TiO2 and SnO2.
Figure 1. SEM micrographs for samples : (a) SnO2/TiO2 bilayered film and (b) TiO2-5wt% SnO2 composite film.
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Figure 2 shows the absorption spectra of SnO2/TiO2 bilayered film electrodes. The film electrode without the dye absorbs UV below 400 nm (figure 2(a)). The ITO/3.5μm SnO2/7μm TiO2 bilayered electrode adsorbed with an eosin Y exhibits absorption over the wide range including the visible light (figure 2(b)). The absorption peak of eosin Y dye on SnO2/TiO2 (525 nm) was shifted towards blue region compared to that of the dye in the ethanol (534nm, figure 2(c)). Redmond et al. [15] reported that the blue shift in the ZnO adsorbed with a Ru dye was due to a change in the dielectric constant at the semiconductor electrode-electrolyte solution interface, dye molecules adsorbed as aggregates or oligomers, and dye chemisorption onto specific sites of the ZnO surface. In this study, the blue shift is attributed to chemisorption of eosin Y dye onto specific sites of the nanoporous SnO2/TiO2 film surface.
Figure 2. Absorption spectra of (a) ITO/SnO2/TiO2 bilayered electrode, (b) ITO/3.5μm SnO2/7μm TiO2/eosin Y bilayered electrode, and (c) eosin Y in ethanol.
Figure 3 shows the UV-visible absorption spectra of the SnO2/TiO2 bilayered film electrodes sensitized by RuL2(NCS)2 dye. The film electrode without the dye absorbs UV below 400 nm (figure 3(a)). The ITO/SnO2/TiO2/RuL2(NCS)2 electrodes exhibit absorption over the wide range including the visible light (figure 3(b and c)). It insures efficient photon capture by a RuL2(NCS)2 dye in the visible spectral range. The thicker TiO2 film on the SnO2 film (figure 3(c)) results in higher absorption peak. Figure 3(d) shows the absorption spectrum of the 3.5μm SnO2/7μm TiO2 bilayered electrode by a commercial RuL2(NCS)2 dye. It has wider absorption range in the visible range than homemade RuL2(NCS)2 dyesensitized SnO2/TiO2 bilayered electrode. The absorption spectra of the TiO2-SnO2 composite film electrodes are shown in figure 4. The film electrode without the dye exhibits absorption of UV light below 400 nm (figure 4(a)). The increase of absorption near 700 nm wavelength is due to the transparent and porous TiO2-SnO2 composite films even though the thickness of the film is about 10μm. The ITO/TiO2-SnO2/RuL2(NCS)2 electrodes exhibit absorption in the wide range including the visible light range (figure 4(b and c)). The composite film electrode with 95 wt% TiO2 content, 5 wt% SnO2 addition (figure 4(c)) exhibits higher absorption peak than the film electrode with 80 wt% TiO2 content, 20 wt% SnO2 addition (figure 4(b)). The intensity of absorption peak for the composite film electrode with 60 wt% TiO2 content is similar to that for the film electrode with 80 wt% TiO2 content.
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Figure 3. Absorption spectra of (a) ITO/3.5μm SnO2/7μm TiO2, (b) ITO/3.5μm SnO2/3.5μm TiO2/RuL2(NCS)2, (c) ITO/3.5μm SnO2/7μm TiO2/RuL2 (NCS)2, and (d) ITO/3.5μm SnO2/7μm TiO2/commercial RuL2(NCS)2 bilayered electrodes.
3.2. Photoelectrochemical Properties of Dye-Sensitized Solar Cells Figure 5 shows the incident monochromatic photon-to-current conversion efficiency (IPCE) of ITO/SnO2/TiO2/eosin Y bilayered cells as function of excitation wavelength and TiO2 film thickness at a constant SnO2 film thickness. Figure 5(a) exhibits SnO2 of 3.5 μm and TiO2 of 3.5 μm in film thickness. Figure 5(b) exhibits SnO2 of 3.5 μm and TiO2 of 7 μm in film thickness. Moreover, figure 5(c) shows SnO2 of 3.5 μm and TiO2 of 11 μm. The IPCE is defined as the number of electrons generated by light in the external circuit divided by the number of incident photons, as follows:
Figure 4. Absorption spectra of (a) ITO/TiO2-20wt% SnO2, (b) ITO/TiO2-20wt% SnO2 /RuL2(NCS)2, and (c) ITO/TiO2-5wt% SnO2/RuL2(NCS)2 composite electrodes.
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Figure 5. Photocurrent action spectra of (a) ITO/3.5μm SnO2/3.5μm TiO2/eosin Y, (b) ITO/3.5μm SnO2/7μm TiO2/eosin Y, and (c) ITO/3.5μm SnO2/11μm TiO2/eosin Y bilayered cells.
The photocurrent density was obtained at short circuit where the SnO2/TiO2 bilayered film electrode is poised to a potential of 0.2 V measured against Ag/AgCl. The electrolyte used was a solution of 0.03 M I2 and 0.3 M LiI in acetonitrile. The SnO2/TiO2 bilayered cell was illuminated from the back face through the ITO glass support. The maximum IPCE value attains 63% at 525 nm wavelength in the 3.5 μm-thick SnO2 and 7 μm-thick TiO2 bilayered cell sensitized by an eosin Y dye, as shown in figure 5(b). The IPCE decreases with thicker and thinner TiO2 thickness at a constant SnO2 thickness. Hagfeldt et al. [16] explained an optimal colloidal film thickness. The quantum efficiency for back-face illumination exhibited a maximum value in the cell with 4μm-thick TiO2 film. The optimum film thickness in the bilayered cell sensitized by a mercurochrome dye was SnO2 of 3.5μm and TiO2 of 6 7μm [17]. RuL2(NCS)2 dye-sensitized Nb2O5 single cell showed the highest photocurrent in a 8μm thickness [10]. At enough large film thickness, the hole transfer to the electrolyte is limited, due to too slow diffusion of the hole acceptor to the inner part of the film. Figure 6 shows the IPCE of ITO/SnO2/TiO2/RuL2(NCS)2 bilayered cell as a function of wavelength. Figure 6(a) shows the IPCE of the bilayered cell with SnO2 of 3.5μm and TiO2 of 3.5 μm in the thickness of the film. Figure 6(b) exhibits SnO2 of 3.5μm and TiO2 of 7μm in the film thickness. The RuL2(NCS)2 dye of figure 6(a) and (b) was synthesized by the author. figure 6(c) shows the IPCE of the SnO2/TiO2 bilayered cell sensitized by a commercial RuL2(NCS)2 dye with the film thickness of a 3.5μm SnO2 and 7μm TiO2. A maximum IPCE value in the 3.5μm-thick SnO2 and 7μm-thick TiO2 bilayered cell sensitized by a commercial RuL2(NCS)2 dye attained 88.1% at 540 nm wavelength. The difference of the IPCE values in the cells sensitized by homemade and commercial RuL2(NCS)2 dyes in figure 6(b) and (c) seems to be due to the dye purification. The increase of TiO2 film thickness up to 7μm at a constant SnO2 thickness resulted in an increase in the value of IPCE. The shape of the photocurrent action spectra was similar to that of the absorption spectra. The SnO2 film exhibits higher transparency and conductivity than the TiO2 film, which results in a decreased electron-loss at an interface between the SnO2 and ITO layers in the ITO/SnO2/TiO2 bilayered cell. Lagemaat et al. [18] reported that the electrical potential drop at a transparent conducting oxide, TCO/TiO2 interface, occurred over a narrow region.
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The IPCEs of ITO/TiO2-SnO2/RuL2(NCS)2 composite cells as a function of wavelength are shown in figure 7. The IPCE value of TiO2-5 wt% SnO2 composite cell is higher than those of TiO2-20 wt% SnO2 and TiO2-40 wt% SnO2 composite cells in the visible range. It means that RuL2(NCS)2 dye molecules adsorb well onto the TiO2 particle surface of the composite film with higher TiO2 content, and charge recombination occurs in the composite cell of higher SnO2 content. The photocurrent flow in the TiO2-SnO2 composite cell was unstable at the cell with higher SnO2 content. The IPCE below 450 nm exhibits relatively high value due to weak photon flux despite the low photocurrent. The SnO2/TiO2 bilayered system shows higher IPCE values than the TiO2-SnO2 composite system in using two oxide semiconductors with different energy levels, different conduction band edge energy positions. In the composite system, the charge recombination between the electron injected into the conduction band of the semiconductor and the oxidized sensitizer is not suppressed because the electrons injected from the excited RuL2(NCS)2 dye (E°= -0.66V vs NHE, in acetonitrile) [10] into the conduction band of SnO2 (ECB = 0V vs NHE) [7] can not migrate to the higher lying conduction band of TiO2 (ECB = -0.5,V vs NHE) [11]. In the bilayered system, however, the charge recombination is suppressed by fast electron transfer process between two oxide semiconductors with different energy levels. In other words, the electrons injected from the excited RuL2(NCS)2 dye molecule into the conduction band of TiO2 are transferred quickly into the lower lying conduction band of SnO2. It means that a better charge separation in the SnO2/TiO2/RuL2(NCS)2 bilayered system is enhanced by fast electron transfer process from excited RuL2(NCS)2 dye to SnO2. The charge recombination is suppressed more in the bilayered system than in the composite system.
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Figure 7. Photocurrent action spectra of (a) ITO/TiO2-5wt% SnO2/RuL2(NCS)2, (b) ITO/ TiO2-20wt% SnO2/RuL2(NCS)2, and (c) ITO/TiO2-40wt% SnO2/RuL2(NCS)2 composite cells.
Nasr et al. [8] reported that the rate of back electron transfer in the SnO2/TiO2 bilayered (coupled) system decreased 3-5 times compared to those in single SnO2 and TiO2 systems, which supports an improved charge separation in the bilayered system. In another study, it has also been reported that the maximum IPCE value of 78.3% at 530 nm was attained in the single-layered TiO2 cell sensitized by RuL2(NCS)2 dye [9], which is slightly lower than that of SnO2/TiO2 bilayered cell. The SnO2 layer between ITO and TiO2 in the bilayered system provides a driving force to pull electrons away from TiO2 layer and away from holes to improve charge separation. Thus, charge separation in the SnO2/TiO2 bilayered cell resulted in lower charge recombination losses and leading to an increased IPCE. An increase in the photocurrent was achieved by reflux treatment of the semiconductor film in a dye solution [19], which was attributed to the increase in the ester-like linkage between the RuL2(NCS)2 dye and TiO2 film. It was also noted that the increase in the photocurrent is due to an increase in the ratio of ester-like linkage to chelating linkage. The binding state between the RuL2(NCS)2 dye and different types of semiconductors was studied by Sayama et al. [10] using FTIR spectroscopy. The absorption at about 2100 cm-1 is the SCN ligand stretching modes [19]. The absorption at about 1730 cm-1 is related to the carboxyl group C=O stretching band, indicating an ester-like linkage between the dye molecules and the semiconductor surface; whereas the absorption at about 1605cm-1 is assigned to the carboxyl group O-C-O asymmetrical stretching, indicating the interaction through chelating or bridging modes to the semiconductor surface [17, 20]. The RuL2(NCS)2 dye adheres to semiconductor surface through an ester linkage, and electrons are transferred mainly through the conjugated orbitals of the ester linkage and the semiconductor conduction band. The TiO2 conduction band consists of a Ti3d orbital and that of SnO2 consists of a Sn5s orbital. The orbital overlap between the conduction band and the ester linkage means that electron transfer from the RuL2(NCS)2 dye to the TiO2 d-orbital is more effective than that from the
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RuL2(NCS)2 dye to the SnO2 s-orbital due to the orbital shape [10]. The one cause of higher IPCE value in the SnO2/TiO2 bilayered cell compared with the TiO2-SnO2 composite cell is the stronger ester-like linkage between the TiO2 surface layer and the RuL2(NCS)2 dye molecules by reflux treatment of the SnO2/TiO2 film in the RuL2(NCS)2 dye solution.
4. CONCLUSION Nanostructured SnO2:TiO2 thin films were prepared by the sol-gel process and the photoelectrochemical properties of the SnO2:TiO2 bilayered and composite solar cells sensitized by eosin Y and RuL2(NCS)2 dyes were studied. The SnO2/TiO2 bilayered cell showed higher IPCE values than the TiO2-SnO2 composite cell in using two semiconductors with different energy levels. A maximum IPCE value of 88.1% was reached at 540 nm in the 3.5μm-thick SnO2 and 7μm-thick TiO2 bilayered cell, which has been attributed to a better charge separation by fast electron transfer process between the constituent layers. The dyesensitized SnO2/TiO2 bilayered cell could be utilized to fabricate a low-cost solar cell.
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O'Regan, B., and Gratzel, M. (1991) A Low-Cost, High-Efficiency Solar Cell Based on Dye-Sensitized Colloidal TiO2 Films, Nature, 353, 737-739. Nazeeruddin, M.K., Kay, A., Rodicio, I., Humphry-Baker, R., Muller, E., Liska, P., Vlachopoulos, N., and Gratzel, M. (1993) Conversion of Light to Electricity by cisX2Bis(2,2'-bipyridyl-4,4'-dicarboxylate) ruthenium(II) Charge-Transfer Sensitizers (X=Cl-, Br-, I-, CN-, and SCN-) on Nanocrystalline TiO2 Electrodes, J. Am. Chem. Soc., 115, 6382-6390. Hagfeldt, A., and Gratzel, M. (1995) Light-Induced Redox Reactions in Nanocrystalline Systems, Chem.Rev., 95, 49-68. Burnside, S.D., Brooks, K., McEvoy, A.J., and Gratzel, M. (1998) Molecular Photovoltaics and Nanocrystalline Junctions, Advanced Materials in Switzerland, Chimia. 52, 557-560. Lindstrom, H., Magnusson, E., Holmberg, A., Sodergren, S., Lindquist, S.-E., and Hagfeldt, A. (2002) A New Method for Manufacturing Nanostructured Electrodes on Glass Substrates, Solar Energy Materials and Soalr Cells, 73, 91-101. Hotchandani, S., and Kamat, P.V. (1992) Charge-Transfer Processes in Coupled Semiconductor Systems. Photochemistry and Photoelectrochemistry of the Colloidal CdS-ZnO system, J. Phys. Chem., 96, 6834-6839. Nasr, C., Hotchandani, S., Kim, W.Y., Schmehl, R.H., and Kamat, P.V. (1997) Photoelectrochemistry of Composite Semiconductor Thin Films. Photosensitization of SnO2/CdS Coupled Nanocrystallites with a Ruthenium Polypridyl Complex, J. Phys. Chem. B, 101, 7480-7487. Nasr, C., Kamat, P.V., and Hotchandani, S. (1998) Photoelectrochemistry of Composite Semiconductor Thin Films. Photosensitization of the SnO2/TiO2 Coupled System with a Ruthenium Polypyridyl Complex, J. Phys. Chem. B, 102, 10047-10056.
Dye-Sensitized Nano SnO2:TiO2 Solar Cells [9] [10]
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Tai, W.-P., Inoue, K., and Oh, J.-H. (2002) Ruthenium Dye-Sensitized SnO2/TiO2 Coupled Solar Cell, Solar Energy Materials and Soalr Cells, 71, 553-557. Sayama, K., Sugihara, H., and Arakawa, H. (1998) Photoelectrochemical Properties of a Porous Nb2O5 Electrode Sensitized by a Ruthenium Dye, Chem. Mater., 10, 38253832. Fessenden, R.W. and Kamat, P.V. (1995) Rate Constants for Charge Injection from Excited Sensitizer into SnO2, ZnO, and TiO2 Semiconductor Nanostallites, J. Phys. Chem., 99, 12902-12906. Tennakone, K., Kumara, G.R.R.A., Kottegoda, I.R.M., and Perera, V.P.S. (1999) An Efficient Dye-Sensitized Photoelectrochemical Solar Cell made from Oxides of Tin and Zinc, Chem. Commun., 15-16. Kiesewetter, T., Tomm, Y., Turrion, M., and Tributsch, H. (1999) Composite Materials for Photovoltaics: A Realistic Aim?, Solar Energy Mat. and Solar cells, 59, 309-323. Liska, P., Vlachopoulos, N., Nazeeruddin, M.K., Comte, P., and Gratzel, M. (1988) cisDiaquabis(2,2'-bipyridyl-4,4'-dicarboxylate)-ruthenium(II) Sensitizes Wide Band Gap Oxide Semiconductors Very Efficiently over a Broad Spectral Range in the Visible, J. Am. Chemi. Soc., 110, 3686-3687. Redmond, G., Fitzmaurice, D., and Graetzel, M. (1994) Visible Light Sensitization by cis-Bis(thiocyanato) bis(2,2'-bipyridyl-4,4'-dicarboxylato) Ruthenium(II) of a Transparent Nanocrystalline ZnO Film Prepared by Sol-Gel Technique, Chem. Mater., 6, 686-691. Hagfeldt, A., Bjorksten, U., and Lindquist, S.-E. (1992) Photoelectrochemical Studies of Colloidal TiO2-Films: the Charge Separation Process Studied by Means of Action Spectra un the UV Region, Solar Energy Mat. and Solar Cells, 27, 293-304. Tai, W.-P. (2001) Photoelectrochemical Properties of SnO2/TiO2 Coupled Electrode Sensitized by a Mercurochrome Dye, Materials Lett., 51, 451-454. van de Lagemaat, J., Park, N.-G. and Frank, A.J. (2000) Influence of Electrical Potential Distribution, Charge Transport, and Recombination on the Photopontial and Photocurrent Conversion Efficiency of Dye-Sensitized Nanocrystalline TiO2 Solar Cells: A Study by Electrical Impedance and Optical Modulation Techniques, J. Phys. Chem. B 104, 2044-2052. Murakoshi, K., Kano, G., Wada, Y., Yanagida, S., Miyazaki, H., Matsumoto, M., and Murasawa, S. (1995) Importance of Binding States between Photosensitizing Molecules and the TiO2 Surface for Efficiency in a Dye-Sensitized Solar Cell, J. Electroanal. Chem., 396, 27-34. Meyer, T.J., Meyer, G.J., Pfenning, B.W., Schoonover, J.R. Timpson, C.J., Wall, J.F., Kobusch, C., Chen, X., Peek, B.M., Wall, C.G., Ou, Erickson, B.W. and Bignozzi, C.A. Molecular-Level Electron Transfer and Excited State Assemblies on Surfaces of Metal Oxides and Glass, Inorg. Chem., 33, 3952.
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 231-244
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 7
STRATEGIES FOR REDUCING CARBON DIOXIDE EMISSIONS - THE CASE OF BOTSWANA RURAL COMMUNITIES* C. Ketlogetswe a and T.H. Mothudi b a
Department of Mechanical Engineering, University of Botswana, Private Bag 0061 Communication and Study Skill Unit, University of Botswana, Private Bag 0061
b
ABSTRACT The International Community’s pre-occupation with the ever-escalating dangers posed by gaseous pollutants need not be overemphasized. Suffice to mention, however that the magnitude of the dire negativity of pollutants is reflected in the numerous international charters that were promulgated with a common objective to sensitise the world about the need to move toward setting up minimum permissible levels of emission for activities whose execution result in atmospheric pollution. In addition, authorities have also gone so far as to offer incentives / motivation as a means of assuaging nations towards implementing various strategies for minimising atmospheric pollutions. This paper explicates efforts taken by. The government of Botswana in an effort to strive for compliance with international protocols and standards to safeguard against deterioration of the planet. Focus will specifically be paid to examining any concrete measures taken with the view to curb the negative impacts of carbon dioxide gas. The suitability and sustenance or, otherwise, of government projects envisaged for reducing carbon dioxide emission levels generated during the combustion of fuelwood and other related energy sources used by rural communities in Botswana will also be discussed.
*
A version of this chapter was also published in Leading Edge Research in Solar Energy edited by P. N. Rivers published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research.
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1. INTRODUCTION The adverse impact of climate change is a matter of grave concern, the world-over. As a result, increased pressure from the United Nations Framework Convention on Climate Change (UN FCCC) to reduce the world’s energy-related greenhouse emission levels particularly carbon dioxide gas is expected to stimulate rapid development of renewable energy facilities in many countries. The authors also believe that pressure to preserve environmental purity is poised to exert immense challenges to energy resources conservation strategies in many developing countries, Botswana included. As testimony to the global nature of this concern, the UK government predicts that by 2010, 10% of the country’s electricity sales should be generated from resources which are eligible for the renewable obligation including waste-to-energy. This figure compares favourably with the entire European Community’s target of 15% by the same period (http:defra March 2003). The Kyoto Protocol to the UN FCCC requires that both the Organisation for Economic Cooperation and Development (OECD) and Non-OECD countries reduce the emissions of greenhouse gas especially carbon dioxide to permissible minimums (The Kyoto Protocol and Beyond (1999) and Porteous (2001)). The emphasis on carbon dioxide is driven by the fact that combustion of hydrocarbons particularly fossil fuels, which are a major global energy resource, has hugely increased the total load of carbon dioxide in the atmosphere. The longterm consequences of this includes alteration of global climate as greenhouse gases trap heat at the earth’s surface. The Kyoto Protocol is designed to ensure that communities across the world begin a long-term shift to a future with lower emissions and more efficient energy sources. The protocol also grants countries opportunities to work out their modalities for reducing emissions. However, it specifies limits for the carbon dioxide emission levels produced by a country or a group of countries. As a result, the target reductions vary from nation to nation. For example, the Protocol requires developed nations to achieve a combined minimum reduction of 5% of the combined collective emissions from the 1990 baseline levels. There are several techniques and measures used world-over to address the problem posed by the release of carbon dioxide gas into the atmosphere. One such technique is geological storage, which is rapidly receiving widespread recognition among countries of the world. This method employs three storage options, namely gas and oil reservoirs which are no longer productive, coal seams which cannot be further mined and deep aquifers. Available evidence indicates that when carbon dioxide is injected in gas and oil reservoirs which are nearing depletion, the injection process enhances the production process by enabling the natural gas trapped in these structures to be released. As a result, the process considerably reduces the capture and storage costs of carbon dioxide. This factor leads to the conclusion that there will be a corresponding increase in the economic case for geological storage of carbon dioxide gas. Research on this approach is on-going. Some of the countries involved in the existing research efforts are those that subscribe to a more technology-oriented approach in their national policy on climate changes. These countries include, the United States, Canada, Japan, Norway, the Netherlands, Australia and some European Union Member States. The clamour for low-emissions, more efficient energy resources and the use of the geological techniques is a step towards sustainable development.
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This paper, as mentioned earlier, discusses efforts taken by the government of Botswana in a bid to comply with international protocols and requirements to reduce carbon dioxide emission levels to be emitted into the atmosphere. Most importantly this paper seeks to examine the present strategies designed for rural communities with the view to consider their feasibility and sustainability as described in sections 3, 4 and 5. Prior to engaging into a comprehensive review of the proposed strategies for rural communities, it is pertinent to consider the uses to which energy resources are placed in Botswana particularly in the context of rural communities. A detailed exploration of this matter is undertaken in Section 2.
2. RURAL COMMUNITIES AND HOUSEHOLDS EXPENDITURE ON ENERGY RESOURCES Rural communities account for more than 70% of Botswana’s population (Government of Botswana Statistics 2001). The majority of these communities are heavily dependent on traditional agriculture for their livelihood. This situation appears to be a common feature of most developing countries particularly those situated in the Southern African Development Countries (SADC) region. For example, estimates indicate that 67% of Namibia’s population live in a rural area, mostly in the northern regions of the country where rainfall is higher (Government of Namibian Statistics 1996). In Botswana, estimates indicate that there are approximately 160 000 rural household populations with an average monthly income below Botswana Pula (BWP) 530 per month, which is equivalent to US$ 106 (Botswana government statistics 2001). The income generated by these communities is used to cover a household’s expenditure including energy supply which is of particular interest to the present study. A study by the Japan International Cooperation Agency (Japan International Cooperation Agency report, 2003) on the households expenditure by rural communities in Botswana found that approximately 85% of homeowners in rural communities spend up to a maximum of BPW 50 (US$ 10) per mouth on energy provision (Japan International Cooperation Agency report, 2003). Figure 1 illustrates the overall expenditure levels on energy resources for the rural communities in Botswana. The data in figure 1 shows that less than 10% of the rural communities in Botswana spend approximately BPW 100 per month on energy resources, which is equivalent to US$ 20 per month. The percentage falls below 3% in respect of those house owners spending BPW 150 or more per month on energy resources. Overall, the data suggests that affordability window for energy resources for the majority of rural communities in Botswana range from PBW 0 to 50 (US$ 10). On the basis of the above observations, it is obvious that an investigation on sustainability of the proposed projects for rural dwellers aimed at reducing energy-related carbon dioxide emission levels generated by the rural community in Botswana is of considerable practical interest. It should be explained that the data presented in figure 1 was collected from nine rural villages, located in various parts of the country. Consequently, therefore, it is assumed that such data reflects the practical situation found in the rest of the rural communities in Botswana.
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Source: Japanese International Cooperation Agency Report (2003). Figure 1. Typical rural community expenditure levels on energy resources in Botswana.
Regarding climate changes, Botswana contributes approximately 7% of Africa’s total greenhouse gas emissions while the entire continent of Africa is estimated to contribute 5% of the global total emission (Government of Botswana framework on climate change report 2001). Although this study places more emphasis on proposed strategies for reducing energyrelated carbon dioxide emission levels generated by rural community in Botswana, it is pertinent also to highlight energy supply and demand in various sectors. This is considered a vital means of linking the supply and demand to the generation of gaseous emissions. In line with this understanding, figures 2 (a) and (b) show net energy supply and demand in the country on sectoral basis. The results in figures 2 (a) and (b) should be viewed in parallel. The data in figure 2 (a) shows that fuelwood is the second major source of energy supply after petroleum. Regarding demand, the data in figure 2 (b) shows that the residential sector is the major energy consumer in Botswana. The high rate of fuelwood supply as shown in figure 2 (a) indicates that fuelwood is the major energy source for rural communities in Botswana and perhaps the least expensive. In many cases, it is harvested at no monetary cost as a common property. Figure 3 shows an increased supply with time of two major energy sources used by rural communities in Botswana. With respect to the reduction of energy-related gaseous emission levels generated by rural communities, the data in figures 2 and 3 suggest that emphasis ought to be placed on the reduction in consumption rate of fuelwood which is mainly used for cooking in open fire, space and water heating. It should be noted that Botswana with ‘estimated population of 1.7 million recorded woodfuel consumption of about 1.5 million tonnes in 1999’ (http:worldenergy;statistical Bulletin, 2001). Based on this observation, and particularly on the results in figure 3, it can be assumed that the carbon dioxide emission levels from the combustion of woodfuel are relatively high.
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Since the proposed strategies for reducing energy-related carbon dioxide gas generated by rural communities do not include reduction in the use of fuelwood, the utilisation of this approach is likely to conjure several questions especially those relating to the techniques for using proposed strategies and their ability to significantly reduce gaseous emissions generated by these communities. Section 3 briefly discusses some of the government strategies aimed at addressing the problem of climate change.
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1983
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Source: Government of Botswana (2001) Report No: TB 10/1/9/99/2000. Figure 3. Uses of various energy sources in a typical rural household
3. CENTRALISED PV BATTERY CHARGING STATION IN BOTSWANA There is scope for action to reduce energy-related carbon dioxide emission levels generated by the rural communities in Botswana. This opportunity is exemplified by the introduction of a number of solar energy projects including centralised a photovoltaic battery charging station at Lorolwana village, hitherto, the country’s sole centralised photovoltaic battery station. The village is located approximately 200 km South of Gaborone City and comprises of a population size and households number of 952 and 180 respectively (Government of Botswana statistics 2001). The facility was constructed in 2003, through funding by the Global Environmental Facility (Energy Affairs Division annual report 2004). The main goals of the project was to provide lighting and also to operate radios. Although adding more solar panels could easily increase the size of such system, the present design is such that its capacity is approximately 1.1 kWp. Figure 4 presents a photograph of the facility. The batteries demonstrated in figure 4 have capacities ranging from 25 to 50Ah and are supplied with an electronic unit to prevent undercharging which is one of the most common causes of plate buckling, due to the plate strain caused by the lead sulphate. In addition to two 12V DC sockets designed for lighting, these batteries incorporate 9V DC sockets for appliances such as radio and black and white television sets.
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Figure 4. Exterior and interior views of the battery charging station at Lorolwana village.
In order to assess the socio-economic merits of the facility shown in figure 4, 42 households were reviewed as part of a pilot study of the technology. The total number of households reviewed as part of the pilot project was determined taking into consideration that the station was going to be supplied with 84 batteries, and also that each household was to be allocated two batteries to ensure availability of a permanent standby battery whilst another is being used. Further, the same was promised on the understanding that in the event socioeconomic factors indicated possible sustenance of the project, the facility will be expanded to provide the entire community of Lorolwana. Furthermore, it was envisaged that upon confirmation of the sustenance of the project, it will ultimately be handed over to the community to take full charge of its running. The overall aim was that the concept could be replicated in other parts of the country and the data collected during the implementation phase would serve as the basis for formulating policies on renewable energy in Botswana particularly among rural communities. Although there are some indications for the successful introduction and utilisation of solar technologies in rural communities, the present study revealed that the facility demonstrated in figure 4 is currently dysfunctional. To pave way for an ensuing discussion, it is pertinent to point out that participants were expected to pay for service charges which included fixed and battery charging coupons which expire during the last day of each month. The overall charge was BPW pula 20 which is equivalent to US$ 4. Based on the results in figure 1, it is clear that the overall charge was within the affordable window as discussed in Section 2. Notwithstanding these conclusions, however, evidence from interviews with facility operator at community level revealed that majority of the selected house owners defaulted from paying the fixed charges and burying battery-charging coupons at the introductory stage of the project alleging high service costs and inflexibility in the payment method. It is perhaps; appropriate to observe that charging coupons are an unsuitable method of payment for most rural communities in Botswana. This confirmation is largely predicated on the fact that majority of this population sector are generally dependent on traditional agriculture and pastoralism as discussed earlier in Section 2. Consequently, the majority of households in rural communities have three settlements, at the same time, thus lands, cattle post and village status, [further making the payment system of charging coupons with a fixed expiring date unsuitable]. This is largely due to movement of participants between these three
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places. It should also be noted that although the overall charge may appear to be within affordable range as discussed earlier in the same section, lack of economic activities in most rural communities appears to contribute to low development of such projects at rural communities levels. Second, the study had also revealed that most components particularly batteries needed rapid replacement because they were unable to store photovoltaic generated electrical energy. Lack of periodic maintenance checks on the overall facility by the management to ensure efficient functioning of equipment as well as provide further user guidance appear to have been the major causes for the present condition in which the facility is non-functioning. This point is reinforced by observations from interviewees (mainly those at management level from Energy Affairs Division) who revealed that management is seeking funds for replacing old batteries at Lorolwana centralised battery charging station (Mr. Sethare)1. Although there are no periodic maintenance checks as mentioned above, it should also be noted that Botswana Power Corporation (the only power generation and distribution company within the country) was sanctioned to monitor the design and installation of the project. It is believed that Botswana Power Corporation was bestowed this mandate because it is the sole government owned company in the specialist area. However, the contract in respect of the Lorolwana project appear not to have included periodic maintenance service, as well. On the basis that the facility demonstrated in figure 4 is currently not functioning, this invites several questions primarily relating to its viability as a mechanism for the reduction of energy-related carbon dioxide emission levels generated by rural communities in Botswana. The current situation at Lorolwana leads to the conclusion that government ambition to replicate the same project in other parts of the country aimed to strive for compliance with international protocols on global climate change is till a far cry. It should be stressed that problems relating to failure to put in place periodic maintenance checks as mentioned in the previous page is likely to bring to surface the existing public perception about poor quality of solar equipment in Botswana, further making the rapid development of solar industry in rural communities difficult. The centralised battery charging system is not the only renewable technology, which is facing resistance from the public, among the major ones being those, highlighted in Section 4, below.
4. MANYANA PHOTOVOLTAIC PILOT PROJECT This section considers the status of photovoltaic facilities at Manyana village. The project at Manyana was selected to constitute the present study on consideration of its status of being among the pioneer project that the Energy Affairs Division had embarked upon during its 8 years of existence. The establishment of Energy Affair Division was to effectively provide policy direction on issues pertaining to energy in order to promote rapid and effective development of National Electricity Grid infrastructure network particularly among in rural communities in Botswana. The findings from the present study would be used to make a case as to whether renewable technologies including photovoltaic techniques could significantly reduce gaseous emission levels generated by rural communities in the country. The village is located 50 km 1
D.Sethare, Renewable Energy Officer
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from Gaborone city. The Manyana photovoltaic project started in 1992. Like the project mentioned in Section 3, the major objective of this project was to assess viability and sustainability of solar energy technology as an alternative source of energy especially for rural based communities. Depending on the findings, such project was also intended to be replicated in other parts of the country. It is pertinent to explain that it is government procedure that after two to three years of project inception, the project changes from pilot to commercial status. As a direct result, the Manyana photovoltaic project went through the above-mentioned processes in 1995 under the auspices of Rural Industrial Innovation Center. At its launch, 42 households were selected to form part of the piloting phase of the technology. To facilitate the implementation processes, government offered to the 42 selected households to purchase photovoltaic systems. The loan scheme was payable over a 4 years period. These loans ranged between BWP 4000 to 20,000 (Porter 1994 in BOT/00/G41/A/1G/99), which is equivalent to between US$ 800 to 4000. The actually costs of the system is influenced by the size of the system. The present study revealed that an evaluation report on the viability and sustainability of Manyana project was carried out in 1994, thus approximately 2 years after the implementation phase (Porter 1994 in BOT/00/G41/A/1G/99). This study has found out that all 42 selected households paid off their loans and were satisfied with the performance of their systems. In contrast to the above findings by Porter (1994), the present study revealed that 83% of the selected households disconnected photovoltaic systems from their houses. From interviews with the majority of the 42 Clients, it had been alleged that the exorbitant costs for replacing components, especially the battery proved to be the main rational for disconnections. The study confirmed that the cost in question is approximately BPW 650 which is equivalent to US$ 150. Regarding the high percentage of disconnecting photovoltaic system by household at Manyana, it should be noted that the present study also confirmed the observation made in Section 3 that donor projects often offer these technologies at heavily subsidised consumer price at the period of project inception. As a direct result, most of such projects become unsustainable upon handover of control to local communities or private enterprise. On the basis of the finding by Porter (1994 in BOT/00/G41/A/1G/99), and the fact that approximately 83% of households at Manyana have disconnected the system, it becomes clear that the evaluation process within 2 years of project launch is too soon to indicate reliable data on viability and sustainability of such projects. On the basis of this evidence, as well as any others such as increasing use of fuelwood consumption as shown in figure 3, it becomes apparent that the use of renewable technologies in rural communities in Botswana does not offer significant potential to contribute to the reduction of energy-related gaseous emission levels. This observation is based on the fact that efforts at reducing energy-related carbon dioxide emission levels have placed more emphasis on the provision of alternative energy system than on intervention techniques aimed at reducing the use of woodfuel from 1.5 million tonnes as discussed in Section 2. As discussed earlier in the same section woodfuel in rural communities in Botswana is used for cooking in open fires, it should be expected that the combustion of 1.5 million tonnes of woodfuel would generate significant gaseous emissions. The major challenge facing government is to put in place new and more effective measures or augment the existing main measures aimed at reducing the use of woodfuel in rural communities. The utilisation of this approach is likely to bring closer to reality the
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Botswana government’s effort to strive for compliance with international protocols and requirement to safeguard deterioration of the planet. Prior to the discussion on the proposed approach on the reduction of combustion emission levels in rural areas in Botswana, it is pertinent to briefly discuss the status of photovoltaic mini-grid system in Motshegaletau village as described in Section 5, below. The findings would be used in the present study to make a case for whether renewable technologies including photovoltaic min-grid systems could play a major role in reducing gaseous emission levels generated by the rural communities in Botswana.
5. CURRENT STATUS OF MOTSHEGALETAU PV MINI-GRID SYSTEM Todate, Botswana possesses only one centralised photovoltaic power station, located at Motshegaletau village, approximately 50km from the nearest national electricity grid line. The village has a population of approximately 440 with approximately 88 households (Government of Botswana Statistics 2001). The system, with a capacity of 5.5kWp, started commercial operation in August 1998. The present study revealed that only 11 households have access to electricity generation from the facility. It is believed that this low access rate to electricity in Motshegaletau is explained by a number of factors including high tariffs. In fact electric tariff at Motshegaletau is 25 thebe/kWh which is the same tariff rate as charge by the Botswana Power Corporation, the only power generation and distribution company within the country. The problem of service costs as discussed in Section 3 appears to surface again here. On the basis of the above observations, and the limitation of photovoltaic electricity generation, it is believed that these could adversely affect government efforts in the battle against global warming and climate change.
6. CURRENT ACTION BY THE GOVERNMENT Preparations to replicate photovoltaic technology packages in small villages in Botswana are at advanced stages at national government and local authorities levels. The project is receiving financial assistance from the United Nation Development Programme Global Environmental Funds (UNDP-GEF). It is estimated that the project should reduce carbon dioxide emission levels by approximately 52 000 tonnes over a 20 year period (Government of Botswana report BOT/00/G41/A/1G/99). This is in the expectation that the use of photovoltaic technology will displace liquid paraffin that would otherwise have to be burned to provide light. The report estimated that on an average saving of 10 litres of liquid paraffin per month per household for selected 88 villages would be achieved. The first observation which cab be made based on the estimated saving to the value of 52 000 tonnes is that the report failed to give similar estimated value of carbon dioxide emission levels generated during the combustion of 1.5 million tonnes of woodfuel over the same period for the purpose of making comparisons. The value of 52 000 tonnes appears to an overestimation. As a subsequent discussion, it would be noted that the cost of 10 litres of paraffin in the city of Gaborone is BPW 32 which is equivalent to US$ 6.4. It can also be noted that this value is 35% more than the overall charge that residents of Lorolwana village
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(discussed in Section 2) were expected to pay as service charge. It is pertinent to mention that the price of liquid paraffin is expected to increase significantly as the location of rural communities increases relative to urban areas. On the bases of the above observations, it is of interest to conclude that the government report (Government of Botswana report BOT/00/G$1/A/1G/99) overestimated the average amount of liquid paraffin used by rural communities in Botswana. Although there is no available data on emission levels of carbon dioxide generated during the combustion of woodfuel used by rural communities to compare with the value for liquid paraffin, the authors believe that combustion of woodfuel generate relatively high gaseous emissions. On these bases, the only attractive option should be the one considered to possess potential to cause significant reduction in consumption rate of fuelwood by the rural communities in Botswana. A discussion on this matter is provided in Section 7, below.
7. PROPOSED APPROACH FOR RURAL COMMUNITIES IN BOTSWANA It is noted that between 1995 and 2002, serious educational campaign was undertaken aimed at discouraging the use of fuelwood particularly in public institutions, such as schools and prisons, and/or rehabilitation centres. The action was largely due to unsustainable harvesting of woodfuel and cutting of live trees for the purpose of drying and using them at a later stage (Energy Affairs Division annual report 2002). As a direct result, the majority of public schools particularly in cities, towns and in big villages are now using liquid petroleum gas which is supplied by local authorities. However, such opportunity is not readily available to most rural communities including areas such as Lorolwana due to lack of infrastructure. On this basis, fuelwood still remains the major source of energy for the majority of the rural communities in Botswana. The challenge to engineers and government is to provide rural communities with a facility which should reduce the consumption rate of woodfuel resource, at a cost that is relatively affordable to rural communities in Botswana. One of the facilities earmarked to promote this objective is demonstrated in figure 5. Figure 5 presents a woodstove designed by Morupule Colliery, a local coal mining company and tested by the University of Botswana. Tests conducted included the determination of thermal characteristics and the emission levels for different woodfuel species commonly used in rural communities in Botswana. The facility is in the form of two rectangular boxes (inner and outer) with detachable top cover. The inner and outer boxes are separated by an air gap of approximately 26 mm. The detachable top cover which forms part of the effective heating zone, has three circular holes of 200 mm, 150 mm and 110 mm diameter and are shown herewith as dark regions. These are closed using three circular plates consisting of recesses to ensure positive location and also to prevent the smoke from the top part of the stove from leaking. The wood stove is made of a 3 mm thick mild steel plate. The section below the fuel grate is open to the atmosphere to ensure that the combustion air enters the combustion zone under natural convection and also to facilitate the removal of ash after use. The cross sectional area of the combustion chamber is approximately 0.066 m2. The stove is internally lined with a 25 mm thick refractory material in an effort to decrease heat loss and thermal distortion of the combustion chamber particularly the grate which is made of perforated thin, mild steel plate.
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Removable top plate
Exhaust system
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Position of smoke level meter Fuel grate
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Positions of thermocouples
Figure 5. Schematic arrangement of proposed wood stove.
An experimental study was conducted to determine the thermal characteristics of the combustion process of woodfuel particles (Sickle bush) using the proposed facility as demonstrated in figure 5. The maximum charge was fixed at 1.5 Kilograms. The description of the instrumentation and operational procedures needed to determine thermal characteristics as mentioned above are described fully in Ketlogetswe (2004). For simplicity, only a sample of the results obtained in Ketlogetswe (2004) are presented in figure 6 and discussed. It should be explained that during the experimental study in Ketlogetswe (2004), an aluminium pot filled with approximately 2.5 litres of tap water was put on top of a 200 mm diameter circular plate. The time needed for the pot to boil was recorded. This was done with the knowledge that a typical rural household family may require the same quantity of water for preparing a single meal. The average boiling time was found to be 45 minutes from the start of the combustion process.
Bed fuel temperature (oC)
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800 700 600 500 400 300 200 100 0 0
5 10 15 20 25 30 35 40 45 50 55 60 65 Combustion time (min)
Figure 6. Temperature profile for the combustion process of 1.5 kg Sickle bush.
As a basis for subsequent discussions, it should be explained that the present study revealed that a typical rural household using open fire consumes approximately 4.1 tonnes/year. This compares with a value of approximately 1.6 tonnes/year required when a stove demonstrated in figure 5 is used. The difference in the rate of consumption suggests that the use of proposed wood stove by the rural communities would significantly reduce energyrelated gaseous emissions levels by approximately 61%. Based on the above observations, it is clear that one of the most attractive options with the potential to cause significant reductions in energy-related gaseous emission levels would be the use of the facility as demonstrated in figure 5. It should also be noted that the approach will address the issue of conservation of such energy resource.
8. CONCLUSION This paper has examined the status of renewable energy including woodfuel in rural communities of Botswana. In particular, the study revealed that woodfuel is the major energy resource used in the country’s rural communities. It can be concluded further that lack of network solar service centers in Botswana is the major factor hampering the development of renewable technology in the country. The implementation of the proposed project involving 88 villages does not appear to adequately address the current problem of over harvesting of woodfuel. The project under review appears to have been concerned primarily with promoting rural electrification rather than being clearly biased towards reducing energyrelated gaseous emission levels in the country. The following measures are therefore, proposed as likely to go a long way in reducing energy-related gaseous emission levels generated by rural communities in Botswana: i.
Simultaneous with encouraging the development of renewable energy-systems in rural communities, authorities should also encourage the use of a woodstove demonstrated in figure 5. Further households should be assisted financially to purchase such stoves. To stimulate public interest in the facility, demonstrations should be mounted to best highlight the advantages of using the stove under review
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ii.
C. Ketlogetswe and T.H. Mothudi as compared to open fires. This argument is based on the fact that the use of renewable energy by rural communities will not replace the use of woodfuel for cooking. To assist rapid development and also maintain public confidence on renewable technologies particularly among rural populations, it is vital for authorities to ensure that there is framework on a network of solar service centers and service technical support. Otherwise the development of the solar industry in Botswana will never prosper.
REFERENCES [1] [2] [3]
[4] [5]
[6]
[7] [8] [9] [10] [11]
[12] [13] [14]
Botswana energy statistics. 2000. Energy Affairs Division. Ministry of minerals, energy and water resources. Energy Affairs Division annual report 2004. Ministry of minerals, energy and water resources Energy Affairs Division annual report, 2002. Fuelwood depletion. Cutting down trees for firewood, leads to environmental degradation, 2002. Ministry of minerals, energy and water resources Government of Botswana Report No [TB 10/1/9/99/2000]. Rural energy needs and requirements in Botswana, 2001. Ministry of minerals, energy and water resources Government of Botswana, report [BOT/00/G41/A/1G/99], Identifying and overcoming barriers to widespread adoption of renewable energy-based rural electrification in Botswana. Ministry of minerals, energy and water resources Government of Botswana. Initial National Communication to the United Nation Framework Convention on Climate Change, 2001. Ministry of works, transport and communication. Government of Botswana. Statistical bulletin, population of towns, village and associated localities, 2001. Government of Namibia. Statistical bulletin, household income and expenditure survey. Living conditions in Namibia, Namibia planning commission, 1996. http://www.defra.gov.uk. March 2003. http:worldenergy. Statistical Bulletin , 2001 Japan International Cooperation Agency Report. Master plan study on photovoltaic rural electrification in Botswana, 2003. Ministry of minerals, energy and water resources. Ketlogetswe. C. Thermal performance of wood particles on household stove. Eastern Africa Journal of Rural Development. 2004, 20, 72 - 80. Porteous, A. Energy from waste incineration – a state of the art emission review with an emphasis on public acceptability. Journal of Applied Energy, 2001, 70, 157 – 167. The Kyoto protocol and Beyond. Action against climate change, OECD Coll, 1999, 7 – 83.
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 245-276
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 8
THE APPLYING OF COATINGS AND SURFACE THERMAL TREATMENT OF MATERIALS IN SOLAR FURNACES: THEORY AND EXPERIMENTS* V.V. Pasichny and B.A. Uryukov Institute for Problems of Material Sciences of National Academy of Sciences of Ukraine, Krzhizhanovsky str. 3, Kyiv 03142, Ukraine
ABSTRACT Solar furnaces make it possible to obtain a temperature of heating equivalent to 3500 K and above it an oxidizing air medium and without any outside contamination. They are used for investigation of materials in the Institute for Problems of Materials Science (IPMS) of theNational Academy of Science of Ukraine (NASU) for the past 40 years. The created experimental base consists of 14 different solar installations of power from 0.1 up to 10 kW. They are included in the two laboratories located in Kyiv and on the Black Sea coast. Some optical furnaces on Xe arc lamps which are the simulators of solar furnaces are added to the experimental base. In the given chapter the works of the last few years are concentrated. They are dedicated to surface heating of materials intended for obtaining coatings and improving their protective, decorative and other operational characteristics. The specialists of various fields of engineering and production are engaged in the development of these energy-intensive processes with the use of traditional energy sources. Their substitution for renewable solar radiation if it is possible can cause not only saving on utilities saving but in some cases the improvement of coatings quality due to chemical purity of the heating source. Some theoretical and experimental results of the investigation in the given field fulfilled in the IPMS are represented in the proposed work. Using an approximate integral method for solving heat conduction equation the problem is solved for the determination of the rate of thermal treatment of a surface by partial melting in a solar furnace when the sample is stationary *
A version of this chapter was also published in Leading Edge Research in Solar Energy edited by P. N. Rivers published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research.
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V.V. Pasichny and B.A. Uryukov and moves relative to the focal spot depending upon the given thickness of fused layer. Taking into account the absence hitherto of industrial (commercial) production of solar furnaces the theoretical and practical foundations have been developed in the IPMS for the creation of solar radiation concentrators on the basis of metallic antennae with plane mirror facets. As it is described in the given work the energy characteristics of these concentrators fully come up to the standards which are necessary for the realization of the greatest part of the investigated processes.
INTRODUCTION Solar energy is considered all over the world to be one of the most promising renewable sources, the intensive mastering of which can be, according to the calculations of the specialists of some countries, an alternative for traditional kinds of energy. So, the representatives of Germany at the 'Euro Sun 2004' International conference (Freiburg Germany, June 2004) have declared that in 2050 the share of renewable sources (Solar energy and wind mainly) in the total energy balance of the country will exceed 50%. Among varied ways of solar energy application the high degree of concentration of solar radiation in solar furnaces (SF) ranks high. Without going into details of the history of this orientation development which is described in many papers and monographs we shall note that the works on creating this kind of energy installation started after World War II. It was caused by intensive development of atomic power engineering, rocket and space technology and other new industries and the advent of corresponding demand in new high temperature and refractory materials and coatings. The synthesis of chemical components and also the investigation of physicochemical and technical properties and characteristics of new materials demand high temperature and specific conditions of its realization. Solar furnaces in spite of some shortcomings (dependence upon weather, time of day, season, geographical coordinates and other factors) turned out to be a very useful instrument for the investigation in the field of new materials. It is explained first of all by the opportunity to obtain high temperature of heating (up to 3800 K and above it) within an oxidizing air medium by complete absence of any contaminating impurities caused by the source of heating. Besides, practically instantaneous heat supply to an object of heating and inertialess control of heating intensity are ensured in solar furnaces. It is very important in some cases. Solar radiation is the only renewable source which permits the obtainment of high temperature of heating without intermediate conversion into electric energy. One-sided heating and strictly directed action of radiant flux can be both a shortcoming and advantage of heating in solar furnaces. In the end we shall note that the potential of solar energy depends strongly upon the location of consumer. The presence occurring everywhere in the world and even in the near-earth orbit is also and advantage of this source. The advent of plasma generators, lasers, arc Xe-lamps of high pressure and other hightemperature installations in the second half of the last-century has reduced the interest for SF because of relative high cost of optical systems, the dependence upon environment and other causes. The world energy crisis in 70-th increased the interest for renewable sources including the systems concentrating solar radiation. Though this attention concerns to a large measure the installations of energy purpose (making electric energy, natural gases conversion and others) the new SF have been created in Spain, Switzerland. Israel, Uzbekistan and other
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countries for the investigation of materials and technological processes in addition to the installations existing mainly in France, Japan, USA and republics of the former USSR. Due to the qualities described above SF are widely adopted for the synthesis and investigation of the properties of high-temperature oxide compounds (France, Japan, USA, Ukraine, Uzbekistan and other) and also for the investigation of thermal and temperature stability of materials and coatings by simulating extreme conditions of their operation (USA, France, Ukraine, Spain and other). In the last case the one-sided directional nature of radiant flux supply to the surface of the sample being heated is of great importance. This quality of solar furnaces as the other ones can be very useful for realizing technological processes of the kind of surface thermal treatment and applying the coatings of various functional purposes. But at present there are very few known works of the kind. The purpose of this work is to demonstrate the opportunities of solar furnaces utilization for obtaining glazed decorative coatings on building materials, wear resistant and protective coatings on metals and in other similar processes using the investigation carried out in the Institute for the Problems of Materials Science of National Academy of Sciences in Ukraine (IPMS NASU). Taking into account the absence of industrial production of solar furnaces and high cost of their individual manufacturing, special attention has been paid to the creation of the concentrators of solar radiation based on obsolete metallic antennae. The technology of their manufacturing has been developed in the IPMS NASU. The theoretical models and analytical methods for the calculation of optimum structure of facet mirror coating for solar concentrators have been developed. The problem has been solved for the determination of the rate of surface thermal treatment depending upon the properties of a material and the nature of power supply. Separately it is necessary to note that in that work not only the solar installations were used. Optical furnaces based on arc Xe-lamps of high pressure, were used also. By their technological potentialities they can be of completely independent importance. Like solar furnaces they possess almost all the advantages of radiant heating. Their functioning does not depend upon the Sun. But they possess their own shortcomings such as rather high expenditure of energy when efficiency is small, ozone and heat liberation to the environment, UV radiation etc. But if optical furnaces are compared with other technological equipment more or less of the same type for obtaining coatings (laser, for example) we can distinguish the following extra advantages: considerably greater area of heating when their dimensions and expenditure of energy are lesser (the question is not about the cases of the use of the most power light fluxes to obtain the hole in super hard materials, when lasers are out of competition).
1. DEVELOPMENT OF SOLAR FURNACES EXPERIMENTAL BASE ON IPMS NASU Taking into account the variety of the problems defined for the scientists in the field of materials science within high temperature region the SF constructions are also highly variable. The simplest SF is a helioinstallation with parabolic concentrator with solar radiation (dish) of direct tracking of the sun. Often they are created on the basis of military searchlights. They permit to obtain the highest heating temperatures. But they are
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characterized by the essential disadvantages. They are the following: object the of heating moves constantly in a space; heating is directed upwards which causes the fall of high temperature particles onto the mirror in the case of sample melting or destruction if certain precautions are not taken. Besides, such installations operate in the open and they require special cover being out of operation state. The installations realized by the 'concentrator + heliostat' scheme are the most widespread.
1.1. Solar and Optical Furnaces of IPMS NASU The solar energy concentration systems developed at the IPMS NASU are divided into high−temperature (2500-3500 K), medium temperature (1500-2000 K) and low-temperature (500-800 K). Table 1-1 gives the main characteristics of the solar furnaces. All high−temperature systems were developed on the basis military searchlight equipment. The systems with the medium temperature level (SGU-6 and SGU-7) used as concentrators metallic radio antennae with bonded flat glass facets. The concentrator of low-temperature equipment SGU-11 was developed on the basis of 90 plane facets. It contains hinged sections for adjusting forming the concentrator facets, a sun tracking system and other elements. SGU9 equipment contains a photoelectric battery for separate feed of tracking system drives. SGU-8 horizontal-axial equipment has two adjacent concentrators: the first one in the form of a parabolic single mirror 2 m of diameter, the second in the form of a set of spherical facets situated on the parabolic surface with an extended focal distance and a correspondingly larger focal spot (the facets of this concentrator was developed by the Moscow Prozhector plant. All installations were certificated for the thermal parameters and other characteristics. Figure 1-1 shows the principle diagrams of a 'Cascade' two-position solar furnace being completed at the IPMS NASU. The optical system of equipment consists of two parabolic mirrors of the searchlight type 2 m in diameter and two flat heliostats. The first one tracks the sun and reflects the radiant flux onto the horizontal-axial concentrator and the other one been set at an angle of 45 degrees radiates the vertical-axial mirror. This design of equipment, regardless of certain losses of energy in the heliostats, is universal and should ensure the most suitable conditions for precision experiments with heating stationary object located on a vertical or horizontal plane. Figure 1-2 shows the general view of the IPMS solar furnaces laboratory in Kyiv. The most serious disadvantage of the solar energy system is that, as is well known, their efficiency depends on weather and seasonal conditions. The developed base of solar furnace simulators – optical furnaces based on high-pressure xenon arc lamps – makes it possible not only to eliminate this shortcoming but also widen the experimental possibilities of apparatus. Table 1-2 gives the main characteristics of optical furnaces developed at the IPMS NASU.
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Table 1-1. Main characteristics of the solar furnaces Equipment SGU-1 SGU-2
Optical system (mirror dimensions) Monoparaboloid (d = 1.5 m) The same
d min, mm
q max,
N max’ kW
Tmax’K
1.2
3800
6.0
1500
1.2
3800
6.0
1500
W/cm2
SGU-3
Monoparaboloid (d = 2.0 m)
1.8
3600
8.4
1200
SGU-4
The same
1.8
3600
8.4
1200
SGU-5
The same
1.8
3600
8.4
1200
SGU-6
Metallic antennae ( d=2.8 m), facets in the form of an equilateral triangle (a=50mm)
3.5
1800
36
80
SGU-7
Metallic antenna (d= 5 m), facets are the same as in SGU-6
8.5
1800
70
80
SGU-8 (ATON-1)
Heliostat 3.5 · 3.0 m, concentrator 2.0 ·2.0 m, 64 spherical facets 0.25 ·0.25 m
1.0
2300
25
100
SGU-9
Monoparaboloid (d = 1.0 m)
0.7
2800
2.2
600
SGU-10
Monoparaboloid (d =2.0 m)
1.8
3500
8.4
1000
SGU-11
Concentrator
1.6
600
150
4
'Cascade'
Heliostat (3.0 2.75 m), auxiliary heliostat (2.0 ·3.0 m) , 2 monoparaboloid (d=2 m)
1.0
2800
8.4
560
Additional description. Application Production of amorphos film, testing of light guides Loading mechanism. Thermal and mechanical tests Supersonic jet generator. Gas dynamic and thermal tests of materials. Loading mechanism, thermomechanical, physical and physico-chemical investigations. Vacuum system. Welding, brazing, coating processes. Thermomechanical test, heat treatment of constructional materials and biological objects, water freshening. Television equipment. Thermal tests of materials, thermo-chemical transformation of solar energy. Equipment for light pulse irradiation of materials and biological object. Photoelectric accumulator for feeding tracking systems. Cutting of cloth, heat treatment. Physicochemical investigations of oxides, heat treatment. Combustion of materials, irradiation of biological objects. Thermal surface treatment of materials and technological processes.
Comments: N max - power, Tmax temperature, dmin - diameter of the focal spot, q max - irradiation in the focal spot.
Table 1-2. Main characteristics of the optical furnaces Furnace Uran USS-1 'Crystal' 'Orbit'
Optical elements ( number, dimension, angle of beam convergence) Monoelipsoid, one piece; d=0.6 m; α=35ο Monoelipsoid, one piece ; d=0.35 m; α=66ο Monoelipsoid, three pieces ;d= 0.6 m; α=35ο Parabolic, six pieces, d=0.5 m; concentrating parabolic (one piece; d=1.5 m); α=120ο
Type and number of lamps, required power DKsShRB 10000-1, one piece; 10 kW DKsShRB 150 A-1 (one piece; 3 kW DKsShRB 10000-1, three pieces; 30 kW DKsShRB 10000-1, six pieces; 60 kW
Diameter of focal spot, mm
Heat flux, W/cm2
Temperature, K
10-12
600
2800
2.0
2000
3500
10
1500
3500
10
1300
3400
Application Heat treatment, thermal tests, irradiation of biological objects Brazing and welding cutting of cloth Examination of oxides, surface treatment and coating Thermal and gas dynamic test of materials
Comment. Orbita furnace is originally equipped with a vacuum chamber and a plasma generator of 300 kW power. Number of systems: Uran –3 systems, rest –1 system.
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Figure 1-1. Basic diagram of bivariant helioinstallation: 1 - movable heliostat; 2 - optical sensor of the tracking system; 3 - solar radiation; 4 - vertical - axial concentrator; 5 -, 7- sample with a coordinate device; 6 - horizontal -axial concentrator; 8 - conditionally immovable heliostat; 9 - flat facets.
Figure 1-2.
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1.2. Development of the Analytic Method for Computation of the Facet Mirror Coating for Applying onto Paraboloid Antennae Now there are many technologies for manufacturing of solar concentrators. They are of single-unit production mainly. But there are no economically justified solutions of the problem and it hampers the use of the concentrators. This work is based on the idea we have been testing during 30 years. From 1974 in the Institute for Problems of Materials Science (IPMS) two concentrators of solar energy are operated without noticeable deterioration of technical data. They have been manufactured on the base of metal antennae ∅2.8 and 5.0 m. The mirror facets have been glued on the surface of the antennae [1]. The technological method used in the IPMS have been found at one time after relatively short period of search by the way of tests and errors and it has demonstrated its value in practice completely. Of course, it cannot be considered universal but it could be widely adopted if some problems are solved. These problems have not been considered in general or have been solved in insufficient volume.
1.2.1. Characteristics of Solar Radiation Concentrators (SRC) with Square Facets It has been demonstrated earlier [2] that when the facets are being placed onto SRC surface along the main rings (concentric circles) the facets configuration must be trapezium form to obtain a focal spot of the given diameter. The facets size changes in going from one main ring to another. Precise manufacturing the optimum facets calls for considerable financial and time expenditures especially when their required number is estimated in thousands. The facets of the identical size are used in practice. Usually they are square and placed along rectilinear secants of a surface as it is shown in the figure 1-3. It demonstrates naturally only qualitative pattern of the facets arrangement because it does not represent the spatialness of an object.
Figure 1-3. Pattern of facets arrangement on SRC.
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Figure 1-4. Radiant flux reflection onto surface. focal plane.
1.2.2. Focal Spot Size by Square Facets Let us determine the focal spot diameter for the SRC the surface of which is formed by square facets. The facet configuration in focal plane is deformed in comparison with initial one. The figure 1-4 explains the cause of this. Linear segment image in a plane being perpendicular to the figure plane remains to be unchanged if we neglect the small change connected with the radiation source finite size and the image of the linear segment laying in the figure plane changes: li = Kl ; K =
cos(θ / 2) cos θ
(1.1)
where l and li the length of the segment and its image, correspondingly; θ is an angle at which the segment center is visible from the focal spot center. So, in the figure central part the image is demonstrated for one of the facets arranged along the radius intersecting the facets along a diagonal (shaded band 1 in the figure 1-3. Depending upon the facets arrangement relatively the planes passing through the concentrator axis their images can take the form of rhomb (band 1), rectangle (for example for the facets lying within the shaded band 2) or nonequal-side parallelogram (band 3). The image deformation causes the change of the zone area in the focal plane center where all the rays reflected by the facets come together. This zone is a focal spot. So, the focal spot radius determined by the least (among all the facets images in focal plane) distance from the center to the image boundaries. Let us analyze the image configuration for the facet located at arbitrary place of the SRC reflecting surface (figure 1-5). Facet boundaries are denoted by thin line of a facet is projected onto focal plane without configuration change. This image is turned by an angle ϕ relatively the images symmetry axis being an axis perpendicular to the figure 1-4 plane and passing though focal spot center. A heavier line demonstrates the boundaries of the facet all the linear sizes of which in the y-axis direction have changes with the same proportionality coefficient.
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V.V. Pasichny and B.A. Uryukov
Figure 1-5. Modification of facet configuration in focal plane.
Geometric analysis demonstrates that minimum distance from the center O to the image boundary is equal to: lmin K = a cos ϕ K 2 + tg 2ϕ
(1.2)
where a is the half of a square side; K is the coefficient of linear magnification by reflection (1.1). Analyzing the eq. (1.2), we can find that the minimum value of the lmin takes place when ϕ = 0 i.e. lmin min = a. Hence, the focal spot diameter will be equal to square facet side (by perfect conditions of facets attaching to SRC bearing surface when the ray being reflected from a facet center gets to focal spot center). When the SRC is great enough and the facets are small it is necessary to take into account the change of the spot diameter due to finite size of radiation source being the Sun. The focal spot radius reduction for this reason is equal to:
ΔrF =
sin α S ⎛ sin(θ / 2) ⎞ ⎜R+a ⎟ cos(θ − α S ) ⎝ cos θ ⎠
where aS is an angular radius of the Sun being equal to 0,004654 Rad, R is an radius drawn from the focal spot center to a facet center (figure 1-4) witch is determined by the following formula for SRC parabolic frame:
R=
2f 1 + cos θ
where f is a focal distance.
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The maximum value of the ΔrF takes place when the θ value is maximum i.e. when θ = θm (the half of SRC aperture). Since under usual conditions as 673 K are polycrystalline; at higher substrate temperatures (Ts ≈ 773K) obtained metal oxide layers are low-resistive and highly transparent. To achieve minimal specific resistivity of tin oxide and ITO films, special alloying with indium, boron or fluorine impurity is necessary [17,66,67]. Therefore, several different technological methods are used to obtain conductive and transparent thin metal oxide films (including various deposition methods, alloying of the initial materials with proper impurities, special post-annealing, etc.) Not all the methods applied are studied deep enough to make exact judgments regarding their optimization possibility to obtain better electrical and optical properties of the resulted films, essential for their photovoltaic applications. Our investigations [22, 28, 68-71] were focused on analysis of technology influence on magnetron-sputtered high-conductive and transparent thin unalloyed SnO2, ITO, and CdO films.
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3. TECHNOLOGY FOR THIN SNO2, ITO AND CDO FILMS Thin films of SnO2, ITO and CdO were obtained using DC and RF magnetron sputtering (DCMS, RFMS), the former one in the atmosphere of Ar and O2. The latter method was used to deposit ITO films on the base of specially modernized industrial setup VUP-5. The magnetron itself was mounted in the window of the vacuum chamber (figure 1). Advanced external magnetron power source allowed controllable settings of direct cathode voltage and current in the ranges of 50-1000 V and 10-500 mA, respectively. For RFMS we used additional HF generator coupled with magnetron power source, operating with frequency 13.56 MHz and maximum power output of 50 W. The main advantage of our film deposition setup comparing to industrial magnetron VUP-5M was current stabilization of magnetron power source, allowing to avoid un-controlled cathode (target) discharge and keeping necessary current during deposition process. The authors also designed a special table for correct mounting and pre-heating of the substrate; we also performed general device optimization for most appropriate pressure control of carrier gas mixture, which allowed more flexible control over film deposition process. 4 1
5 6
3 2
7
50 – 1000В
A
V 9
8
Figure 1. Magnetron sputtering setup: 1– cooling agent (water); 2– magnetron; 3– vacuum chamber; 4– screen; 5– plasma; 6– substrate; 7– sputtered particles; 8– main body of vacuum setup VUP-5; 9– external magnetron power supply.
Total gas pressure in the chamber Pg was kept within the range of 0.1-10 Pa, using 5Npurity argon in carrier gas mixture. DCMS cathode was made of vacuum-synthesized 5Npurity tin, cadmium or 9:1 indium-tin alloy, forming the disk 60 mm in diameter. For RFMS the cathode of the same form and dimensions was made of pressed ITO ceramics. We used both glass and silicon substrates to deposit metal oxide films; the former to study their optical, and the latter to investigate their electrical properties and measure film thickness. Prior to deposition, glass substrates were cleaned in ethanol, silicon ones – in acetone. The substrate was located in some 5-7 cm away from the target. If necessary, substrates were preheated before the deposition to certain temperatures Ts (in the range of 300 - 473 K), kept constant till the end of the sputtering process. RF sputtering required pure argon plasma, formed when the pressure of carrier gas overcame some minimal threshold value. To perform film deposition at different pressures,
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the chamber was first pumped out to gain the limit pressure to glow up the plasma, and then Pg was adjusted to the required value, as plasma was self-maintaining in all the pressure ranges studied. Optimal cathode power for DCMS was determined experimentally to be within the range of 7.5-38 W (for the voltages 150-250 V and currents 50-250 mA). For the case of RFMS, cathode power was kept constant and equal to 15 W. Our investigations have shown that higher values of cathode power can result in local melting of target material, changing stoichiometric composition of the film. In general, film deposition rate was about 0.8 - 60 nm/min depending on target material and technological conditions. As we know [72], there exists critical cathode power for reactive sputtering, overcoming which it is impossible to ensure complete metal oxidation even in the atmosphere of pure oxygen. That is why it is possible (depending on partial oxygen pressure and discharge power) to deposit oxide mixtures with different content of Cd, In, Sn and O2, deviated in composition from stochiometric CdO, SnO2, and ITO. For example, increase of oxygen content in the carrier gas improves film transparency, but makes electrical properties of SnO2 and ІТО worse. Investigations have shown that DC-sputtered ITO films have better parameters if carrier gas is composed of 79% Ar and 21% of O2. Film thickness was estimated with interference Linnick microscope MII – 4, yielding different values depending on parameters of film deposition technology (target material, carrier gas pressure, cathode power, substrate temperature, deposition time, etc.). Surface morphology of the films was investigated using X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM) at Queretaro Branch of research centre CINVESTAV (Mexico). Investigations of their electrical properties included four-probe surface resistivity measurements. Optical transparency (transmission) of SnO2, ІТО, and CdO films was investigated with spectral photometer SF-20 at room temperatures in wavelength range 250 –1000 nm. To determine the influence of the temperature on electrical properties of the films, they were isothermally annealed for 10 minutes at 323 – 773 K in the air. For the sake of comparison, the samples were divided into two groups consisting of the samples obtained under the same conditions. First group was subjected to multiple 10-minutes long annealing stages, increasing temperature to 773 K in 50 K steps and measuring the resistivity of the sample after each stage. The second group was annealed only once during 10 minutes under constant temperature with further resistivity measurement. As it follows from the equal values of specific resistivity for both sample groups (within the measurement precision), the annealing time considered was sufficient to establish all the stationary states in the material.
4. RESULTS AND DISCISSION 4.1. Thin SnO2 films Thin SnOx films obtained were slightly yellowish, very clear and transparent, with smooth mirror-like surface characteristic to tin dioxide [73]. The technological conditions during film deposition are summarized in table 1. Film deposition rate was 1.0–13.0 nm/minute. All the films obtained had electron conductivity.
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As one can see from the table 1 and figure 2, dependence of deposition rate on chamber pressure has a maximum at certain optimal pressure (samples 3 and 9). At lowest and highest pressures investigated, deposition rate were the smallest (e.g., samples 1, 2 and 6). It also diminishes with temperature increase (samples 3, 5, 10, 11), but can be increased if the magnetron current becomes greater (samples 3, 4, 9, 10). Film thickness depends on the deposition time if the other conditions are kept invariable (samples 1, 2). With carrier gas pressure increase the adhesion of the film to non-pre-heated substrate becomes worse and deposition rate shorter (samples 6, 7). Under low chamber pressure (0.13–0.4 Pa) adhesion of the films are quite high even if the substrates were not pre-heated, but the magnetron power has to be reduced (samples 5, 11). In the opposite case the surface of the substrate gets the metallic speckle because of deposition of tin atoms that escaped oxidation. Table 1. Technology of SnO2 film growing by means of reactive magnetron sputtering Sample No.
1 2 3 4 5 6 7 8 9 10 11
Deposition time min
Substrate temperature Ts, K 300 300 300 300 300 300 473 473 473 473 473
Magnetron current Im, mА 100 100 100 70 70 100 160 160 160 100 70
30 15 30 15 60 30 30 30 30 30 60
Chamber pressure Pg, Pa 0.67 0.67 1.46 1.46 0.13 7.98 7.98 0.67 1.46 1.46 0.13
Film thickness, Nm 150 80 400 140 130 100 130 180 270 200 70
Deposition rate Vd, nm/min
14 Ts = 300K, Im = 100mA Ts = 473K, Im = 160mA
12 10 8 6 4 2
0
1
2
3
4
5
6
7
8
Carrier gas pressure, Pg
Figure 2. SnO2 film deposition rate depending on Ar/O2 carrier gas pressure.
9
Deposition rate Vd, nm/min 5.0 5.0 13.0 9.0 2.2 3.3 4.0 6.0 9.0 6.7 1.2
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Measurement of specific resistivity of the films immediately after formation yields the values ρ = 1–200 Ω·cm, failing quality requirements for conductive covers. The subsequent isothermal annealing of the films leads to significant resistivity drop. After annealing at 773 K specific resistivity decreases in about four-five orders of magnitude, reaching the values 1.5·10-3–6·10-4 Ω·cm. SnO2 films featured high parameter reproduction; after heating and cooling in the temperature ranges investigated film properties were stable and remained constant after a year of storage under normal conditions. As it was shown, sputtering rate and surface adhesion of SnO2 films depend significantly on integral pressure in the chamber (see table I.) Lower deposition rates at higher pressure (samples 1, 3, 6-9) can be attributed to increase of multiple collisions of sputtered atoms with those of carrier gas, which scatter the metal particles and decrease the total flux of the atoms moving towards the substrate. Moreover, the atoms show lower adhesion upon reaching the substrate if they lose their kinetic energy even partially. Decrease of deposition rate under lower pressures is caused by the lack of the positively charged ions of the carrier gas. Metallic layer of tin atoms forming at low pressure is caused by insufficient amount of oxygen atoms, leaving a portion of tin atoms without oxidation. The composition of SnOx film in this case will deviate from stoichiometric value for SnO2 towards the oxides of lower valence. This assumption is proved by dark yellow hue characteristic to SnO [73,74] if the films are grown at low chamber pressure (0.13 Pa) and magnetron current 250 mA. Figure 3 shows an example of annealing effect on film resistivity under various temperatures Ta for two films deposited on substrates with different substrate temperature (samples 1 and 10, according to table I). All the samples studied featured similar curves for ρ = f (103/Ta) with slight variations depending on substrate temperature while film deposition.
103
35eV EA=0.1
Resistivity ρ, Ω.cm
102 101 E
100 10-1
= EA
10-2 10-3
V 0e 5 . 0
eV 70 . =0 A EA=0.075eV
V 7e 4 . =0
EA
V 30e =0.
EA
10-4 1.0
0. E A=
V 30e
1.5
2.0
103/T
2.5 a,
K-1
Figure 3. Specific resistivity of SnO2 versus annealing temperature.
Sample 1 Sample 10 3.0
3.5
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As it follows from the figure 3, all the interval of temperatures studied could be divided into several parts, in which the dependence ρ (Тa) has activation character and could be described by the formula [75]: ρ (Тa) = 1 / (e n μeff) ≈ f (Ta, m, r).exp( EA / kTa ),
(1)
Here n and μeff are concentration and effective mobility of the carriers, f (Ta, m, r) is a function depending on annealing temperature Ta, material parameters m and dominant carrier scattering mechanism r; EA is the activation energy; other designations are common. As it is seen from the figure 3, films deposited on the substrate without pre-heating (sample 1) under low annealing temperatures (300 K < Ta < 330 K) feature activation energy EA = 0.135 eV. Good correlation of the latter value with formation energy for oxygen vacancy in SnO2 (EV = 0.130 eV [76]) makes sound the assumption that namely oxygen vacancy ionization leads to comparably small lowering of specific resistivity of the SnO2 films in this case. For annealing temperature 350 K < Ta < 470 K activation mechanism changes, which is reflected in significantly greater activation energy EA = 0.69 ± 0.01 eV, suggesting that oxygen divacancies are formed in the film or that these vacancies (or divacancies) become trapped by impurity atoms, resulting into complex associates. Hence, activation energy will have significant value, being a sum of vacancy (or divacancy) migration energy and associate formation energy. The associates appeared in the material are instable formations, dissociating under further temperature increase (470 K < Ta < 700 K), which leads to appearance of new defects with EA = 0.50 ± 0.01 eV. It is peculiar, that for Ta > 730K another defect subsystem with EA = 0.30 ± 0.06 eV becomes dominant. Kinetics of annealing processes for the films deposited on pre-heated substrate (473K, sample 10, figure 3) differs from the previous case. First, for 300 K < Ta < 370 K activation energy is significantly lower and is equal to EA = 0.075 ± 0.005 eV. It worth noting that this value is quite close to the height of inter-crystallite barriers Vd in the films of other semiconductor materials (e.g. for CdS the value of Vd is about 0.06-0.2 eV [75]). It makes it possible to assume that decrease of specific resistivity of SnO2 films, deposited over preheated substrates is caused by the crystallite grains forming in the material studied. It is important that there are no traces of complex associates formation in the films deposited over pre-heated substrate, which lowers defect level of the material and significantly reduces its specific resistivity. It is also curious that activation energies EA = 0.47 ± 0.03 eV and EA = 0.30 ± 0.04 eV, determined for Ta > 470 K, show no dependence on the substrate temperature during film deposition, at least within experiment precision. Further annealing time increase and multiple annealing does not change SnO2 resistivity in any significant way. Analysis of transmission spectra of SnO2 films (figure 4) shows that isothermal annealing at 473K for ten minutes improves their transparency to 90 – 95% (for example, figure 4 curves 1 and 1') and makes steeper the slope of intrinsic absorption edge. The latter becomes steeper also if the film deposition had carried out at higher substrate temperatures (samples 8 and 10). Such a behavior of transmission coefficient could be explained by specific transformations of defect subsystem during SnO2 film deposition on pre-heated (T = 473 K) substrate. Band gap estimations made from spectral dependence of transmission coefficient give the values of 3.54 – 3.75 eV, which corresponds quite well with SnO2 data, published in different sources [17, 77, 78].
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1.0
Transmission, d.u.
10
8 1' 1
0.5
0.0 200
400
600
800
1000
Wavelength, nm Figure 4. Optical transmission of SnO2 film (curves 1, 8, 10 – data for samples1, 8 and 10 (see table I), curve 1' – data for sample 1 after annealing at 473 K for 10 min).
4.2. Thin ITO Films Analysis of the experimental results allowed us to determine the optimal technology to grow high conductive and transparent ITO films with good adhesion to the substrate. Table 2 summarizes main technological film deposition regimes. All the films obtained had electron conductivity. As it follows from the table 2, film deposition rate Vd depends on the temperature of the substrate Ts, carrier gas pressure Pg and cathode power Pc. In the figure 5 deposition rate Vd is plotted versus Pc for different Ts and constant Pg. As one can see, for all the values Pc and Ts studied this dependence is linear in the terms of measurement precision: Vd = C . Pc,
(2)
with coefficient C decreasing linearly with substrate temperature growth (inset to the figure 5), which could be explained by increase of back-evaporation of the material from the heated substrate [72]. On the other hand, deposition rate Vd = f(Pg) at constant Pc and Ts has a form of the curve with a maxima (figure 6) characteristic to dynamic systems with damping, which obeys the expression Vd = C1 . Pg . Py / ( (P02 – Pg2 )2 + Pg2 Py2 ),
(3)
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Table 2. Technological parameters for ITO films obtained by magnetron sputtering Sample No.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
Cathode power Pc, W
Substrate temperature Ts, K
300 300 300 300 300 300 300 300 300 373 373 373 373 373 373 473 473 473 473 473 473 473
7.5 7.5 7.5 7.5 15.0 15.0 15.0 15.0 38.0 7.5 7.5 7.5 7.5 15.0 38.0 7.5 7.5 7.5 15.0 38.0 38.0 15.0
Film thickness, nm
0.13 0.5 0.8 1.5 0.13 0.5 0.8 1.5 0.8 0.13 0.5 0.8 1.5 0.8 0.8 0.13 0.8 1.5 0.8 0.8 7.8 0.8
400 490 540 620 450 520 600 710 980 300 320 400 400 650 1000 250 250 250 600 1000 100 550
Deposition rate Vd, nm/min
15
40 44 46 52 35 39 41 47 26 20 21 23 27 20 11 8 9 10 7.5 5.5 9.5 4.8
0.6
1
0.4
2
0.2
10
300
400
TS, K
Specific resistance ρ, 10-2Ω⋅cm
1.5 3.5 4.4 3.7 2.3 6.1 9.0 7.2 20.0 1.1 2.3 3.0 2.6 6.0 16.5 0.8 1.8 1.5 5.3 11.5 1.2 11.0
C, nm min-1 W -1
Deposition rate Vd, nm/min
20
Chamber pressure Pg, Pa
500
Surface resistance ρ, Ω/□
10000 8980 8519 8387 7778 7500 6833 6620 2653 6667 6562 5775 6750 3077 1100 3200 3600 4000 1250 916 9500 850
3
5
0
0
10
20
30
40
Power Pc, W Figure 5. Dependence of ITO film deposition rate Vd for different substrate temperatures Ts (1 – 300 K; 2 – 373 K; 3 – 473 K) on the cathode power Pc for direct current reactive magnetron sputtering and pressure of carrier gas Ar/O2 = 0.8 Pa. Inset: dependence of Vd on Ts..
Yu.V. Vorobiev, J. Gonzalez-Hernandez, P. Gorley et al.
Deposition rate Vd, nm/min
20
1
16
2
12
3
C1, nm min-1 Pa2
288
300
200 300
8
400
500
TS,K
4 0
0
2
4
6
Carrier gas pressure Pg, Pa
8
Figure 6. Dependence of ITO film deposition rate Vd for different substrate temperatures Ts (1 - 300K; 2 – 373K; 3 – 473K) on the pressure of carrier gas Ar/O2 in the chamber, magnetron cathode power Pc = 38 W. Inset: plot of constant C1 from (3) versus Ts.
with damping coefficient Py = 10.17 Pa and parameter P0 = 3.23 Pa, analogous to intrinsic gas pressure. The damping in the system considered may appear due to scattering processes taking place for the sputtering atoms over carrier gas atoms or other sputtering atoms. Coefficient С1, corresponding to the peak value of Vd plot, appears decreasing linearly with increase of Ts (inset to figure 6). Physical mechanisms leading to damping could be connected with increase of multiple collisions and scattering of the sputtered atoms over carrier gas atoms in the chamber, and also by lowering of general atomic flow towards the substrate. It is worth noting that under pressure increase Pg > 1.1 Pa film adhesion to room-temperature substrates also becomes lower, which could be addressed to partial decrease of kinetic energy of sputtering atoms after the scattering. Under the lower pressures for Pg < Pgmax (where Pgmax is the pressure corresponding to a maximum of Vd(Pg) curve), one can observe deposition rate decrease, caused by the lack of positive charged ions of the gas necessary to keep with phase equilibrium. Under low pressures film adhesion is rather high even for room-temperature substrates, but in this case one has to decrease cathode power to avoid deposition of nonoxidized In and Sn atoms due to the lack of oxygen, causing metallic shine of the film and significant deviations from stoichometry. Analysis of experimental data from the table 2 shows that the films grown under the constant cathode power have rather high resistance (ρ ≥ 0.06 Ω.cm), which increases slightly with carrier gas pressure Pg and depends inversely on substrate temperature Ts (figure 7). The similar dependence ρ = f(Pg) was observed also in [79]. Significant improvement of film electric properties upon isothermal annealing was reported in [80, 81]. Figure 8 shows characteristic curves of specific resistivity ρ versus annealing temperature Та for the samples 7, 14 and 19 (table 2), obtained under the same Pg and Pc, but different Ts. Our investigations proved that 10-minute annealing under constant temperature is completely enough for establishing equilibrium state in the films, judging from equal values of specific resistance obtained for both groups of the samples.
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Specific resistivity ρ, Ω⋅cm
100
1
2 10-1
0
2
4
6
8
Ar/O2 carrier gas pressure Pg, Pa Figure 7. Dependence of ITO specific resistance ρ on carrier gas pressure Pg for different substrate temperatures (1 – 373K, 2 – 473K) and cathodepower Pc = 15W.
100
14
19
10-1
10-2
10-3
10-4 200
Activation energy EA, 10-2eV
Specific resistivity ρ, Ω⋅cm
7
18
1
15
2
12 9
300 400 500 TS, K
300
400
500
600
700
800
Temperature of annealing TA, K Figure 8. Specific resistance of ITO films versus annealing temperature (curve numbers correspond to the sample number in the table 2). Inset: constants Ea (1) and E1a (2) versus Ts.
As it follows from the figure 8, the character of ρ=f(Ta) is significantly different for given Ta, making it possible to divide all the temperature range investigated into three parts. Lowtemperature annealing (300 K < Ta < 473 K) is characterized with slight changes of ρ with increase of Ta. This dependence becomes even weaker for higher substrate temperatures. Moderate-temperature annealing (473 K < Ta < 600 K) leads to fast decrease of resistance by several orders of magnitude. Upon reaching the minimal value (4 – 9)⋅10-4 Ω⋅cm at nearly 530
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K, ρ starts to grow and at Ta=600 K it becomes equal to (1–2)⋅10-3 Ω⋅cm. High-temperature annealing (600 K < Ta) features slight resistance increase with Ta. To explain possible mechanisms causing these changes of resistance behavior, one have to keep in mind that ITO films obtained were amorphous according to the XRD and AFM surface structure investigations (figure 9). In this case, as it was discussed in [82], changes of specific resistance of the film in wide temperature ranges could be described by
ρ = ( A exp( -∆E / kT ) + A1exp( -∆E1/kT ) + A2exp( -∆E2/kT ) )-1,
(4)
with constants A, A1 and A2 determined by technological parameters during film deposition but independent on the temperature, and different activation energies ∆Е, ∆Е1 and ∆Е2. Three items in right hand side of (4) describe partial contributions to current transport by different groups of carriers: those at delocalized states, excited carriers at the edge of allowed energy band (i.e. close to the energy of donor and acceptor levels), and by electrons contributing to hopping conductivity between localized states close to Fermi level. As it is generally accepted, third mechanism is dominating only for low temperatures, while two others – for higher ones [83]. Nevertheless, results of experimental investigations for amorphous silicon and germanium proved the hopping conductivity to be significant in the wide temperature range of 40-400K. Annealing could lead to the changes of dominating mechanism of conductivity (for the case of amorphous germanium, one can observe hopping conductivity prevailed by band conductivity [83]), resulting in changes of specific resistance. Moreover, analyzing influence of the annealing in the air over ρ of ITO films obtained, one may also have in mind presence of stoichiometric and molecular oxygen. The former already exist in crystalline lattice and forms complex associates upon annealing [84], while the latter could be absorbed by the surface of the film and undergo further chemisorption by trapping of conductivity band electrons, which will result in formation of depleted layers at the surface [66]. It is important, that with increase of annealing temperature, initially amorphous ITO could be gradually turned into monocrystalline material with grain size depending on Ta. This effect triggers formation of carrier-depleted, inverted or enriched areas at grain boundaries resulting in different kinds of potential barriers [83], depending on the nature of subsurface states and energy distribution of surface levels. Such a complex mechanism determining specific resistance could be properly considered only with corresponding complicated physical model, which will require separate research work. Here we will present only qualitative discussion of the data presented in figure 8. The low-temperature annealing changes of specific resistance ρ with temperature are caused mainly by activation mechanism with activation energy Еа, obeying to [83]
ρ = 1 / σ = 1 / ( e n μeff ) = A0 ( Та / 300 )3/2 exp( Ea / kTa ),
(5)
where n is carrier concentration and μeff - effective mobility, e - absolute value of elementary charge, and independent on the temperature normalization constant A0. In (5) it was taken into account that for the temperature range investigated the most probable carrier scattering mechanism involve acoustic phonons. Calculation results obtained with (5) correlate well with experimental data (dashed lines in figure 8, plotted for three different substrate
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temperatures Ts). Activation energy Ea linearly decreases with increase of Ts (curve 1 at inset to the figure 8), which could be connected with different concentration of oxygen vacancy acting as donor. Obtained values 0.10 ≤ Ea ≤ 0.18 eV, correlating well with formation energy of oxygen impurity EF = 0.13eV in SnO2 [76] could be considered as qualitative proof of this assumption.
Figure 9. Surface morphology AFM data for ITO film deposited on room-temperature substrate.
For high-temperature annealing ( 600 K < Ta ) experimental results fit well the formula
ρ = A exp ( -E1a / kTa ),
(6)
with normalization constant A and parameter E1a, which most probably describes the difference of energies corresponding to formation of different structural defects, such as vacancies, interstitial atoms, associates, etc. Dash and dot lines in figure8 represent calculation data obtained according to (6). Comparing (5) and (6), one may notice that physical processes taking place in low- and high-temperature annealing modes are significantly different. It is also proved by the fact that the value of E1a increases with Ts (curve 2, the inset to figure 8) on the contrary to the behavior of energy Ea for lowtemperature annealing. As formula (6) has no coefficient depending on temperature by the exponent, one can assume that carrier scattering is connected mainly with neutral impurities or their clusters for high-temperature annealing. One of the possible explanations of ρ = f(Ta) behavior after annealing at 600K < Ta could be either crystallization processes leading to increase of grain size or qualitative changes in defect sub-system. Our experiments have shown that specific resistance of the films in moderate-temperature annealing mode (473 K < Ta < 600 K) could not be described as superposition of (5) and (6). It means that to determine the nature of physical and chemical processes taking place at these annealing temperatures it will be necessary to apply methodology developed for chemical kinetics and non-equilibrium thermodynamics [83]. Construction of appropriate physical model will allow finding functional dependence of ρ on technological conditions during film deposition, opening ways to obtain ITO films of maximal possible conductivity. At the moment we have only determined optimal technological regimes for magnetron-sputtered
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low-resistive ITO on the base of analysis of experimental data. Our films featured reproducible parameters and were characterized with specific resistance ρ = 4 - 6⋅10-4 Ω⋅cm, being among the best results published [83, 86, 88]. Investigation of optical properties of obtained ITO films proved their high transparency (visible spectra transmission for the best samples 90-95%, figure 10). For the sake of comparison with ITO films annealed in the vacuum figure 10 features experimental data from [87]; as one can see, our best films has a little higher and homogeneous transmission for visible light. Insignificant deviation of transmission slope at the intrinsic absorption edge between our films and data of [87] could be caused by difference of their thickness. Experimental results also shown a correlation between electric and optical parameters of ITO films obtained – samples with smaller minimal specific resistance (figure 8) has higher slope of transmission curves at intrinsic absorption edge (figure 10). At the same time films deposited on room-temperature substrates (i.e. sample No. 7) are characterized with less steep absorption edge than those deposited on pre-heated substrates (samples No. 14, 19, and 21). Band gap of ITO films estimated from figure 10 was about 3.7eV, which agrees well with previously published data [17, 72, 89-91]. 100
Optical transmission, d.u.
19 80
14 60
22
7
40 20 0
400
600
800
1000
Wavelength λ, nm Figure 10. Optical transmission of ITO films (curve numbers 7, 14, and 19 corresponds to the sample numbers from the table 1; sample 14 was additionally annealed at 523K, 19 – at 773K, 22 – high frequency magnetron sputtering, squares corresponds to the data from [87]).
4.3. Thin CdO Films Thin CdO films are usually obtained by pulverization with further pyrolysis or either by growing from the melt [17, 92, 93]. However, these methods do not allow to obtain films with high transparency and conductivity or to ensure their stoichiometric homogeneity, causing moderate or low efficiency of solar cells with CdO films grown with either of these two methods. Results of our investigations prove that magnetron sputtering is a promising method to obtain high-conductive transparent CdO layers, suitable for photovoltaic applications.
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Deposition rate Vd, nm/min
Main technological data and properties of DC magnetron sputtered CdO films are presented in the table 3 and figures 11-13. Our CdO films were transparent and continuous, with smooth mirror-like surface and good film adhesion to the substrate. Thermal probe measurements proved electron conductivity type of all the films obtained. As it follows from the figure 11 and table 3, film deposition rate decreases with substrate temperature increase; this effect is most pronounced for maximum constant magnetron current and maximum pressure of carrier gas (Pg = 1 – 2 Pa), for which deposition rate Vd is the highest (curves 1-3 and 4-6). 60 50
1
40
2
30
4
20
5 3
10
6 300
350
400
450
500
Substrate temperature Ts, K
Deposition rate Vd, nm/min
Figure 11. CdO film deposition rate depending on substrate temperature for different carrier gas pressures Pg and magnetron currents (curves 1, 2, 3 – Рg = 1.5 Ра, Іm = 130, 100, 50 mA; curves 4, 5, 6 – Pg = 6.0 Ра, Іm = 130, 100, 50 mA).
60
1
50
2
40
3 4 5 6
30 20 10 60
80
100
120
140
Magnetron current Im, mA Figure 12. CdO film deposition rate versus magnetron current (curves 1, 3, 4 – Тs = 300 K, Pg = 1.5, 0.13, 6.0 Pa; curves 2, 5, 6 – Тs = 473 K, Pg = 1.5, 0.13, 6.0 Pa).
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Table 3. Technology and parameters of DC-reactive magnetron sputtered CdO films Sample No.
Substrate temperature Тs, K
Magnetron current Im, mA
Carrier gas pressure Pg, Pa
Film thickness, nm
Deposition rate, nm/min
Specific resistivity ρ×10 2 Ω⋅cm
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
300 300 300 300 300 300 300 300 300 300 300 373 373 373 373 373 373 473 473 473 473 473 473 473 473 473 473 473
50 50 50 50 50 50 50 100 100 100 130 50 50 50 100 130 100 50 50 50 50 100 100 100 130 130 130 130
0.13 0.5 0.8 1.5 2.5 3.5 6.0 0.13 1.5 6.0 1.5 0.13 0.8 1.5 1.5 1.5 6.0 0.13 0.5 1.5 6.0 0.8 1.5 2.5 0.8 1.5 3.5 6.0
550 750 880 950 875 800 1300 1175 1500 1075 1800 520 725 850 760 750 925 475 550 575 425 440 500 525 450 550 500 575
14 19 22 24 22 20 13 29 47 27 60 13 18 21 42 54 23 12 14 17 10 34 38 35 39 48 38 27
6.12 8.21 9.40 12.10 13.78 13.48 14.60 4.75 5.80 5.95 5.52 0.70 0.75 0.80 0.63 0.59 0.68 0.17 0.18 0.22 0.24 0.19 0.21 0.22 0.20 0.25 0.24 0.27
Higher magnetron power (or current) and lower deposition temperature also increase film deposition rate (figure 12). The latter also depends on pressure of carrier gas (figure 13), but, as it could be seen comparing figures 13, 15, table 3 and data presented in figures 2, 5, 6 and tables 1, 2, Vd(CdO) is significantly higher than Vd(SnO2, ІТО) under the same technological conditions. The peak of maximum deposition rate for CdO is blurred and shifted towards higher pressures (Pg = 1 – 2 Pa). Investigated technological regimes made it possible to change film deposition rate in wide ranges of 10-60 nm/min.
Deposition rate Vd, nm/min
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60 50 40 1 30
2
20
3 4 5
10 0
0
1
2
3
4
5
6
Carrier gas pressure Pg, Pa Figure 13. CdO deposition rate depending on carrier gas pressure for different substrate temperatures Тs and magnetron currents Іm (curves 1, 4 – Тs = 300 K, Іm = 130 i 50 mA; curves 2, 3, 5 – Тs = 473 K, Іm = 130, 100, 50 mA).
Specific resistivity ρ, Ω⋅cm
10-1
10-2
9
15 23
10-3
300
400
500
600
700
800
Temperature annealing Ta, K Figure 14. Specific resistivity of CdO films obtained for different substrate temperatures Ts as a function of annealing temperature TA (curve numbers correspond to sample numbers in the table 3).
Typical specific resistivity curves for CdO films are presented in figure 14 for the samples 9, 15, and 23, grown under different Ts (see table 3), with subsequent annealing in the air at Ta = 323 – 773 K. This dependence of resistivity on annealing temperature was observed for all the films obtained. For Ts= 300 – 473 K, resistivity of the films remains within the ranges of 5.8⋅10-2 – 2.1⋅10-3 Ω⋅cm. With increase of annealing temperature specific resistivity decreases at first in the temperature range Тa = 300 – 573 K, reaching the minimum ρ = 5⋅10-4 Ω⋅cm. The samples, deposited on the non-pre-heated substrate (curve 9) show higher resistivity deviation comparing to the samples deposited on pre-heated substrates (curves 15, 23). With further increase of annealing temperature Тa > 573 K specific resistivity of the resulted films shows no particular dependence on the latter. Average temperature
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Optical transmission, d.u.
coefficient of resistivity dρ / dTa for the samples 9, 15, 23 are 2.1⋅10-4, 0.2⋅10-4, and 0.07⋅104 Ω⋅cm/K, respectively. Almost the same values of dρ / dTs coefficient are characteristic for non-annealed samples (e.g. curves 9, 15, and 23 for ТА =300 K and Тs = 300 – 473 K). Resistivity values obtained correlate well with other published data [88, 89]. Resistivity decrease with higher substrate and annealing temperatures can be most probably connected with film structure improvement due to grain size increase, and therefore decrease of the area of inter-barrier crystalline phases. These factors diminish the concentration of traps and interbarrier scattering over grain boundaries which, in turn, increase carrier mobility and conductivity. The similar behavior of resistivity is characteristic to transparent conductive SnO2 films (see 4.1). Transmission spectra of CdO films obtained for different substrate temperatures or after annealing are presented in figure 15. Films, which were grown under room temperatures (curve 9) feature rather low transmission (Т ≈ 65 %) and small intrinsic absorption slope, which is caused by their low structural perfection and possible presence of un-oxidized cadmium in the films, which was proved on the base of X-ray investigations in the paper [18]. 1,0 0,8 0,6
23 a 15′
15
9
9′
0,4 0,2 0,0 400
500
600
700
800
900
Wavelength λ, nm
1000
Figure 15. Optical transmission of CdO films (curves 9, 15, 23 – corresponds to sample numbers from the table 3; curves 9′, 15′ – data for annealed samples 9, 15 (TA= 573 K); curve а – transmission data from [18]).
Films deposited at temperatures 373 and 473 K are characterized with higher transmission (Т = 80 – 85 %) with abrupt absorption edge, insignificantly shifted to the shorter wavelengths. For comparison, transmission data for CdO films according from [18] for Тs = 523 K are plotted in figure 15 (curve a), showing good correlation with the data obtained by the authors. Film annealing (at temperature Тa characteristic to minimum film resistivity) leads to increase of transmission coefficient and steeper transmission curve (compare figure 15, curves 9, 15 and 9′, 15′). For the sample 15′ one can observe the interference pattern, not presented in the figure 15 to avoid visual overloading. Transmission of the samples, deposited on room-temperature substrates, can be significantly improved by annealing (from 60-65 to
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75-80 %), while for the samples grown with Тs = 473 K the slope of transmission curve and transmission coefficient itself do not feature significant changes (Т = 80-90 %), while their interference peaks become sharper (e.g., for the film 23 transmission prior and after annealing are practically the same). Improvement of optical properties of CdO films deposited on preheated substrates or after isothermal annealing in the air can find reasonable explanation by improvement of their crystalline structure, proved by the character of the curves ρ = f(Ts) and ρ = f(TA), as well as by the presence of sharp interference pattern for the samples, obtained for Ts > 373 K, as well as those annealed at Тa = 573K. Presence of well-defined interference peaks made it possible to estimate film thickness using the following formula [95] d = λ1λ2 / [4n (λ1 – λ2)],
(7)
with CdO refraction coefficient n = 2.49 [96] and position of two subsequent maximums or minimums λ1 and λ2. Calculated film thickness agrees well with the thickness measured on MII-4 setup. Band gap value, estimated from the optical transmission of the films grown under different technological conditions was approximately 2.2 – 2.45eV. For higher substrate temperatures (figure 15, curves 9, 15) or after annealing (curves 9, 9′ and 15, 15′) the band gap decreases, which can be caused by the Burstein-Moss effect [17].
5. CONCLUSION Results of current investigations prove the possibility to obtain high-transparent and conductive thin metal oxide films with magnetron sputtering and further controlled annealing. Direct-current and radio-frequency magnetron-sputtered films were obtained with specially modernized industrial setup VUP-5 allowing more flexible control over magnetron power, carrier gas pressure, substrate temperature, etc. Optimal film deposition and annealing regimes were determined empirically, resulting in thin films with the following parameters: SnO2 – specific resistivity ρ = 6 – 15.10-4 Ω⋅cm, optical transmission T = 90 – 95%; ITO – ρ = 4 – 6.10-4 Ω⋅cm, T = 90 – 95%; CdO – ρ = 5 – 20.10-4 Ω⋅cm, T = 80 – 90%. Further improvement of these parameters (i.e. resistivity decrease keeping high transparency), to our opinion, will be possible when the physical processes taking place during film deposition and annealing will be better understood, which will take place upon development of proper theoretical models describing metal oxide layer formation. This model has to consider the decrease of inter-crystalline boundaries caused by grain size increase during film deposition and further annealing, which may lead to decrease of their influence on electrical and optical properties of the films. To our point of view, it is impossible to obtain better high-conductive and transparent films of SnO2, In2O3-SnO2 (ITO) and CdO films without additional investigations (including ellipsometric data), which will allow for the determination of the influence of grain boundaries, and hence, to enhance technology optimization to obtain thin metal oxide layers with better electrical and optical parameters.
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In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 301-326
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 10
DYNAMIC IMPEDANCE CHARACTERIZATION OF SOLAR CELLS AND PV MODULES BASED ON FREQUENCY AND TIME DOMAIN ANALYSES* D. Chenvidhya†, K. Kirtikara and C. Jivacate Clean Energy Systems Group (CES), King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand
ABSTRACT This article describes new methods to derive dynamic impedance of solar cells and PV modules from time and frequency domain analyses. Initially, we propose a new method, based on the frequency domain analysis, to measure dynamic impedance of x-Si solar cells and PV modules in the dark using basic instruments and FFT analysis. The dynamic parameters in the AC equivalent circuit, in addition to the DC model, consists of dynamic resistance, diffusion capacitance and transition capacitance. Loci of impedance in the complex plane can be obtained by inputting a small signal square wave, superimposing on either forward bias or reverse bias, to cells or modules. Such technique is compared with sinusoidal inputting. All of these parameters can be obtained from impedance loci in the complex plane. The impedance of a cell or a module can be derived in a closed form equation in terms of frequency dependent and voltage dependent resistance and capacitance under the dark condition with reverse bias. The relationship between the dynamic and static characteristics is compared for solar cell modules having low and high fill factors. Another new analytical method determining solar cell and module dynamic impedance is demonstrated using the same measuring techniques. Determination of dynamic parameters, previously outlined, and time constant of solar cells and modules, based on a time domain response, can be simultaneously obtained at each bias condition. *
A version of this chapter was also published in Leading Edge Research in Solar Energy edited by P. N. Rivers published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research. † Email:
[email protected] or
[email protected] 302
D. Chenvidhya, K. Kirtikara and C. Jivacate The merits of this second characterization method using square wave inputs are reduction in measuring steps and yielding of dynamic parameters and time constants in a single measurement. Experiments on polycrystalline and amorphous silicon cells and modules are also conducted and their results will be separately revealed at a later date. Knowledge of dynamic impedance characterization of solar cells and modules will lead to better understanding of behaviors of PV grid-connected systems and improvement of power quality from such distributed power generation systems.
1. INTRODUCTION Understanding of solar cell characteristics is very important for studying solar cells performances. In practice, this involves understanding the fundamentals and development of devices, performance evaluation and various methods of measurement. Characteristics measurement would yield information to identify and the improvement of material properties in cell production, to identify solar cell grades for module production, to verify suitable models, and to evaluate cell or module performances. Solar cells parameters are basically determined in static characteristics. The solar cell characteristics consist of open circuit voltage (Voc), short circuit current (Isc), voltage, current and power at the maximum point (Vmp, Imp and Pmp), the fill factor (FF), series resistance (Rs) and shunt resistance (Rsh). These parameters can normally be characterized by various static characterization methods. In static characteristic determination, measurements can be done either under illuminated or under dark conditions. Under illumination, the measurements of IV characteristics are used in most standard measurements. However, the characteristics in the dark can often be found in various research works. The static characteristics or I-V characteristics of solar cells, both illuminated and dark characteristics, are often described in most of solar cell textbooks. These include the dc equivalent circuit model (lumped and distributed model), equations, operating conditions, curves, etc. Therefore, it will not be repeated here. In the past, most of solar cell applications were for stand-alone purposes, with battery storages in most cases. Knowledges of static parameters are adequate as any fluctuation in output from solar cell modules due to light intensity will have no impact on loads. Either constant dc voltages can be drawn from the battery or uniform ac voltages are available from inverters connected between the module and loads. However, it is clear from all situation reports that the direction of PV applications is a rapid increase and trend in grid-connected applications. Cloud movements will cause fluctuating module output. The module output, in turn, becomes the inverter input whose outputs are sensitive to the inverter operating condition (e.g. input voltage, input power). As the loads draw powers from both the inverter and the line, the electrical quality of the loads, the inverter and the line are related. To understand the dynamics of module and grid connection under varying cloud conditions, the solar cell, module and array ac or dynamic parameters are essential. The solar cell dynamic parameters, such as minority carrier lifetime, time constants, diffusion length, diffusion and transition capacitances (CD and CT) can be calculated by measurements when solar cell operates under dynamic or transient conditions.
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For modeling of a solar cell or a PV module, a dc model or dc equivalent circuit is adequate for describing solar array behavior in general. A dc circuit model consists of a series resistance (Rs), a shunt resistance (Rsh) and a diode having a non-ideal diode factor. The solar cells dynamic characteristics and impedance measurements had been described and reported in some specific applications, such as satellite applications [5, 6], the Mars Pathfinder and measurement of impedance of GaAs/Ge solar cells [3] and the Si Back Surface Field Reflector (Si-BSFR) solar cells [3]. The results are used to design efficient, reliable, high power devices with stability. In all cases, the impedances are determined by special equipment, such as an electrochemical interface (ECI), a frequency response analyzer (FRA) using an impedance spectroscopy technique. In previous studies, they highlight solar cell impedances in terms of material properties, and measured solar cells under dark conditions with either forward bias or reverse bias conditions. In our studies, we aim that understanding of dynamic impedances of solar cells and arrays are essential in determining the dynamic performance of arrays when connected to electricity distribution networks. It will become increasingly important when more PV systems are connected to the networks. This article describes new methods to measure and to derive dynamic impedances of a solar cell and a PV module from time and frequency domain analyses. The outline of this chapter consists of theoretical background for an ac equivalent circuit and Impedance Spectroscopy, a new method for solar cell impedance characterization, dynamic impedance in frequency domain analysis, PV module diagnostic method with dynamic impedance, and dynamic response in time domain analysis. The detail of each section is following.
2. THEORETICAL BACKGROUD
2.1. AC Equivalent Circuit An ac model of a solar cell, shown in figure 1, contains the illumination controlled current source (IL), series resistance (Rs), shunt resistance (Rsh), diode resistance (Rd) and in additional to equivalent components of a dc model, the transition capacitance (CT) and diffusion capacitance (CD). Rd represents non-ideal diode characteristic. CT is the junction or space-charge capacitance of the depletion region. CD is the capacitace due to minority carrier oscillation in response to the ac signal. It is recognized that an ac equivalent circuit of a module or and array takes similar forms to that of a solar cell. The particular forms depend on characteristics of individual solar cells and how solar cells are connected in modules and connection of modules into arrays.
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Figure 1. Ac equivalent circuit of a solar cell connecting to a load ZL under illumination.
The values of Rs and Rsh, are both voltage independent. The CT and Rd are voltage dependent, and a CD is voltage and frequency dependent. The values of CD, CT and Rd vary with the level of incident light, the cell temperature, the cell operating voltage, the solar cell material constant and processing parameters. In the high frequency range, the value of CD is approaching zero with increasing frequency. This is due to the minority carrier storage effects. Therefore, the CT is the only capacitance remaining at the higher frequencies. The value of CT depends upon dc voltage. From the static I-V characteristic of a solar cell under steady state illumination, the incremental diode dc resistance (Rdc) at any point on the output is defined as
R dc = dVdc dI dc
(1)
Rdc is related to Rd as follows
R dc =
R d R sh + RS R d + R sh
(2)
Variations of Rdc can be illustrated as a function of the dc voltage, Vdc. The values of Rdc of a solar cell vary in the range of 103 to 10-1 Ω. Near the short circuit condition, Rd becomes very large, and Rsh dominates the cell impedance. But near the open circuit condition, Rd becomes small, Rs exerts a large influence on the impedance.
2.2. Impedance Spectroscopy Technique In previous works, the impedance measurement technique mostly uses the method of impedance spectroscopy. The concept of the method can simply be described in figure 2.
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Figure 2. Block diagram describing the simply concept of Impedance Measurement using sinusoidal signal inputs.
The impedances of a solar cell are measured in the dark using sinusoidal signal inputs with varying frequencies and superimposing on the dc bias. It is measured in both forward bias and reverse bias conditions. The impedance loci are plotted and interpreted in a complex plane at any bias levels.
3. A NEW METHOD FOR SOLAR CELL IMPEDANCE CHARACTERIZATION A new method developed under this research work has been introduced by the author. To characterize the dynamic impedance of solar cell or module, we use square wave inputs superimposed on a dc biasing voltage in either forward or reverse condition. A square wave signal, being periodic, consists of infinite numbers of sinusoidal signal. Thus, inputting one square wave to a solar cell is, in theory, equivalent to simultaneously inputting infinite sinusoidal signals. In principle, any periodic inputting signal can be used. A square wave is used because it is readily available from most signal generator equipment. In this method, the responses are calculated by signal processing input and output signals (voltages and currents) using FFT technique to obtain various harmonic contents of input and output. A block diagram describing the concept of measurement is shown in figure 3. At the same time, this method permits analyzing data regarding the transient behavior of solar cell under study so that response time, rise and fall time, or time constant can be determined.
Figure 3. Block diagram of the method of dynamic impedance measurement using square wave inputs.
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In this method, the measuring results can be obtained by basic instrument such as oscilloscope and signal generator. At each square wave input of a certain frequency, phases and amplitudes of up to 10 corresponding harmonics can be determined with accurate measurement. It means that one whole impedance locus can be measured by using 2-3 square wave inputs at different frequencies. For previous studies, a large number of sinusoidal test frequencies covering 4-5 decades are required, hence, more measuring steps and time. Therefore, the advantages of this method, compared with the sinusoidal input method, are less expensive equipment setup, simpler measurement, and reduction in measuring steps, yielding comparable results. The experiment is setup to ensure the results obtained from this characterization method for solar cell dynamic impedance using square wave inputs. Both are done in the dark with forward bias conditions. The experiment is measured and calculated impedance of a solar cell using square wave inputs and using sinusoidal signal inputs. The measurements are using the same basic instrument, such as digital oscilloscope, signal generator and audio amplifier. The measuring data are analyzed by the FFT technique on MATLAB. The measured solar cell impedances are plotted in a complex plane. In this experiment, the impedance loci obtained by the new method using square wave inputs, shown in figure 4, are compared with the impedance loci obtained by the previous method using sinusoidal, shown in figure 5. The impedance loci, at the same bias level 0.2 V, obtained from the two methods are compared in figure 6. It is found that the trends of the impedance loci determined by both methods are the same in semicircular shape.
Figure 4. Impedance loci of the 10 cm x 10 cm solar cell measured by this new method using square wave inputs at forward bias levels of 0.2, 0.3 and 0.4 V.
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Figure 5. Impedance loci of the 10 cm x 10 cm solar cell using sinusoidal inputs at forward bias levels of 0.2 V, 0.3 V and 0.4 V.
Figure 6. Comparison of impedance loci obtained by square wave inputs and sinusoidal inputs at forward biasing level of 0.2 V.
From figure 1, the ac equivalent circuit can be derived and modeled with a simplified equivalent circuit at the frequency ω consisting of one resistive component and one reactive component in series in the form of RPV+jXPV by the following equation:
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D. Chenvidhya, K. Kirtikara and C. Jivacate Z PV = R PV + jX PV 2 ⎤ ⎤ ⎡ ⎡ [(R sh + R d )R sh R d ] ω(R sh R d ) (C D + C T ) j − = RS + ⎢ ⎢ 2 2 ⎥ 2 2 ⎥ ⎣⎢ [ωR sh R d (C D + C T )] + [R sh + R d ] ⎦⎥ ⎣⎢ [ωR sh R d (C D + C T )] + [R sh + R d ] ⎦⎥
(3)
The series resistance of solar cell, Rs is constant at any bias level, and is given by the high frequency end interception of the impedance locus on the real axis. Due to the reactive component of solar cell impedance is close to zero at low frequency (ω→0) and consists of only the series resistance at high frequency (ω→∞). By the comparison results in figure 6, the values of Rs obtained by the square wave inputs method is 0.352 Ω, and Rs obtained by the sinusoidal inputs is 0.356 Ω. It is noted that the results determined by the two methods, using the same basic instrument, are not different. In addition, the other experiment is setup to compare the results obtained by the method with the results measured by the special instrument, impedance gain-phase analyzerSolartron Analytical or Frequency response analyzer (FRA).
4. DYNAMIC IMPEDANCE IN FREQUENCY DOMAIN ANALYSIS 4.1. Derivation of an AC Equivalent Circuit The ac equivalent circuit of a solar cell is shown in figure 7. In figure 7 (a), it shows the normal operating condition of cell. The figure 7 (b) shows the cell, without light generated current and load connecting, which the dynamic impedance are measured and derived in this condition. It is noted that Rd, CT and CD are voltage dependent.
(a) AC equivalent circuit of a solar cell connecting to a load ZL under illumination.
(b) AC equivalent circuit of a solar cell under dark condition.
Figure 7. AC equivalent circuit of a solar cell.
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Under dark condition when looking into the solar cell output port, normally connecting to a load, the solar cell impedance Zpv (ω) at a frequency ω can be shown to consist of one resistive component and one reactive component in series in the form of Rpv+jXpv. At each bias voltage V, the impedance Zpv(ω) can be expressed as the equation Z PV ( V , ω) = R PV ( V , ω) + jX PV ( V , ω) ⎡ ⎤ [{R sh + R d (V )}R sh R d (V ) ] = RS + ⎢ 2 2 ⎥ ⎢⎣ [ωR sh R d ( V ){C D ( V , ω) + C T ( V )}] + [R sh + R d ( V ) ] ⎥⎦ 2 ⎡ ⎤ ω{R sh R d ( V )} {C D ( V , ω) + C T ( V )} − j⎢ 2 2 ⎥ ⎣⎢ [ωR sh R d ( V ){C D ( V , ω) + C T ( V )}] + [R sh + R d ( V )] ⎦⎥
(4)
where RsRsh Rd(V) CD(V,ω) CT(V) ω
series resistance -shunt resistance dynamic resistance of diode diffusion capacitance transition capacitance -signal frequency
For simplicity, we drop V and ω in the equation (4) and write Z PV = R PV + jX PV ⎤ ⎡ [(R sh + R d )R sh R d ] − = RS + ⎢ 2 2 ⎥ ⎣⎢ [ωR sh R d (C D + C T )] + [R sh + R d ] ⎦⎥
2 ⎤ ⎡ ω(R sh R d ) (C D + C T ) j⎢ 2 2 ⎥ ⎣⎢ [ωR sh R d (C D + C T )] + [R sh + R d ] ⎦⎥
(5) Further, in the equation (5) we replace Rsh in parallel with Rd by Rp, and CT in parallel with CD as Cp. The simplified dynamic impedance equation can be rewritten as the equation
⎤ ⎡ ωR 2P C P ⎤ ⎡ RP Z PV = ⎢R S + ⎥ ⎥ − j⎢ 2 2 + 1 ω ( R C ) P P ⎦ ⎣ (ωR P C P ) + 1⎦ (6) ⎣ 4.2. Interpretations of Impedance Loci In the dark with forward bias, (1)
(2)
Rsh is much greater than Rd because diode resistance normally decreases with increasing conduction or biasing voltage, but Rsh is quite constant. Therefore, Rp is close to Rd. CD is more dominant than CT.
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(4)
The reactive component of the solar cell dynamic impedance is close to zero at low frequency (ω → 0). Moreover, the impedance consists of only the series resistance at high frequency (ω → ∞). The impedance locus on the complex plane is close to semi-circular.
The two intercepts of the impedance locus on the real axis are approximately Rs and Rs+Rp. Rp is close to Rd in this case. In the dark with reverse bias, (1) (2) (3)
Rd is much greater than Rsh (in case of low level of biasing). Therefore, Rp is close to Rsh, CT is more dominant than CD. The reactive component of solar cell dynamic impedance is close to zero at low frequency (ω → 0). The impedance consists of only the series resistance at high frequency (ω → ∞). The impedance locus on the complex plane is close to semicircular.
The two intercepts of the impedance locus on the real axis are approximately Rs and Rs+Rp. Rp is close to Rsh in this case.
Figure 8. Impedance loci of a PV cell or module at low (V1), intermediate (V2) and high (V3) biasing voltages.
It can be shown that the equation describing each semi-circular impedance locus is of the form ⎡ ⎡ R R − R S (R sh + R d )⎤ ⎛ R sh R d + R S (R sh + R d ) ⎞⎤ ⎟⎟⎥ + X 2PV = ⎢ sh d ⎢R PV − ⎜⎜ ⎥ 2(R sh + R d ) 2(R sh + R d ) ⎣ ⎦ ⎝ ⎠⎦ ⎣ 2
At any biasing voltages, the equation (7) can be simplified as
2
(7)
Dynamic Impedance Characterization of Solar Cells and PV Modules… 2
⎡ ⎡R − RS ⎤ ⎛ R P + R S ⎞⎤ ⎟⎥ + X 2PV = ⎢ P ⎢R PV − ⎜ ⎥ 2 2 ⎦ ⎣ ⎠⎦ ⎝ ⎣
311
2
(8)
The equation (8) when expressed in terms of the magnitude |Zpv| and the argument θ of the impedance Zpv can be written as
Z PV − (R P + R S ) Z PV cos θ + R P R S = 0 2
(9)
In case of, ω = 0 or dc resistance of solar cell, therefore, equation (6) turns into
Z PV = R S + R p Zpv is corresponding to Rdc in static model of solar cell in equation (2).
Figure 9. Impedance loci of the module under reverse bias, plotted in the complex Zpv plane.
By the derivations of an ac equivalent circuit of solar cell and the interpretations of impedance loci in a complex plane, it is found that the impedance loci in the reverse bias conditions can yield the parameters of a cell or a PV module, such as the series resistance, the shunt resistance. Therefore, the measurement on the dynamic impedance of a 20 Wp crystalline silicon PV module is setup to confirm the above principle. The measurement is done in the dark with any reverse bias levels, and the impedance loci are plotted in complex plane as figure 9. It is the first time that a report on commercial PV module dynamic impedance is made. At low reverse biasing (0.3 and 0.5 V/cell), the two impedance loci are closely located implying that the impedances are nearly identical. We know that the intercept is equaled to Rd
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in parallel with Rsh, Rd is voltage dependent and Rsh is voltage independent, therefore, the two coincident loci imply that Rd is much greater than Rsh and the intercept on the real axis of Zpv is basically Rsh. The high frequency end intercept is approximately Rs. For this tested module Rs is 0.79Ω. When we plot the real axis intercepts at low frequency ends of the loci and the biasing voltage, we obtain the relationship between Rp (of Zpv at ω → 0) and the voltage. The plot is shown in figure 10. 160 140 120
Rp (k Ω)
100 80 60 40 20 0 0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
V (Volt/cell)
Figure 10.The relationship of Rp (of Zpv at ω → 0) versus biasing level.
4.3.Voltage and Frequency Dependencies of RPV and XPV Voltage and Frequency Dependencies of a Cell From the loci of impedances Zpv, we can determine the following: (a) Rpv, Xpv, |Zpv| and argument of Zpv. The equations (4), (5) and (6) give the relationship between the above quantities with the equivalent components and the frequency. (b) Rs from the high frequency intercepts and Rsh from the low frequency intercepts.
Forward Bias
Frequency Response Plots Based on the results shown in figure 4, we calculate the Rpv, Xpv, |Zpv| and argument of Zpv of the cell. The results are shown as figure 11, 12, 13 and 14.
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20 18 16
Rpv (Ω )
14 12 10 8 6 4 2
0.2V
.
0.3V
1.E+05
1.E+04
f (Hz)
1.E+03
1.E+02
1.E+01
1.E+00
0
0.4V
Figure 11. Rpv of the cell as a function of frequency.
0 -1 -2
Xpv (Ω )
-3 -4 -5 -6 -7 -8 -9
0.2V
Figure 12. Xpv of the cell as a function of frequency.
0.3V
0.4V
1.E+05
1.E+04
f (Hz)
1.E+03
1.E+02
1.E+01
1.E+00
It is seen that the complex impedance plot yields information on Rs and Rd. However, the Rd vs. frequency plot gives an additional information on the frequency and the voltage dependent nature of Rd. At low forward bias voltage of 0.2 V Rd is about 15.53Ω and remains constant and dominant until a frequency of 100 Hz. However, at higher bias voltage Rd decreases. Moreover, Rd remains constant and dominant upto a higher frequency range, about 1 kHz in our cell.
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|Zpv| (Ω )
14 12 10 8 6 4 2
0.2V
0.3V
1.E+05
1.E+04
f (Hz)
1.E+03
1.E+02
1.E+01
1.E+00
0
0.4V
Figure 13. |Zpv| of the cell as a function of frequency.
0 -10
Arg. Zpv (deg.)
-20 -30 -40 -50 -60 -70 -80
0.2V
0.3V
Figure 14. Arg. of Zpv of the cell as a function of frequency.
0.4V
1.E+05
1.E+04
f (Hz)
1.E+03
1.E+02
1.E+01
1.E+00
Frequency Dependence of Capacitance From the Rpv frequency plot (11), the Xpv frequency plot (12) and the equations (4) and (5), Cp (CD in parallel with CT) has been determined. The calculated Cp at the bias voltage of 0.2 V are 3.19, 5.45 and 5.85 μF at 100, 500 Hz and 1 kHz. It may be recalled that the transition capacitance CT is voltage dependent whereas
Dynamic Impedance Characterization of Solar Cells and PV Modules…
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the diffusion capacitance CD is both voltage and frequency dependent. Moreover, CD increases with frequency. From the above results, it can be seen that Cp, and hence CD, increases with frequency as expected. CD and CT can separately be determined. By selecting an impedance locus at a fixed bias voltage, therefore CT is fixed, CD can be calculated.
Reverse Bias Based on the results of the cell in reverse bias condition, we calculate the Rpv, Xpv, |Zpv| and argument of Zpv of the cell. The results are shown as figure 15, 16, 17 and 18. 200
Rpv (Ω)
160
120
80
40
1.E+04
1.E+05
1.E+04
1.E+05
1.E+03
1.E+02
1.E+01
1.E+00
0
f (Hz) 0.3V
0.5V
0.9V
1.5V
1.E+03
1.E+02
1.E+01
1.E+00
Figure 15. Rpv of the cell as a function of frequency. f (Hz)
0
Xpv (Ω)
-20
-40
-60
-80
-100
0.3V
0.5V
Figure 16. Xpv of the cell as a function of frequency.
0.9V
1.5V
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|Zpv| (Ω)
160
120
80
40
1.E+05
1.E+04
1.E+03
1.E+02
1.E+01
1.E+00
0
f (Hz) 0.3V
0.5V
0.9V 1.5V
Figure 17. |Zpv| of the cell as a function of frequency.
0
Arg. Zpv (deg.)
-2 0
-4 0
-6 0
-8 0
-1 0 0
0 .3 V
0 .5 V
0 .9 V
Figure 18. Arg. of Zpv of the cell as a function of frequency.
1 .5 V
1.E+05
f (H z )
1.E+04
1.E+03
1.E+02
1.E+01
1.E+00
Voltage and Frequency Dependence of Rpv and Xpv of A PV Module Based on similar procedures in calculating the Rpv, Xpv, |Zpv| and Arg. of Zpv of the cell, we undertake similar calculation of those of the module. We use the results shown in figure 9 (impedance loci of the module under reverse bias of 0.3, 0.5, 0.9, 1.2 and 1.5 V/cell). Figure 19 to 22 show the frequency response plots. From the frequency plot of Rpv, figure 19, we see that the shunt resistance of the module (Rpv at low frequency and the low bias voltage of 0.3 V/cell) is about 143 kΩ. This gives Rsh of each cell of 4.33 kΩ.
Dynamic Impedance Characterization of Solar Cells and PV Modules…
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1.6E+05 1.4E+05 1.2E+05
Rpv (Ω )
1.0E+05 8.0E+04 6.0E+04 4.0E+04 2.0E+04 0.0E+00 1.E+00
1.E+01
1.E+02
0.3V
0.5V
1.E+03
f (Hz) 0.9V
1.2V
1.E+04
1.E+05
1.5V/cell
Figure 19. Rpv of the module as a function of frequency.
However, when we consider the frequency dependent nature of Rpv of the selected test cell and that of the module, we see that Rpv of the module drops more rapidly with frequency. This implies that, per cell basis, Cp (CD in parallel with CT) of the module is larger than that of the cell. f (Hz) 1.E+00 0.0E+00
1.E+01
1.E+02
1.E+03
-1.0E+04 -2.0E+04
Xpv (Ω )
-3.0E+04 -4.0E+04 -5.0E+04 -6.0E+04 -7.0E+04 -8.0E+04
0.3V
0.5V
0.9V
Figure 20. Xpv of the module as a function of frequency.
1.2V
1.5V/cell
1.E+04
1.E+05
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|Zpv| (Ω)
1.0E +05 8.0E +04 6.0E +04 4.0E +04 2.0E +04 0.0E +00 1.E +00
1.E+01
1.E +02
0.3V
0.5V
1.E +03
f (H z) 0.9V
1.2V
1.E+04
1.E +05
1.5V/cell
Figure 21. |Zpv| of the module as a function of frequency.
In this section, it is shown that the frequency range of which the solar cells and module impedances rapidly change is in the region of few tens to few hundreds Hz. However, changes due to cloud movements are slow, over few seconds or few minutes period. So we are of the view that the solar cells impedances variation would largely be caused by voltage changes arising: -
in some part due to cloud and radiation fluctuation and in other part due to electrical nature of power conditioning units, loads and distribution network. We cannot yet be certain about the relative importance of these electrical entities connected to the PV array. f (H z )
Arg. Zpv (deg.)
1 .E + 0 0 0 .0 E + 0 0
1 .E + 0 1
1 .E + 0 2
1 .E + 0 3
-3 .0 E + 0 1
-6 .0 E + 0 1
-9 .0 E + 0 1
0 .3 V
0 .5 V
0 .9 V
1 .2 V
Figure 22. Arg. of Zpv of the module as a function of frequency.
1 .5 V /c e ll
1 .E + 0 4
1 .E + 0 5
Dynamic Impedance Characterization of Solar Cells and PV Modules…
319
5. PV MODULE DIAGNOSTIC METHOD USING DYNAMIC IMPEDANCE From the static characteristic of solar cell, the series resistance, shunt resistance, fill factor and efficiency can be calculated from the illuminated current-voltage curve. These parameters determine performance of a solar cell or a module. Cells or modules having low Rs, high Rsh and high FF are recognized as having good quality. The current-voltage characteristic of a cell having a high fill factor is rather rectangular-like while that of a cell with a low fill factor is triangular-like. Based on the derivation outlined in the Section 4, in the complex plane, impedance loci of solar cells with low Rs would have the high frequency intercepts lying close to the origin. On the other hand, impedance loci of solar cells having large Rsh would have the low frequency intercepts lying towards the right hand side of the real axis. Thus, based only on measuring the dynamic impedance of solar cells and plot them in the complex plane, without having to determine their static characteristics, one can quickly distinguish between solar cells having good quality (low Rs and high Rsh) and those having low quality (high Rs and low Rsh). Comparatively speaking, the impe-dance loci of good solar cells would be semi-circularly large.
(a) Schematic picture of static characteristics of two PV modules, M1 being of good quality and M2 being of low quality.
(b) Schematic picture of impedance loci of two PV modules, M1 and M2,
Figure 23. Comparative of schematic pictures of the static characteristics and impedance loci of two PV modules being of good quality and low quality.
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Figure 23 shows a schematic picture of current-voltage static characteristics and dynamic characteristics of solar cells of good and low quality. Two modules, one having a high fill factor of about 0.7 and the other low fill factor of about 0.5, having been selected from a number of PV modules. Illuminated static I-V characteristics of the modules are determined. Static parameters obtained for each module are the open circuit voltage (Voc), the short circuit current (Isc), the module efficiency (η) and the fill factor (FF). The I-V characteristics of the two modules are compared in figure 24. 3.00
2.50
Current (A)
2.00
1.50
Module1 Module1: Pm=28.15W (13.8V,2.04A) Isc=2.20A Voc=18.0V FF=71.08%
1.00
Module2 Module2: Pm=22.40W (10.0V,2.24A) Isc=2.52A Voc=18.2V FF=48.84%
0.50 Test Conditions: Radiation of 780 W/m2 and Module Temperature of 43C
0.00 0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
18.0
20.0
Voltage (V)
Figure 24. Illuminated Static I-V Characteristics of Two Modules.
The dynamic impedances of the modules under dark condition with reverse biasing are measured from their frequency responses. Measurement of dynamic impedances of each module yields its Rs, Rsh, dynamic resistance (Rd), diffusion capacitance (CD) and transition capacitance (CT). The dynamic impedance loci, under a biasing voltage of 0.3 V/cell, are plotted in figure 25. Rs of the Module 1 and the Module 2 are 0.93 and 3.13 Ω, respectively. On the other hand, Rsh of the Module 1 and the Module 2 are 52.6 and 13.95 kΩ, respectively. From the comparison, we see the well established correspondence between the FF, Rs, and Rsh of solar cell modules, i.e. low Rs and high Rsh results in high FF modules. We can say that dynamic characterization can yield qualitative information on comparative fill factors of modules, but not quantitative values. However, other essential electrical parameters of modules required to predict the module–grid interaction can only be obtained from the dynamic characterization. This becomes essential as the trend in solar cell applications are in the grid interactive applications. If we are mainly interested in investigating the module-grid interaction, information from the dynamic characterization of modules is necessary and sufficient. We note that the same information on the module dynamic characteristics provide an adequate qualitative nature of fill factors as well.
Dynamic Impedance Characterization of Solar Cells and PV Modules… 0.000 0.000
0.002
321
0.004
-0.020
Rpv (k ohm)
-0.040
0 -0.060
0
-0.080
-5
10
20
30
40
50
60
ω
Xpv (k ohm)
-10
-15
-20
-25
Module1 Module2 Module 1: Rs=0.93ohm, Rsh=52.6 k ohm Module 2: Rs=3.13ohm,Rsh=13.95kohm
-30
Figure 25. Dynamic Impedance Loci of Two Modules (Dark Reverse Bias of 0.3 V/Cell).
6. DYNAMIC RESPONSE IN TIME DOMAIN ANALYSIS An alternative method can also analyze dynamic characteristics of a solar cell from time domain responses. In previous sections of this chapter, the method of measurements and derivations of dynamic impedances of a solar cell or a PV module are done in frequency domain analysis. A solar cell or module are measured by impedance spectroscopy method using sinusoidal signal inputs in general, and a new proposed method measures by using square wave inputs with FFT technique to analyze harmonic contents of the output response. Both measuring results are analyzed in frequency domain analysis, and plotted the magnitudes and the arguments of impedances of solar cell in a complex plane. In the same measurement on the new characterization method for dynamic impedances using square wave inputs in section 3, the time constants of a solar cell or module can be simultaneously obtained, in the time domain responses, at each bias condition. Time responses can be directly observed and analyzed in the time domain whereas the frequency domain analysis can be done by using FFT to determine harmonics contents. Under dark conditions at each bias voltage, the dynamic impedance of a solar cell, ZPV(ω) can be modeled with one resistive component and one reactive component in series in form of RPV+jXPV. The impedance can be expressed in function of input signal frequency ω
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as the equation (4), and ZPV can be rewritten in simplicity form in equation (5) and (6) detailed in section 4. The impedance loci of a solar cell or PV module can be described in frequency domain analysis as frequency response plots or impedance plotted in a complex plane at any bias levels, as shown in figure 8. In the time domain analysis with the same measurement using square wave inputs, a response time or time constant of a solar cell, at any bias voltage V, can be derived and written as equation (10) Time Constant =
(10)
R s R sh R d (V)[(CT (V)) + C D (V, ω)] R d (V)R sh + R s [R d (V) + R sh ]
The time constant can be yielded from the slope of output response curve at the transition point of a square wave. It is noted that some components in an equivalent circuit model are voltage and frequency dependencies as mentioned in section 4. At any fixed bias level, CD is only one component that is voltage dependence. It is observed that the time constants are also varied with frequency. From the same measured results using square wave inputs, the time constants can be analyzed and plotted as a function of frequency, at any bias voltages either forward and reverse conditions. These are shown in figure 26 and 27. 250
200
0.2 Volt
Time Constant (µS)
0.3 Volt 0.4 Volt
150
100
50
0 10
100
1000
10000
100000
Frequency (Hz)
Figure 26. Relation between frequency and time constant on forward bias.
As shown in figure 26 and 27, it is observed that time constants of a solar cell are also voltage and frequency dependencies. Time constants in reverse bias conditions rapidly drop in lower frequency than in forward bias conditions. Time constants under reverse bias conditions are larger than under forward bias conditions. This is due to the dominance of the junction capacitance in reverse bias, especially at low level. However, the effect of the junction capacitance should prominent in cells with good junction quality. The cell that we use has low junction quality reflecting in low Rsh reported prviously.
Dynamic Impedance Characterization of Solar Cells and PV Modules…
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1000
0.3 Volt
Time Constant (µS)
750
0.5 Volt 0.7 Volt
500
250
0 10
100
1000
10000
100000
Frequency (Hz)
Figure 27. Relation between frequency and time constant on reverse bias.
From the results, the relationship of bias voltage and the time constant can be plotted in Figure 28 and 29 to illustrate that at the same frequency, the time constants decrease with increasing voltages. We note that the voltage dependent components are Rd, CT and CD. We do not determine the relative dominance between them. In principle, we can use this method to determine all the equivalent components. This will be reported separately. 200
30 Hz
Time Constant (µS)
150
500 Hz 4 kHz 10 kHz
100
50
0 0.15
0.2
0.25
0.3
0.35
0.4
Bias Voltage (V)
Figure 28. Relation between bias voltage and the time constant on forward bias.
0.45
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50 Hz 200 Hz 700 Hz Time Constant (µS)
750
3 kHz
500
250
0 0.2
0.3
0.4
0.5
0.6
0.7
0.8
Bias Voltage (V)
Figure 29. Relation between bias voltage and the time constant on reverse bias.
As we mention earlier, from one single set of measurements this method allows simultaneous analyses in both the frequency domain and the time domain. The relationship between the time constant and the bias voltage and frequency can be used to determine the AC equivalent circuit components. If the frequency domain analysis is carried out with consistency of the equivalent components, then comparison of results, as obtained from both domains, can be compared.
7. CONCLUSION In this chapter, dynamic impedances of a solar cell or a PV module can be characterized and derived in both frequency domain analysis and time domain analysis. A new characterization method for solar cell dynamic impedance is proposed, based on frequency domain analysis. By this method, a solar cell is measured in the dark by using a basic instrument, such as a digital oscilloscope, signal generator and audio amplifier. The new simple method for measuring solar cell impedances using square wave inputs instead of sinusoidal inputs reported earlier. The impedance loci are calculated from the output responses by FFT technique to analyze harmonics contents, and then plotted in a complex plane. Comparison is made with results obtained from the measurement, based on the same principle, using sinusoidal inputs. It is confirmed the comparable results. The dynamic impedance of a solar cell or a PV module in the dark can be derived in a closed form equation in terms of frequency dependent and voltage dependent resistance and
Dynamic Impedance Characterization of Solar Cells and PV Modules…
325
capacitance in reverse and forward bias conditions. The dynamic parameters in an AC equivalent circuit, in addition to the DC model, consisting of dynamic resistance, diffusion capacitance and transition capacitance are also derived in the frequency domain analysis. Impedance loci of solar cells are separately interpreted in forward bias and reverse bias conditions. Intercepts of each impedance locus yield series, shunt and dynamic resistance of a cell or a module. Moreover, the dynamic characteristics in the dark can also diagnose the quality of PV modules. Comparison of the static I-V characteristics and the dynamic impedance of PV modules having low and high fill factors are made. It is noted that the dynamic characteristics of modules can provide an adequate qualitative nature of respective fill factors as well. Another new analytical method is made in the same measurement of dynamic impedance of a solar cell using the square wave inputs method, both in the frequency domain analysis and in time domain analysis. Dynamic impedance parameters are analyzed in the frequency domain, and the time constants are analyzed in time domain. Dynamic impedance parameters and time constants of solar cells or PV modules can be simultaneously obtained at each bias condition. The advantages of this simple measuring method are reduction in measuring steps and yielding of dynamic parameters and time constants in single measurement. However, the dynamic impedance characterization method is not only done on crystalline silicon solar cells, but also done on polycrystalline and amorphous silicon cells and modules, and their results will be separately revealed at a later date. Knowledge of dynamic impedance characterization of solar cells and modules will lead to better understanding of characteristics of PV grid-connected systems in distribution networks, and be used to diagnose the quality of PV modules.
ACKNOWLEDGMENTS The authors are grateful to the Clean Energy Systems Group (CES), the Pilot Plant Development and Training Institute (PDTI), the Department of Electrical Engineering Department, the School of Energy and Materials of the University for equipment and facilities. We would like to thank Dr. Veerapol Monyakul, Mr. Nattavut Chayavanich, Mrs. Tasanee Chayavanich, Mr. Jutturit Thongpron and Mr. Chamnan Limsakul and the staff of CES for their valuable discussion and comments.
REFERENCES [1] [2] [3] [4]
Rauschenbach, H.S. Solar Cell Array Design Handbook; Van Nostrand Reinhold; New York; 1980. Pierret, R.F.; Semiconductor Device Fundamentals; Addison-Wesley, Reading, M.A.; 1996. Mueller, R.L.; Wallance, M.T.; Illes, P. Scaling nominal solar cell impedances for array design, WCPEC-1, December 5-9, 1994. 2034-2037. Suresh, M.S. Measurement of solar cell parameters using impedance spectroscopy, Sol Energy Mater Sol. Cells. 1995, vol. 43, 21-28.
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Kumar, R.A.; Suresh, M.S.; Nagaraju, J. Measurement of AC parameters for Gallium Arsenide (GaAs/Ge) solar cell by impedance spectroscopy, IEEE Trans Electron Devices. 2001, vol.48, 2177-2179. [6] Chenvidhya, D. PV Grid-Connected Systems for Residential Distribution System: Dynamic Impedance Characterization of Solar Cells and PV modules; Doctor of Engineering Thesis, King Mongkut’s University of Technology Thonburi; Bangkok, Thailand; 2002. [7] Chenvidhya, D.; Kirtikara, K.; Jivacate, C. A new characterization method for solar cell dynamic impedance; Sol. Energy Mater Sol. Cells. 2003, vol. 80, 459-464. [8] Chenvidhya, D.; Kirtikara, K.; Jivacate, C. PV module dynamic impedance and its voltage and frequency dependencies; Sol. Energy Mater Sol. Cells. 2005, vol. 86, 243251. [9] Chenvidhya, D.; Kirtikara, K.; Jivacate, C. On dynamic and static I-V characteristics of solar cell modules having low and high fill factors, WCPEC-3, May 12-16, 2003. [10] Wongyao, N.; Kirtikara, K.; Jivacate, C.; Chenvidhya, D. Time Responses of a Crystalline Silicon Solar Cell to Varying Light Inputs: Equivalent Components Determination, PVSEC-14, January 26-30, 2004. [11] Chenvidhya, D.; Limsakul, C.; Thongpron, J.; Kirtikara, K.; Jivacate, C. Determination of Solar Cell Dynamic Parameters from Time Domain Responses, PVSEC-14, January 26-30, 2004.
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 327-365
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 11
WIND ENERGY TECHNOLOGY OVERVIEW* United States Department of the Interior, Bureau of Land Management SUMMARY Modern wind energy technologies rely heavily on the very complex scientific discipline of fluid dynamics (which includes the study of the atmosphere) and the equally complex engineering discipline of aerodynamics. A comprehensive treatment of either of these disciplines is well beyond the scope of this programmatic environmental impact statement (PEIS). The discussions that follow are intended only to establish a basic understanding of wind technology and the factors that control its evolution. References are provided for those who wish to have a more detailed understanding of wind technology. This appendix provides an overview of the fundamentals of wind energy and wind energy technologies, describes the major components of modern wind turbines, and introduces terms that are unique to the field of electric power generation using wind energy. Important site characteristics and critical engineering aspects of wind energy technologies are presented, and their respective influences on future development decisions are discussed.[1] An overview of the current state of wind energy technology and ongoing research and development (R&D) is provided. Descriptions of a typical wind energy project and the major actions associated with each phase of development — site monitoring and testing, construction, operation, and decommissioning — are presented in Chapter 3 of this PEIS.
*
A version of this chapter was also published in Wind Energy: Technology, Commercial Projects and Laws edited by Marco A. Telles published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research.
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United States Department of the Interior, Bureau of Land Management
1. IMPORTANT TERMS AND CONVENTIONS Discussions in the following sections introduce important terms and conventions, some of which are unique to the wind energy industry. The terms and conventions are described in the text where they are first introduced. Additional details are provided in the glossary of this PEIS (Chapter 10).
2. WIND ENERGY Wind represents the kinetic energy of the atmosphere. In simplest terms, wind is the movement of air in the earth’s atmosphere relative to a fixed point on the earth’s surface. The major initiator of that movement is the uneven heating of the earth’s surface by solar radiation. The materials that compose the patchwork of the earth’s surface (e.g., vegetation, exposed rock, snow/ice cover, and water) react differently to solar radiation, absorbing heat energy and reflecting some of that energy back into the atmosphere at different rates. The result is a nonequilibrium condition in which adjacent air masses have different heat energies and, as a result of adiabatic expansion or compression, different barometric pressures. Wind is one result of the atmosphere’s attempt to normalize those differences and return to the lowest possible equilibrium state. The rotation of the earth around its axis initially causes a generally uniform global flow of air from west to east; however, many other factors add complexity to the dynamics of the earth’s atmosphere. The text box on the next page has additional information on atmospheric motion.
3. EXTRACTING THE POWER OF THE WIND The kinetic energy of wind is related to its velocity. This relationship is represented mathematically by the following equation: P=½×ρ×A×V3,
(1)
where P = wind power (W), ρ = air density (typically 2.70 lb/m3 [1.225 kg/m3] at sea level and 59 F [15 C]), A = cross-sectional area of the wind being measured (m2), and V = mean velocity of the wind within the measured cross section (m/s). A careful examination of this power equation reveals the following important fundamental truths about wind energy. Both the air’s density and the cross-sectional area of the wind being intercepted have a direct relationship to wind power. The air’s density varies with temperature, elevation, and humidity, but, in all instances, the density remains relatively low. Thus, any changes to air density have a minimal effect on the wind’s inherent power. Doubling the cross-sectional area of a wind front leads to a doubling of the intrinsic power. Most important to wind farmers is the fact that the wind’s power is proportional to the cube of
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its average velocity. Thus, a doubling of the average or mean wind speed results in an eightfold increase in its power. As a practical matter, wind energy technologists focus on the wind’s “power density” or power per unit area of wind being intercepted, expressed in W/m2. Simple manipulation of the above power equation allows power density to be calculated by using the following expression: Power density = P/A = ½ × ρ × V 3.
(2)
The height of the wind above the earth’s surface also affects the average wind speed. Frictional drag and obstructions near the surface of the earth generally retard wind speed and induce a phenomenon known as wind shear (the change in a wind’s speed with elevation). The rate at which wind speed increases with height varies on the basis of local conditions of the topography, terrain, and climate, with the greatest rates of increase observed over the roughest terrain. Unique local conditions notwithstanding, a reliable approximation is that wind speed increases approximately 10% with each doubling of height (Gipe 1995). Understanding Atmospheric Motion
Wind represents the earth’s atmosphere in motion. Understanding the development and progression of wind involves understanding the complex array of forces that constantly act upon the earth’s atmosphere and cause its continuous motion. The velocity, direction, and variability of wind are products of those collective forces. The major forces at play include basic laws of thermodynamics, the force of the earth’s gravity, frictional forces and obstructions imposed by the topography of the earth’s surface, and the Coriolis effect caused by the earth’s rotation. Thermodynamics governs the ways in which a given air mass behaves as it exchanges heat energy with its surroundings. Although the atmosphere’s density is quite low, the gravitational forces of the earth nevertheless exert a constant downward force on the atmosphere that continuously affects its behavior. It can be intuitively understood that the surface of the earth over which wind passes can also have some influence on wind, especially in the planetary boundary layer (the portion of the atmosphere immediately above the earth’s surface). Topography can either increase or decrease wind speed in localized areas. Topography can also contribute to or induce wind shear (the rapid change of direction of wind with altitude). When other overriding forces are absent, topographic obstructions and friction at the earth’s surface generally result in higher wind speeds at higher altitudes, with the highest wind speeds being achieved when all surface influences disappear. This wind is called the geostropic wind. The height or thickness of the planetary boundary layer varies over the surface of the earth (and actually changes slightly over the course of the day as a result of solar heating), reaching to thousands of feet in some locations. For the practical purpose of harvesting wind energy, the wind regime of greatest interest
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United States Department of the Interior, Bureau of Land Management is contained completely within the boundary layer and, ideally, is composed largely of geostrophic wind. The force commonly referred to as the Coriolis effect is more difficult to comprehend. Although it is easy to understand wind as being the motion of the atmosphere relative to one’s point of observation on the surface of the earth, it is also important to recognize that one’s point of observation, while it is fixed on the earth’s surface, is not fixed in space, and it is itself moving as the result of both the earth’s rotation and its orbit around the sun. The Coriolis effect is most easily defined as that apparent force on the wind that would not have otherwise occurred except for the earth’s rotation and movement through space. It is manifested as a bending or redirection of the wind into circular patterns as air masses move from high-pressure to lowpressure areas. The magnitude of the Coriolis effect is a function of latitude. Winds directly above the earth’s equator and moving in a direction parallel to the earth’s axis of rotation experience very little in the way of a Coriolis effect. Winds occurring at other latitudes experience a Coriolis effect that is roughly proportional to the distance of that latitude from the equator. This fact can be easily understood by recognizing that any given point on the earth’s surface along its equator is traveling at roughly 373 mph (600 km/h) around the earth’s axis of rotation, while both the north and south poles have virtually no angular momentum. Other characteristics of atmospheric motion that are of great practical significance to wind energy development are those factors that contribute to its variability over both time and geographic location. These factors include topography-induced variations, annual and seasonal wind speed variability, synoptic variations (resulting from or influenced by broad-area weather patterns and storm fronts), diurnal variations (reflecting changes in levels of solar radiation over a 24-hour cycle), turbulence (the uneven, chaotic motion of air), wind gusts, and extreme wind speeds. All such factors are critical to identifying ideal wind regimes and to designing wind turbines that can capture wind energy with the greatest efficiency while still withstanding the forces to which they will be exposed over their lifetimes. Since most of these forces exhibit their greatest influence on atmospheric motion in the planetary boundary layer (the portion of the atmosphere in which wind turbines normally operate), their influence on siting decisions and turbine design is substantial. While many of these variability factors can be intuitively understood, many others cannot. This uncertainty leads directly to the difficulties that now exist in accurately predicting weather. This uncertainty also greatly increases the complexity involved in selecting and developing the ideal wind farm.
Because wind flows not only more quickly but also more uniformly as the elevation from the earth’s surface increases, the power contained in the wind is both greater and more easily extractable at higher elevations. Because turbulence decreases as the distance from surface obstructions increases, power actually increases faster with height than the relationship of
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power to the cube of the wind’s speed would indicate. Thus, for example, a fivefold increase in height results in nearly a doubling of available wind power. To take advantage of this relationship, wind turbine developers pursue designs that not only allow the capture of the greatest cross-sectional area of wind but also allow the capture of wind at the highest practical elevation possible. There are trade-offs, however. Higher turbine elevations require more substantial support systems (both towers and their foundations) and substantially greater initial investments. Higher altitudes also subject the rotor and the nacelle, as well as the tower itself, to greater aerodynamic forces, which can require extensive design modifications and can shorten the expected operating lives of the tower and its components. Finally, operation and maintenance (O&M) activities can also be more complicated and costly with increases in the elevation of the rotor.
3.1. Characterizing Candidate Sites and Site Selection The wind energy industry has adopted a convention by which annual average wind power densities and speeds are divided into seven power classes. It is also common practice to represent wind speed at a specified elevation above the land surface to allow comparative evaluations of sites within a given class to be made. To facilitate the identification of ideal wind regimes, the U.S. Department of Energy’s (DOE’s) National Renewable Energy Laboratory (NREL) has developed comprehensive wind maps for the United States that show the spatial distributions of these power classes. These maps were derived from meteorological data collected at thousands of locations. Figure 1 shows the wind resource distribution map for the contiguous 48 states. (Power density maps have also been developed for Alaska and Hawaii. However, since lands administered by the Bureau of Land Management [BLM] in those states are outside the scope of this PEIS, maps for those two states are not displayed here.) A more detailed discussion on the distribution of ideal wind regimes and more detailed maps showing ideal wind regimes on BLM-administered lands and their locations relative to existing electric power transmission lines are provided in Appendix B. Developers using currently available wind turbine technologies have found that sites with wind power densities at Class 4 or higher represent economically viable sites for a wind farm. These wind maps serve only as a preliminary screening tool for site selection. Developers must still investigate the properties of the wind regime at any candidate site in much greater detail before assigning a practical value to the site and deciding on a course of development. The principal limitation to the wind power distribution map displayed here is that it shows only the annualized average wind speeds and power densities. Two sites with identical annual average wind speeds and power densities may have arrived at those average values by entirely different paths. Sites whose average speeds and power densities are the product of widely varying instantaneous wind speeds over time are much less attractive than sites displaying lesser wind speed variations over time with few or no instances of excessive, potentially damaging wind speeds.
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Figure 1. Wind Resource Distribution Map for the 48 Contiguous United States (Source: EERE 2004b)
The developer must understand the time variability of the instantaneous wind speed. The ideal wind regime is one at which the instantaneous wind speed is near the upper limit of the operating range of commercially available wind turbines for the greatest percentage of time over the course of the year, thus maximizing annual energy production. (See Section 5.3 for additional discussion on turbine operating ranges.) Therefore, the first step in any future wind farm development involves the collection of meteorological data (primarily wind speed and direction) at a potential candidate site for at least 1 year. For candidate sites in complex terrain or in areas with weather extremes, as many as 3 years of meteorological data may be necessary to support site development decisions. To realize their fullest value, the data must be collected at various locations within the site to support “micrositing” decisions (e.g., selecting the precise positioning of a wind turbine) and at various elevations to validate wind turbine decisions (e.g., selecting a turbine model and tower in which the rotor hub can be positioned at or near the elevation of maximum wind speed within its operating range and at a sufficiently high elevation so as to be above the chaotic and potentially damaging wind turbulence at or near the ground surface).[2] When the wind regime is precisely mapped, wind farms can consist of a variety of turbine models operating at different hub elevations to reach maximum sitewide efficiency. However, this type of composition complicates site development, construction, operation, and maintenance and may also complicate the collection and conditioning of the electric power that is generated. The use of various turbine models is unlikely; however, placing turbines at different hub elevations is technically feasible.
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3.2. Other Factors in Site Selection Site selection primarily involves matching wind regimes to turbine performance characteristics. The wind’s elevation profiles and variability over time and location, as well as the range of extant wind speeds, must be matched to turbine designs (and vice versa). All such efforts to find the perfect match are conducted with the intention of maximizing the capacity factor of each turbine. This capacity factor is the ratio of expected energy output to the turbine’s maximum rated power capacity, expressed as an annualized percentage (see additional discussion on capacity factors in Section 5.3). A wind farm’s expected capacity factor is the single greatest influence on the farm’s return on investment (ROI). Obviously, selecting a location with the highest average wind speed within the operating range of the proposed wind turbine for the greatest percentage of time is a principal site selection objective. In practice, many other circumstantial factors, such as transmission access and road access, substantially affect the costs of site development and O&M; therefore, they also play a key role in site selection.
4. WIND TURBINE TECHNOLOGIES The centuries-old history of efforts to harvest wind energy is fascinating, and an extensive discussion is beyond the scope of this PEIS. However, many excellent sources exist, including Gipe (1995), Hau (2000), Burton et al. (2001), Manwell et al. (2002), and Wilson (1994) and the references therein, as well as Web sites maintained by the DOE Office of Energy Efficiency and Renewable Energy (EERE 2004a), NREL (2004a), Sandia National Laboratories (2004a), the National Wind Coordinating Committee (NWCC 2004), and the American Wind Energy Association (AWEA 2004c). Sailing ships probably represent the earliest attempt to harness the wind. Windmills, the most familiar wind technology, have been used for myriad applications, most commonly to grind grain and pump water and crude oil. There is speculation that the earliest windmills went into service more than 3,000 years ago. More reliable historical documentation dates the earliest use of windmills to 200 B.C. in Persia (now Iraq) (Sandia National Laboratories 2004a). There is also evidence that windmills may have been used much earlier in China to drain rice fields, but the earliest dates of service are unclear. The use of windmills to generate electricity began in the late 19th century to provide electric power in rural areas, before the advent of far-ranging power transmission and distribution systems. Many windmills used in rural areas of Europe and the United States to pump water were converted for the production of electricity. Windmills such as the one shown in Figure 2 were used to generate small amounts of electricity, normally to satisfy the demand for electric power in the immediate vicinity. Windmills are the progenitors of the modern wind turbine.[3] In fact, they share a common fundamental function: converting the kinetic energy of the wind into the mechanical energy of a rotating shaft. Throughout the development and evolution of the windmill, a variety of designs have been explored. The evolution of wind turbine design has followed a similar path. The earliest windmills had their axis of rotation oriented vertically, and verticalaxis wind turbines (VAWTs) were also developed. Later-model windmills have their axis of
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rotation in the horizontal position, and the analogous horizontal-axis wind turbines (HAWTs) also evolved. Although the orientation of the rotational axis defines the two primary design categories of wind turbines, many variations exist within each category. Early sailing ships and the earliest windmills utilized the principle of “aerodynamic drag” to capture wind energy. Applying this principle involves installing an obstruction in the path of the wind. Depending on how this obstruction is oriented and what it is connected to, the force of the wind striking it can cause work to be performed (e.g., propelling a square-rigged sailing ship through the water). The common instrument for measuring wind speed, the cup anemometer, is an example of a present technology that still utilizes aerodynamic drag. Machines utilizing aerodynamic drag are easy to construct, and they make few design or operational demands. However, despite the relative simplicity of aerodynamic drag machines, their overall efficiency is generally low.
Figure 2. Great Plains Windmill (Source: EERE 2004a)
No modern wind turbine operates on the principle of aerodynamic drag; instead, “aerodynamic lift” is utilized. When this principle is employed, the wind turbine’s blades do not obstruct the wind; rather, they direct its flow. The cross-sectional shape of all modern wind turbine blades is that of an “airfoil.” These blades are similar in shape and purpose to an airplane wing. Wind flowing around an airfoil creates two different regions of pressure: a low-pressure region on the convex or “suction” side of the airfoil, and a higher-pressure region on its concave or “pressure” side. The atmosphere’s attempt to return to pressure equilibrium creates the phenomenon of aerodynamic lift. However, whereas an airplane’s
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airfoils are oriented in such a way that aerodynamic lift helps the plane defy the laws of gravity (i.e., air pressure is lower above the wing than below it, causing the wing to “lift”), the orientation of a wind turbine’s blades relative to incident wind converts aerodynamic lifting forces into the rotation of the blades around an axis parallel to the direction of the wind.[4] Wind turbines utilizing aerodynamic lift can have power efficiencies up to 50 times greater than the efficiencies of turbines operating on aerodynamic drag (Wilson 1994). As noted previously, wind turbines have been developed with their axis of rotation in both the vertical orientation and the horizontal orientation. The VAWT traces its ancestry farther back in time than does the HAWT, to as early as 200 B.C. (Sandia National Laboratories 2004b). Modern VAWTs are variations of a design first introduced by French scientist Georges Darrieus around 1920. Figure 3 shows examples of a commercial VAWT in California and an experimental VAWT currently operating at a DOE test facility in Texas. In theory, both VAWTs and HAWTs should be able to capture the wind’s energy by means of the principle of aerodynamic lift. However, VAWTs have a number of practical advantages. Because their blades are always perpendicular to the prevailing wind, they do not need to be reorientated when the wind direction changes in order to operate at their maximum efficiency. Thus, both their design and the complexity of their required operational controls are simplified. They are generally easier to erect than HAWTs and can have serviceable components located at or near ground level, thereby greatly simplifying their O&M. However, some of those same design characteristics contribute to the VAWT’s intrinsic limitations. Many VAWT designs are not “free-wheeling” and must use an external energy source to start their rotation. Many also have limited wind speed operating ranges. VAWTs also have certain design limitations with respect to their maximum practical height. Most important to their commercial application, however, is blade reliability and working life. VAWT blades must pass through the “wind shadow” or wake of their rotational axis, which also serves as the machine’s primary support. This region typically exhibits a good deal of turbulence, which not only reduces power capture efficiencies but also subjects the blades to forces that are different and opposite to those that they experience when they are upwind of the center support; thus, significant engineering issues, such as fatigue, are introduced. Considerable research continues even today on how to overcome the intrinsic shortcomings of VAWTs, and VAWTs are being used as test platforms to generally advance the understanding of wind turbine technology. DOE’s Sandia National Laboratories play a key role in this effort. However, only a few commercial wind farms that utilize VAWTs have ever been developed, and none are anticipated in the foreseeable future. Wind farms at Tehachapi Pass in California; Pincher Creek in Alberta, Canada; and Cap-Chat in Quebec, Canada, utilize or have utilized VAWTs. The leading manufacturer of commercial VAWTs, FloWind Corporation, is no longer in business. No VAWTs have ever gone into commercial service in Europe (Gipe 1995). Therefore, it is likely that HAWTs will continue to dominate the commercial market in the foreseeable future. Additional discussion of VAWT technology is therefore unnecessary for purposes of this PEIS.
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Figure 3. Examples of VAWTs (Left: FloWind Corporation VAWT at Tehachapi, California. Photo credit: R. Thresher. Source: Photo #04688, NREL 2004b. Right: Darrieus-design VAWT operated as a wind energy technology test bed by Sandia National Laboratories at the U.S. Department of Agriculture research station at Bushland, Texas; 138 ft (42 m) high, 112 ft (34 m) in diameter. Photo credit: Sandia National Laboratories. Source: Photo #01671, NREL 2004b.)
In recent years, HAWTs have become the predominant technology used in commercial wind farms; thus, they are the focus of discussion in this PEIS. Figure 4 shows an example of a typical front-facing HAWT. Within this category, Manwell et al. (2002) identified the following significant design variants: front-facing or rear-facing rotors and blades, rigid or teetering hubs, rotor rotation controlled by pitch or stall, number of blades (usually two or three), and free or controlled yaw motion. The majority of these design characteristics influence the overall performance of a turbine, but most have little or no influence on the environmental impacts of an operating turbine and thus are not discussed in further detail.
Figure 4. Typical Front-Facing or Upwind HAWT (GE’s 3.6-MW prototype wind turbine is an example of a front-facing HAWT. It is one of the largest HAWTs in existence, with a rotor diameter of 341 ft [104 m], giving a swept area of the blades of 91,432 ft2 [8,495 m2]. Rotor speed is variable between 8.5 and 15.3 rpm. The tower is constructed of concrete [lower portion] and tubular steel. Here, the turbine faces into the wind, which enters from the left.Sources: Photo adapted from EERE 2004c. Turbine specifications available from GE 2004.)
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5. IMPORTANT CONCEPTS OF MODERN HAWT OPERATION Figure 5 shows the major components of a HAWT. As noted previously, many factors influence the design and performance of modern wind turbines. This section focuses on the aspects of wind turbine design and operation that can have direct and/or cumulative environmental impacts. Also discussed here is the spatial arrangement of wind turbines on a wind farm, which can also result in environmental impacts.
5.1. Power Coefficients Intercepting the greatest practical cross-sectional area of wind creates the opportunity for capturing the greatest amount of energy; therefore, the primary design focus is on the rotor, which is the part of the turbine that actually extracts the wind’s energy. No mechanical device, including the wind turbine, is 100% efficient. The practical efficiency of a wind turbine is usually represented as its power coefficient, Cp , defined as that fraction of the wind power that may be captured by the turbine and converted to mechanical work (and, subsequently, electricity). The power coefficient of a wind turbine is almost entirely a function of the rotor’s efficiency.The power coefficient is represented by the following expression: P= ½ × Cp ×ρ × A × V 3,
(3)
where P = power output of the turbine, Cp = power coefficient of the rotor,
Figure 5. Major Components of a Modern HAWT (Source: EERE 2004c)
Anemometer: Measures the wind speed and transmits wind speed data to the controller. Blades: Most turbines have either two or three blades. Wind blowing over the blades causes the blades to “lift” and rotate. Front-facing turbines normally have three blades. Brake: A disc brake, which can be applied mechanically, electrically, or hydraulically to stop the rotor in emergencies.
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Controller: The controller starts the machine at wind speeds of about 8 to 16 mph (13 to 26 km/h) and shuts off the machine at about 65 mph (105 km/h). Turbines cannot operate at wind speeds above about 65 mph (105 km/h) because their generators could overheat. Gear box: Gears connect the low-speed shaft to the high-speed shaft and increase the rotational speeds from about 30 to 60 rotations per minute (rpm) to about 1,200 to 1,500 rpm, the rotational speed required by most generators to produce electricity. The gear box is a costly (and heavy) part of the wind turbine, so engineers are exploring “direct-drive” generators that operate at lower rotational speeds and do not need gear boxes. Generator: Usually an off-the-shelf induction generator that produces 60-cycle alternating current (ac) electricity. High-speed shaft: Drives the generator. Low-speed shaft: The rotor turns the low-speed shaft at about 30 to 60 rpm. Nacelle: The rotor attaches to the nacelle, which sits atop the tower and includes the gear box, low-speed and high-speed shafts, generator, controller, and brake. A cover protects the components inside the nacelle. Some nacelles are large enough for a technician to stand inside while working. Pitch: Blades are turned, or pitched, out of the wind to keep the rotor from turning in winds that are too high or too low to produce electricity. Rotor: The blades and the hub together are called the rotor. Tower: Towers are made from tubular steel (shown here) or steel lattice. Some taller towers may incorporate concrete over the lower portions of their height. Because wind speed increases with height, taller towers enable turbines to capture more energy and generate more electricity. Wind direction: This is an “upwind” turbine, so-called because it operates facing into the wind. Other turbines are designed to run “downwind,” facing away from the wind. Wind vane: Measures wind direction and communicates with the yaw drive to orient the turbine properly with respect to the wind. Yaw drive: Upwind turbines face into the wind; the yaw drive is used to keep the rotor facing into the wind as the wind direction changes. Downwind turbines do not require a yaw drive, since the wind blows the rotor downwind. Yaw motor: Powers the yaw drive.
ρ = air density (typically 2.70 lb/m3 [1.225 kg/m3] at sea level and 59 F [15 C]), A = rotor-swept area, and V3 = cube of the incident wind speed. The power coefficient of the rotor has a theoretical maximum value of 0.593, called the Betz limit or Lancaster-Betz limit. This value is based upon the physical reality that even the most aerodynamically efficient turbine blade disrupts the airflow of incident wind, even before the wind front reaches the rotating blade. In actuality, the air molecules within the cross-sectional area swept by the rotor slow down as they approach rotating turbine blades and thus lose kinetic energy proportional to the cube of that velocity loss.[5] The power coefficient of the rotor can be thought of as a correction factor, introduced into the above power equation to reflect the reality that the rotor’s power-capturing efficiency is less than perfect. To calculate the power coefficient of the entire wind turbine, one simply
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has to introduce additional correction factors to represent the mechanical inefficiencies of the entire turbine drivetrain. However, for the purpose of this discussion, the power coefficient of the rotor is the source of greatest turbine inefficiency to the extent that drivetrain inefficiencies need not be discussed in detail. A comparison of the turbine efficiency equation above with the equation presented in Section 3, which represents the power inherent in the wind, leads one to fully appreciate how energy is produced by wind turbines. The Betz limit actually reflects the impossibility of extracting all the energy from the wind. Because the theoretical limit of rotor efficiency is always considerably less than 100%, the power produced by a wind turbine is always less than the power contained in the wind cross section that the turbine is intercepting. And because the rotor’s efficiency is the major contributor to the overall turbine efficiency, rotor design considerations are of paramount importance.
5.2. Turbine Power Curves The graphical representation of a turbine’s electric power output as a function of incident wind speed is known as the turbine’s power curve. At a fixed rotor speed, the power production of a wind turbine is defined by the following equation: Pel
= cp × ρ /2 × (vw)3 × A ,
(4)
where Pel = electric power (expressed in W, kW, or MW), cp = power coefficient of the turbine, ρ = air density (kg/m3), vw = wind speed (m/s), and A = swept area of the rotor (m2). Turbine manufacturers routinely use the power curve as a representation of their wind turbine’s official certificate of performance. Certain design features can have minor influences on the exact shape of the power curve; however, these influences notwithstanding, the power curves of virtually all commercial wind turbines are strikingly similar. As incident wind speed increases from zero to the “cut-in velocity,” the net power extracted from the wind becomes greater than that which is necessary to overcome the mechanical drag of the turbine’s drivetrain, and the excess power is used to begin producing usable electric power. With increasing wind speed, power production increases rapidly until the “rated velocity” is reached. At this wind speed, the turbine has reached its maximum electric power production capability. Power production continues at this maximum level with further increases in wind speed until the “cut-out velocity” is reached. At the cut-out velocity, the wind’s energy is so great that it can cause mechanical damage to major turbine components. To prevent such damage, designers introduce various controls (such as pitch and stall control on the rotor, mechanical braking of the rotor shaft, and clutching mechanisms on the rotor shaft) that can decouple the rotor from the remainder of the turbine drivetrain.[6] With the application of such controls, the electric power production drops precipitously to zero, and the turbine effectively becomes nonfunctional as a power
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source. The range of wind velocities over which the turbine can produce electricity is referred to as its operating range; however, the maximum electric power production (i.e., the turbine’s nameplate rating) is achieved only at the upper end of the operating range. At incident wind speeds between the cut-in velocity and the rated velocity, power production is well below the nameplate rating. In general, commercial wind turbines have operating ranges between 2.5 and 25 m/s. (Table 2 in Section 6, which provides commercial wind industry profiles, has examples of operating ranges.) A turbine’s power output can be derived solely from engineering calculations. However, because the power curve represents the manufacturer’s guarantee of a turbine’s performance, theoretical calculations are also carefully validated with real-world measurements. To overcome myriad real-world variables that can affect power production, such empirical verifications of power output are based on the statistical evaluation of a large number of measurements. Hau indicates that measurements averaged over a minimum of 10 minutes are usually sufficient to account for the time variability of operating conditions (Hau 2000).
5.3. Capacity Factors Although the power curve is an accurate measure of the turbine’s ability to generate electricity from incident wind, it does not adequately describe expectations of real-world power production. Overlaying the relevant characteristics of a given wind regime (most importantly, the percentage of time the incident wind is at the uppermost portion of the operating range) and introducing additional correction factors that reflect the turbine’s technical availability (i.e., periods when the turbine is fully functional and not down for maintenance or repairs)[7] yield the capacity factor, the most realistic and reliable prediction of the energy yield for a given candidate site. Capacity factors are dimensionless, expressed as a ratio in which the turbine’s annual predicted energy production is divided by the energy it would produce if it operated at its nameplate rating continuously. Capacity factors are normally represented as annualized values to account for seasonal variations in wind regimes. In practice, the most efficient wind farms exhibit individual turbine capacity factors of 30 to 35% (EPRI 2001; DOE/TVA/EPRI 2003; Robichaud 2004). However, capacity factors as high as 45% have been observed (Manwell et al. 2002; EPRI 2001; McGowan and Conners 2000). Capacity factors of at least 25% are considered minimally necessary for a site to be considered economically viable (McGowan and Conners 2000). Because it is rooted in the real world, the capacity factor becomes a much more valuable tool for supporting decisions about wind farm development than the turbine’s power curve alone. The ideal site from a power production perspective is one that yields the highest capacity factor for each of the turbines. That being said, however, it is important to also recognize that power-producing potential, although important, is not the exclusive basis for site development decisions. Many other factors, including ease of site access, access to transmission lines, site development costs, the absence of sensitive ecosystems, and market price for energy, are always also considered in site selection decisions. Thus, it is often the case that the sites with the ideal wind regimes yielding the highest predicted capacity factors are not necessarily assigned the highest priority for development.
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5.4. Rotor Tip Speed and Tip Speed Ratio The rotor tip speed is the tangential velocity of the very end of the blade of a rotating rotor (i.e., the speed at which the tip of the blade moves around the circumference of the swept area of the rotor). Early wind turbine designs sought to match the rotor speed with the rotational speed requirements of the electric generator’s rotor.[8] However, modern designs utilizing more sophisticated and more reliable transmissions (Figure D-5) can adequately maintain the rotational speed of the electric generator’s central shaft at much lower rates of rotor rotation. This results in substantial additional benefits, including reductions in the bending moments on the blades and reductions in the forces on the turbine drivetrain, by minimizing the effective weight of the rotor. Wind turbine designers concern themselves not with the blade’s tip speed but rather with the tip speed ratio, which is defined as the ratio of the angular velocity of the blade tip to the mean velocity of the wind entering the rotor. For a given mean wind velocity and a rotor with a given number of blades, the design objective is to select a tip speed ratio that maximizes the opportunity for the incident wind to interact with the turbine blades and impart aerodynamic lift while simultaneously minimizing the disruptions of airflow ahead of the rotor blades. A rotor spinning too fast will present a greater obstruction to incident wind. Conversely, a rotor revolution that is too slow will allow large amounts of air to pass through the rotor’s plane without ever interacting with a turbine blade and imparting aerodynamic lift. At a given mean wind speed, the power coefficient of a turbine initially increases with an increasing tip speed ratio until a maximum is reached; beyond this point, performance actually decreases with further increases in the tip speed ratio. A more detailed discussion of this relationship and the influence of the Betz limit on turbine performance is provided by Burton et al. (2001). The ideal tip speed ratio is empirically derived and is inversely related to the number of blades. Because the rotor’s (and the turbine’s) power coefficient is directly related to the tip speed, controlling that ratio is a desirable objective. For a specific rotor operating in a given wind regime, the tip speed ratio at which maximum performance is achieved becomes the controlling design basis value. In addition to the basic performance relationship between the blade’s tip speed and the turbine’s power coefficient, two impacting factors are directly related to rotor rotation and tip speed: aerodynamic noise and shadow flicker. Both can influence turbine design decisions. The aerodynamic noise generated by a wind turbine is proportional to the fifth power of the tip speed.[9] Thus, small variations in tip speed can dramatically affect the noise profile of a wind turbine. Empirical data have led turbine designers to limit the tip speed to no more than 213 ft/s (65 m/s). Limiting the tip speed (which is proportional to the rotor’s rate of rotation and based on the swept area of the rotor) and limiting the distance to the nearest habitation to at least 1,312 ft (400 m) are expected to result in a turbine noise level at or near ambient levels (Burton et al. 2001). However, other factors, such as the height of the rotor and the topography of the site, can significantly influence the propagation of sound energy. In addition to the mathematical and geometric relationships between the rotor’s rate of revolution and the tip speed and the relationships between the tip speed ratio and the power coefficients, rotor revolution can also cause a visual phenomenon unique to wind turbines known as shadow flicker. Shadow flicker refers to the shadows that a wind turbine casts over structures and observers at times of the day when the sun is directly behind the turbine rotor from an observer’s position. Shadow flicker is most pronounced in northern latitudes during
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winter months because of the lower angle of the sun in the winter sky. However, it is possible to encounter shadow flicker anywhere for brief periods after sunset and before sunrise. Empirical data suggest that shadow flicker can have a disorienting effect on a small segment of the general population. Empirical data also suggest that limiting the frequency of rotor rotation to below 2.5 Hz can mitigate the deleterious effects of shadow flicker.[10] Burton et al. (2001) indicates that limiting a (three-bladed) rotor revolution to 35 rpm will result in a blade passing frequency of 1.75 Hz (i.e., where the passing is between the sun and the observer). Increasing the spacing between a turbine rotor and the nearest observer to at least 10 rotor diameters also dramatically mitigates shadow flicker effects. Finally, another closely related phenomenon is “blade glint,” which is the reflection of sunlight off the surfaces of rotating blades. Such glint can also have a disruptive effect on some observers. However, as discussed elsewhere, the trend in the industry is toward longer blades. To control the resulting weight (and provide better aerodynamic properties), modern blades are now constructed almost exclusively of carbon composites or plastics, the natural surfaces of which are quite dull, especially relative to the steel and aluminum blades of the past. In the majority of cases, this technological development has made blade glint a relatively moot point with regard to modern turbines.
5.5. Blade Length and Tower Height Because the speed of the incoming wind cannot be controlled, attaining and maintaining the ideal tip speed ratio involves controlling the tip speed. There are two paths to this objective: changing the rate of rotor rotation or increasing the blade length. Increasing the blade length is often the preferred option for a number of engineering reasons. However, the law of diminishing returns is also at play here. Larger rotor diameters result in additional bending moments on the blades that must be accounted for. Longer blades mean additional rotor weight and increased strain on the mechanical drivetrain components. Research on alternative materials and fabrication procedures is being conducted by turbine manufacturers and under government sponsorship. (See Section 7 for more details on blade research.) Preliminary DOE-sponsored research on the technological impediments to scaling up current blade designs has identified the need to modify construction materials and processes (Griffin 2002) and the need to take a fundamentally different approach to airfoil design for extremely long blades (TPI Composites, Inc. 2002). To accommodate longer blade lengths, the turbine support towers have to be taller and more substantial. Irrespective of blade length, taller towers allow the rotor to operate in geostrophic wind regimes above the interferences introduced by surface topography. Principal performance factors affecting tower height selection include the wind profiles of the candidate site and the blade length of the turbine model selected. Costs of fabrication and erection are balanced against the performance advantages. Other factors related to site conditions can also influence tower height selection. These include access to the site by the larger equipment needed to transport towers (or tower segments), longer blades, and lifting/erection equipment; temporary amendment of site surface conditions to accommodate erection activities; and subsurface conditions that could affect the difficulty and the cost of constructing sufficient foundations for larger towers.[11] Installation costs, site access, and transportation logistics are important limiting factors with regard to tower height, and all
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factors must be considered in calculating improved performance with height. Developers are not likely to erect towers any taller than necessary to achieve economic power production (Steinhower 2004). The principal impacting factors that directly relate to a rotor’s geometry and the elevation at which it operates are listed below: • • •
• •
Larger rotors require higher, more formidable towers that are more expensive to fabricate and erect. Higher towers, in turn, are visible from greater distances, increasing the size of the impacted viewshed. Larger rotors allow for the economical capture of wind energy at slower rotor revolutions, which could lessen or completely eliminate the adverse viewshed impacts and bird-strike hazards. Larger rotors can rotate at frequencies less than the frequencies that induce shadow flicker. Larger rotors operating at fewer rotations per minute produce less aerodynamic noise than their smaller counterparts, which must rotate faster to capture the same amount of wind energy.
5.6. Grid Interconnection Issues The distance to an existing transmission line of suitable voltage and with reserve powercarrying capacity is a critical factor to consider with regard to future wind energy development projects, because the wind farm developer is expected to absorb the cost of establishing the physical link from the wind farm to the nearest existing transmission grid.[12] However, connecting to the grid is not necessarily a straightforward process. In reality, many factors related to grid interconnectivity can influence site development costs, design selection, initial installation and subsequent operating costs, and ROI schedules. To prevent disrupting the grid, the electric power generated at the wind farm must first be conditioned. This requires installing various power management and conditioning devices. Other devices are required to automatically isolate a wind farm from the grid during certain disruptive events. Sophisticated supervisory control and data acquisition (SCADA) systems are also required to ensure that the operating conditions of both the individual turbines and the overall wind farm and any rapid changes to grid interconnections are adequately controlled, in order to prevent the effects of potentially damaging disruptive events at the wind farm from cascading onto the grid. Although power management and control devices and SCADA systems certainly affect site development costs and the ability of the wind farm to interconnect to the grid, they represent only an incremental change to the footprint of the wind farm, and most have little or no direct or cumulative environmental impacts.[13] There are two notable exceptions, however: “voltage flicker” and lightning protection. If not adequately conditioned and controlled, wind farm power introduced onto the grid can result in voltage flicker. Voltage flicker occurs when changes to the network voltage occur faster than steady-state voltage changes that exist within the transmission system. Voltage flicker can cause perceptible changes to the brightness of incandescent lights that
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draw power from the grid. Such changes, in turn, can have a disorienting effect on certain individuals. Transmission grid operators can be expected to require wind farm operators to establish power management systems capable of eliminating conditions leading to voltage flicker. Lightning protection is also required for wind farm components to prevent catastrophic impacts to the grid. Each individual turbine tower on the wind farm, as well as the electrical substation, must be protected, and control systems must be capable of isolating the wind farm from the grid during upset conditions caused by lightning. Although lightning protection technologies are available, their application in some wind farm settings may appreciably increase site development costs. Conventional lightning control involves providing a lowimpedance path for the lightning’s electrical energy to pass to the ground.[14] To establish adequate lightning protection for wind farms developed on rocky ground where there is no soil mantle, it may be necessary to drill one or more wells into which a current-conducting metal rod is inserted to extend the grounding path to the nearest aquifer. Moreover, the aquifer must be continuous over a large area rather than perched to provide reliable protection. In some western states within the study area, the nearest appropriate aquifer may be thousands of feet below a candidate wind site. Installation of such grounding wells will increase costs ↓ not only costs directly related to well installation, but also costs to support the hydrogeologic studies that may be required to identify appropriate aquifers.[15]
5.7. Variable versus Fixed Rotor Rotation Wind turbines can be designed to operate at both fixed and variable rotor rotation speeds. Of the two systems, variable-speed systems are preferred for a number of reasons related to overall wind turbine performance. However, while variable-speed machines can take fuller advantage of variations in the incident wind speed, the alternating current (ac) electricity they produce has a variable frequency that cannot be safely delivered to existing power transmission grids without conditioning. Variable-speed wind turbines are routinely connected “indirectly” to the grid to allow this power conditioning to occur at the wind farm. The majority of modern turbines include transmissions, clutches, and rotor shaft braking systems or aerodynamic stall features that act on the rotor blades to maintain the variations in a rotor shaft’s rotation within prescribed design limits. Such turbines are also equipped with SCADA systems that can adjust operating conditions (e.g., aerodynamic stall and blade pitch) to changing wind conditions. Variable-speed capability allows the turbine to operate at ideal tip speed ratios over a larger range of wind speeds. The most dramatic increase in performance is realized at lower wind speeds. Wind turbines with either a fixed or variable rotor rotation speed can be outfitted with either synchronous or asynchronous electric power generators.[16] In general, initial installation costs for asynchronous generators are lower, and the generators are generally very reliable. More important, asynchronous generators have mechanical properties that make them very suitable for wind turbine applications, including good overload capabilities and a relatively small generator slip.[17] Asynchronous generators can easily accommodate changes in the torque applied by the wind turbine’s rotor shaft (through the transmission), thus reducing overall mechanical wear and tear over the generator’s operating life. Because of the relatively constant operating conditions of asynchronous generators, turbines equipped
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with such generators are normally directly connected to the grid with little additional conditioning. The use of synchronous electric generators rather than induction generators improves the wind turbine’s overall power-generating performance and reduces the likelihood that the turbine will be a source of harmonic electric currents that can be disruptive to the power grid. However, initial installation costs are higher, and the power produced by synchronous generators must first be conditioned before delivery to the grid, further increasing installation and operational costs. As rotor diameters increase, the turbine’s rated power increases proportionally to the square of the rotor diameter. The amount of torque produced by the rotor shaft also increases markedly, placing significant operating demands on transmissions and generators. Industry and government researchers are now exploring the use of multiple generators or the use of multipole generators as a way of distributing torque and reducing its damaging effects on mechanical systems (Cotrell 2002). The use of multiple generators operating at different shaft speeds is also being investigated as a means of producing optimal levels of power at more widely varying rotor rotational speeds. Regardless of turbine and generator design choices, the attendant power-conditioning prerequisites do not themselves have additional environmental impacts of any significance. Operation at variable rotor speeds increases the complexity of the initial turbine design as well as the SCADA system required. However, it also promises to increase the overall longevity of major system components and to reduce O&M costs. Thus, turbines with variable-speed rotors can be expected to have less of an environmental impact over their operating lives than would their fixed-speed counterparts. Wind farms could consist of a mixture of fixed-speed and variable-speed turbines. Although the development costs of such a wind farm would be incremental, the increased sophistication of power management systems and SCADA systems and the expected greater O&M costs of such a configuration make such a wind farm unlikely. Wind farms consisting of identical turbines operating at different rotor elevations in order to take the fullest advantage of existing wind profiles are still a conceivable option, however. The following impacting factors relate to rotor operation at a variable rotation speed: •
•
•
Reducing the dynamic forces on the turbine drivetrain, extending the operating lives of major components, extending the maintenance intervals, and reducing the incidence of breakdowns, all of which would result in a smaller environmental impact over the life of the wind farm; Allowing the turbine to be “elastic” with respect to its interaction with the grid, thereby reducing the generation of power harmonics that can be disruptive to the grid; and Allowing the turbine to efficiently generate power at lower wind speeds, thus reducing the aerodynamic noise signal of the blades.
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5.8. Micrositing and Site Development Once a candidate site has been selected and more detailed meteorological data have been gathered for a minimum of 1 year, site developers have the data necessary to make micrositing decisions (i.e., determine the precise location on the site at which the wind turbines will be located). The natural turbulence at the site due to the surface topography and obstructions and the induced turbulence of each wind turbine tower are the primary factors that govern turbine micrositing. Empirically derived nomographs[18] exist that indicate the necessary minimum distances for turbine placement from natural obstructions; however, they are often imprecise. Improving the methods for characterizing site-specific turbulence and understanding the influence of turbulence on site development make up a major ongoing R&D initiative (Section 7). It is possible that site developers may find it appropriate to remove some natural obstructions (e.g., trees) to mitigate turbulence caused by natural obstructions.[19] It is also reasonable to conclude, however, that the extent to which natural features of the site will be altered to improve the wind regime will be limited by site development costs. Thus, while tree removal is a feasible step associated with site development, major alterations of the existing grade over a large scale are not. It is also reasonable to expect that a site developer will seek to take advantage of economies of scale and develop a candidate site to its fullest potential. Thus, multiple turbines will likely be erected, and turbulence considerations will again be the primary factor governing their number and interspatial relationships.[20] Empirical nomographs that describe the induced turbulence of a wind turbine and its tower and that indicate the minimum distance of separation needed to avoid such interferences will likely be used to support micrositing decisions. (Research is ongoing to develop more precise modeling tools for characterizing the wind regimes on a site; see Section 7.) Avoiding the wind shadow of turbines will probably be a first priority in siting multiple turbines, and access to the indicated micrositing location will be of secondary importance. Pursuing economies of scale in site development will amortize site characterization and site development costs. However, the extent to which a site will be developed can have additive effects on many of its impacting factors. Primary impacting factors related to site development and micrositing include the following: •
• • • • •
Potential for ancillary activities, such as tree and vegetation removal, that will result in surface scarring and additional impacts to the viewshed beyond the impact of turbine visibility itself; Increased potential for fugitive dust, proportional to the area of disturbed ground surface; Potential for invasive species being established in disturbed areas before indigenous vegetation can be reestablished; Potential for bird strikes, generally proportional to the number of turbines installed; Increased time required for construction, with proportional increases in both the magnitude and duration of impacts related to construction; Potentially additive impacts from individual turbines, including noise and viewshed impacts; and
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Proportional increases in O&M costs, including costs to deal with wastes associated with system maintenance and repair.
6. COMMERCIAL WIND ENERGY INDUSTRY PROFILES This section provides an overview of the existing commercial wind energy industry within the study area. The AWEA compiles and maintains data on commercial wind farms.[21] The review and analysis of these data provide a reasonable basis from which to anticipate the characteristics of future wind farms. Industrywide reviews of the commercial utility-scale wind energy industry have identified the following important trends, each of which will greatly influence future wind farms. •
•
•
• • •
•
In general, average individual wind turbine power-generating capacities have steadily increased in North America, from 500− 750 kW in the late 1990s to megawattcapacity turbine installations beginning in 1999, resulting in typical wind farm generating capacities of 50 MW or larger (Kaygusuz 2004). The (worldwide) average growth rate of the cumulative installed wind energy powergenerating capacity over the period 1998 to 2004 has been about 30% per year (Kaygusuz 2004). As the understanding of aerodynamics has been increasing and as designs have been defined, wind turbine efficiencies have been increasing, especially for turbines with larger rotor-swept areas. Average annual yields per unit of rotor-swept area (RSA) have increased by more than 50% as rotor diameters have increased from 66 to 262 ft (20 to 80 m) (Milborrow 2002). Wind turbines now have power-generating capacities of as much as 600 W/m2 of RSA. Three-bladed, upwind turbines dominate the commercial utility-scale market (Milborrow 2002). The majority of wind turbines run at fixed rotor speeds and utilize induction generators. However, newer models equipped with sophisticated electric power conditioning controls have rotors that run at a variable rotational speed (Milborrow 2002). Newer-model turbines tend to run at slower rotor rotational speeds but have relatively high energy capture/conversion efficiencies (Milborrow 2002). About the AWEA
The American Wind Energy Association (AWEA) is a national trade association that represents wind power plant developers, wind turbine manufacturers, utilities, consultants, insurers, financiers, researchers, and others involved or interested in the wind energy industry. The AWEA provides up-to-date information on wind energy projects operating worldwide and projects under development, and it conducts technology and policy development activities related to wind energy.
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United States Department of the Interior, Bureau of Land Management The AWEA compiles and regularly updates relevant domestic and worldwide statistics on the wind energy industry and makes them available to industry participants, the interested general public, and the news media. These data are available at the association’s Web site at http://www.awea.org. Also available on the AWEA Web site is access to various wind-energy-related information resources, including wind energy fact sheets and a catalogue of related publications. The AWEA also publishes a weekly newsletter devoted to wind energy news and hosts an annual national conference, WINDPOWER. Detailed information on AWEA activities and services can be obtained by visiting the Web site. Information developed by the AWEA has been incorporated into this PEIS without independent verification. The BLM does not endorse the AWEA and does not make any warranty regarding the accuracy or completeness of the data it provides.
Although the commercial wind energy market in the United States has existed for some time, it has only recently (since 1999) begun to experience substantial growth, with calendar years 2001 and 2003 witnessing the two largest single-year’s growth. Figure 6 graphically depicts the rise in wind energy capacity (nameplate ratings in megawatts of electricity; the bars in the foreground represent capacities added annually; the bars in the background represent cumulative power capacity) over the period from 1981 through 2003. Data published by the AWEA indicate that the total installed capacity for all domestic commercial wind energy as of December 2003 was 6,374 MW, with 1,687 MW coming on line in 2003, which was a 36% increase from the capacity at the previous year’s end (AWEA 2004d). Calendar year 2003 compared favorably with the previous year, showing a worldwide increase in capacity of 6,868 MW to reach a total of 31,128 MW and a U.S. increase of 410 MW to reach a year-end total of 4,685 MW, which represents 15% of the world’s market (AWEA 2003a). Of the current total domestic capacity of 6,374 MW, 2,999.7 MW (or 47%) is being produced in the 11-state study area of this PEIS. The increase in overall generating capacity has been accompanied by a steady increase in individual turbine proportions and capacities. In the late 1980s, average turbine power outputs averaged 450 kW. Outputs increased to an average of 600 to 750 kW by the late 1990s. Now, individual turbines with ratings greater than 2 MW (2,000 kW) are commonplace (McGowan and Connors 2000). Figure 7 shows the distribution of wind energy power-generating capacity across the United States. The numbers represent power capacities of utility-scale wind farms only, all of which deliver power directly to the electric power transmission grid. Additional power capacities from distributed energy systems are not included. The power capacities represent nameplate ratings and are rarely realized in practice. (See the discussion on typical capacity factors in Section 5.2.) Within the 11-state study area for the PEIS, the total installed wind energy capacity is 2,999.7 MW.
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Figure 6. U.S. Installed Capacity (MW) for 1981 through 2003 (Source: AWEA 2004d. Reprinted with permission. Courtesy of the AWEA.)
Figure 7. Wind Energy Projects in the United States (Source: Adapted from AWEA 2004a. Reproduced with permission. Courtesy of the AWEA.)
Table 1 lists the commercial wind energy projects completed in 2003. Projects completed within the 11-state study area are in bold type. The projects listed in the table represent new wind farms and phased expansions, or “repowering” of existing wind farms (i.e., replacing existing turbines with ones of newer design). Facility expansions and repowering activities are not expected to have the same array and magnitude of impacting factors as would a completely new facility. By definition, such site modifications are outside the scope of this PEIS. In general, the number of manufacturers of wind turbines has greatly decreased from earlier years. In fact, a number of manufacturers have gone out of business. However, also represented in this decline are a number of mergers among manufacturers.
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United States Department of the Interior, Bureau of Land Management Table 1. Wind Energy Projects Installed in 2003a
State Alaska Arkansas California California California California
Project Name Selawik Wind Project Bitworks High Winds Mountain View III
Illinois
CalWind II CECrepower Whitewater expansion Karen Avenue II Colorado Green Lewandoski wind farm Mendota Hills
Iowa Iowa
Flying Cloud Henry Hills
Iowa Iowa Iowa
Lenox Wall Lake Sibley Hills
Minnesota Minnesota
Chanarambie Moraine Wind Power Project Farmers’ cooperative corporations McNeilus
California California Colorado Idaho
Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota
McNeilus Viking McNeilus Fairmont Missouri River Energy Systems Shaokatan Power Partners McNeilus Don Sieve Wind Farm
Minnesota Pipestone School District New Mexico New Mexico Wind Energy Center New Mexico Llano Estacado Wind Ranch at Texico North Dakota North Dakota Ohio Oklahoma Blue Canyon Wind Power
Location Selawik Prairie Grove Industrial Park, Washington County Solano San Gorgonio Sacramento Tehachapi
Combine Hills
Turbine Manufacturer AOC
No. of Wind Turbines 4
NEG Micon
1
Vestas Vestas Vestas Vestas
90 34 15 13
4.5
FPL Energy `PPM Energy SMUD CalWind Resources, Inc. Cannon Power Corp.
GE Wind
3
San Gorgonio Near Lamar
4.5 162 0.216
San Gorgonio Farms GE Wind Bob Lewandoski
GE Wind GE Wind
3 108 2
Lee County, near Mendota Near Spirit Lake Osceola County, near Sibley Lenox Wall Lake Near Sibley
50.4
Navitas Energy
Gamesa Eolica
63
43.5 3.6
GE Wind Gamesa Eolica
29 2
NEG Micon Vestas Vestas
1 1 1
85.5 51
PPM Energy Northern Alternative Energy Lenox Municipal Wall Lake Municipal Northern Alternative Energy enXco PPM Energy
GE Wind GE Wind
57 34
22.8
DanMar & Associates
Suzlon Energy
24
22.8
Garwin McNeilus
NEG Micon
24
16.5 12 6 1.9 1.9
NEG Micon NEG Micon NEG Micon NEG Micon
11 8 4 2 2
Gamesa Eolica
2
NEG Micon NEG Micon
1 1
NEG Micon
1
NEG Micon
1
204
Garwin McNeilus Project Resources Garwin McNeilus SMMPA Missouri River Energy Systems Northern Alternative Energy Garwin McNeilus Diversified Energy Solutions Diversified Energy Solutions Pipestone School District FPL Energy
1.32
Cielo Wind Power
Vestas
2
40.5
FPL Energy
GE Wind
27
21
FPL Energy
GE Wind
14
Bowling Green Zilkha Renewable Energy & Kirmart Corp. FPL Energy FPL Energy Eurus
Vestas NEG Micon
2 45
GE Wind GE Wind Mitsubishi
34 34 41
Murray County Pipestone & Murray Counties
Near Minn. Highway 56 Murray County Fairmont Worthington Lincoln County, near Hendricks
162 22.44 9.9 8.58
0.75 0.66 0.66
1.6
Lincoln Co.
1.65 0.95
Lincoln Co.
0.9
Minnesota
Oklahoma Oklahoma Oregon
Capacity Developer (MW) 0.2 Kotzebue Electric Association 0.1 Bitworks, Inc
0.75 Quay, DeBaca Counties
Near Edgeley Near Kulm Bowling Green North of Lawton
3.6 74.25
Near Woodland Near Woodland
51 51 41
GE Wind
136
Wind Energy Technology Overview State
Project Name
Pennsylvania Waymart Pennsylvania South Dakota South Dakota Texas Texas Texas Texas Washington Wyoming a
Meyersdale Highmore
Location Clinton & Canaan Township Somerset Near Highmore
Capacity Developer (MW) 64.5 FPL Energy
351 Turbine Manufacturer GE Wind
No. of Wind Turbines 43
30 40.5
FPL Energy FPL Energy
NEG Micon GE Wind
20 27
Rosebud Sioux
0.75
DisGen
NEG Micon
1
Brazos Wind Ranch 90 miles south of Lubbock Sweetwater Sweetwater Hansford County, Texas Indian Mesa Nine Canyon, Phase Benton County II Evanston Evanston
160 37.5 3
Cielo Wind Mitsubishi Power/Orion Energy DKR/Babcock-Brown GE Wind FPL Energy Vestas
3 15.6
Energy Northwest
Vestas Bonus
1 12
144
FPL Energy
Vestas
80
160 25 1
Bold type indicates projects within the 11-state study area. Source: Adapted from AWEA (2003b). Reprinted by permission. Courtesy of the AWEA.
Table 1 lists the manufacturers of commercial wind turbines whose products were installed in U.S. wind farm projects in 2003. Although there are many other manufacturers, those listed in Table 1 nevertheless represent a cross section of vendors. One should therefore take a more careful look at the turbine models offered by these vendors. Table 2 lists the ranges of values for critical parameters of wind turbines installed in 2003. Although it is assumed that installations in 2003 constitute a reasonable representation of the most current facility installations and expansions, there is still a possibility that future wind farms will utilize turbines from other manufacturers. Nevertheless, it is reasonable to assume that the turbines installed in 2003 met the technical requirements of the sites at which they were installed. It is therefore also reasonable to assume that future developments at sites with similar wind regimes may also utilize turbines with these approximate specifications. It is not the BLM’s intention to endorse any specific equipment manufacturer.[22] Consequently, rather than present the specifications of individual turbines, the table displays a range of values for each parameter that is addressed. Only design specifications that were readily available from manufacturers’ Web sites are included in the range calculations. Not always accurately reflected in the range value displayed, but nevertheless important for anticipating future wind farm characteristics, is the fact that many manufacturers offer modules rather than complete turbines, providing a number of options for each major component. Thus, the developer can custom build a turbine that is precisely suited to a particular site’s wind conditions and to the stipulations of a particular interconnection agreement with the transmission line operator. For the reader’s convenience, the Web sites for the manufacturers whose turbines are represented in the range of values displayed are provided as footnotes to Table 2. The data displayed in Table 1 appear to support the following conclusions about the characteristics of future wind farms. Notwithstanding the fact that calendar year 2003 was an exceptional year for industry growth, a reasonable assumption is that the projects that went on line in 2003 reflect the state of the technology with respect to commercially available wind turbines. Another reasonable assumption is that the wind turbine models installed in 2003 offered operating parameters that matched well with the specific conditions at the sites at which they were installed. A further assumption is that future sites with wind characteristics
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similar to those at sites developed in 2003 will utilize turbines with operating parameters similar to those displayed in Table 2. Table 2. Specifications for Wind Turbines Installed in 2003a Parameterb Power (nameplate rating)d Turbine type Cut-in speed (m/s) Nominal wind speed (m/s) Cut-out speed (m/s) Rotor diameter (m) Rotor-swept area (m2) Rotor speed (rpm) Rotor hub height (m)e Tower construction material
a
Tower weight (kg)f Nacelle weight (excluding rotor) (kg)e,f Rotor weight (kg)g Total weight (kg)h
pH 9)
Water binding powders, textiles, absorber
Heat denaturation and drying Cross-linking to enhance cohesion and reduce water sensitivity Chemical modification by acylation and crosslinking of the acyl-modified protein with dialdehyde (*)
Binding of nonpolar liquid contaminations Adhesive, coatings
Thickener, stabilizer (dispersed systems), regulation of flow behavior of coatings or building materials
Industrial absorbents, waste water reclamation, heavy metal sequestration
Biobased Polymers by Chemical Valorization of Biomass Components
469
The edible protein concentrate from alfalfa prepared by ultrafiltration and spray-drying at 85°C showed excellent functional properties (Knuckles and Kohler, 1982). Emulsions containing 2 wt% alfalfa protein and oil were stable and their consistency was similar to mayonnaise. Firm gels were obtained by heating solutions of 3 wt% alfalfa protein to 72°C and cooling. Foam volume and stability were similar to those of egg white. Since the 1980’s much research has focused on the purification and technological evaluation of Rubisco, the main soluble protein of leaves. Due to the excellent functional and nutritional properties of this tasteless and odorless white powder, purified Rubisco is regarded as having great potential as an ingredient in animal and/or human foods. The reviews of Barbeau and Kinsella (1988) and Douillard and de Mathan (1994) demonstrated that Rubisco was able to form stable foams and emulsions at low temperature, to produce firm gels when heated and to give high fat-binding capacity when the protein has not been modified by heat treatment.
4.1.6. Effects of Enzymatic and Chemical Modification of Leaf Proteins The modification of proteins via enzymatic, chemical or physical procedures is a common way to tailor the functionality. It is generally accepted that limited hydrolysis enhances the surface properties, whereas extensive hydrolysis has a detrimental effect on the stabilization properties. It was shown that the initial enzymatic degradation of native crystalline tobacco fraction-1 protein led to the removal of oligopeptides from the large subunits without a loss of small subunits and destruction of the quaternary structure (Sheen and Sheen, 1987). Insoluble alfalfa protein concentrate was solubilized by the proteolytic enzyme Delvolase and a peptide isolate suitable as a protein supplement in human diets was obtained by coupling the process with ultrafiltration using a 10 kDa MW cut-off membrane (Prevot-D’Alvise et al., 2003). According to Yang et al. (2004) the pepsin digest of leaf protein with a high Rubisco content could potentially be useful in the prevention and/or treatment of high blood pressure (hypertension). So far, the influence of the degree of hydrolysis on the functional properties of leaf protein samples has not been investigated. Chemical modification can be subdivided into (i) hydrophilization (incorporation of polar groups, e.g. –COOH, -NH2, -OH), (ii) hydrophobization (incorporation of apolar groups, e.g. alkyl or aromatic) and (iii) cross-linking (covalent linking of protein molecules). Only a few studies exist regarding the chemical modification of leaf proteins. The succinylation of 84% of the ε-amino groups of lysine resulted in improved flavor, increased solubility (>10-fold), enhanced emulsifying activity (32%) and increased foaming capacity (3-fold) of protein isolated from alfalfa leaves (Franzen and Kinsella, 1976). Acetylation of leaf protein improved the solubility and foaming capacity also but to a much lesser extent. Studies of the soluble tobacco leaf proteins (F-1-p and F-2-p) confirmed an improvement in functionality by succinylation (Sheen, 1991). 4.1.7. Future Trends and Necessary Investigation In order to force the valorization of biomass components, it is important to develop a new market for leaf proteins. Besides the food and feed field, technical applications of proteins are a promising area. Such non-food applications cover a very heterogeneous market ranging from surfactants (emulsifiers, detergents, wetting agents), coatings (e.g. in paint, ink, paper, packaging), and adhesives to biodegradable plastics or materials (e.g. disposable dishes or cutlery). The market potential of renewable materials depends primarily on their superior
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performance, including functionality and price. The suitability of leaf proteins for such nonfood applications has been insufficiently tested. In most cases, the presence of antinutritive components, dark color or unpleasant grassy smell is not prohibitive to the use of leaf proteins in non-food products. The excellent interfacial and gelling properties of a properly extracted cytoplasmic fraction and Rubisco make them suitable for use as surfactants or film-forming agents in personal care products or biodegradable packaging films. The extreme purity of crystallized leaf protein (e.g. Rubisco from tobacco) may support its use in the field of medicine and pharmaceutics. Due to its large charge/mass ratio, Rubisco has a high tendency to bind ionic substances (Barbeau and Kinsella, 1988). This may allow it to be used as a sequestering agent for environmental pollution. Although for food applications it is important that the proteins are in the native (not denatured) state in order to exert the desired functionality, for technical applications this is less relevant (de Graaf, 2000). The basis for the formation of biomaterials is the reactivity of the macromolecules. The ability of water-insoluble plant proteins to produce biodegradable materials with antistatic and flame resistant properties (useful in electrical devices) will be described in order to demonstrate the potential of leaf protein in such applications. During a simultaneous treatment of pressure (1.2 MPa) and temperature (120 – 170°C) the raw materials (e.g. plant protein with 25% water or a mixture of plant proteins, native potato starch and/or dialdehyde starch with 25% water) were plasticized, fluidized and cooled to create materials with special mechanical properties (Bindrich, 2004). Different plant protein sources when used to make “bioplastics” demonstrate differences in mechanical behavior which cannot be predicted solely from the molecular status of the protein samples (Figure 7). Under certain conditions, the mechanical properties (bending elastic modulus) of composite materials made with wheat were superior to plexiglass (bending elastic modulus 1000 MPa) (Figure 8). At temperatures above 120°C it is so far impossible to predict changes within the protein molecules, i.e. breaking or forming of bonds, and their effects on the mechanical properties of biodegradable materials. Only experimental tests can provide the desired information. Hence, leaf protein concentrates (single or combined with other plant proteins or starch) have potential in the production of biodegradable materials. To date, nearly all information on protein denaturation has been obtained from research on solutions with water content > 90 wt%, and little research has been done in systems with water content lower than 30 wt%. The denaturation temperature of proteins strongly depends on the water content, and can increases to 120-200°C at water contents < 20 wt% (de Graaf, 2000). By using green leaf proteins in the production of packaging materials, the existing pigments (e.g. chlorophyll) could be used to protect light-sensitive substances from oxidation.
Biobased Polymers by Chemical Valorization of Biomass Components
B endin g elastic mo dulus (M Pa)
1400
471
P P-nS P-DAS P-nS-DAS
1200 1000 800 600 400 200 0 Pea
Maize Wheat Potato Rape
Plant Protein Figure 7. Mechanical properties of biomaterials made from protein (P) or a mixture of proteins, native starch (nS) and/or dialdehyde starch (DAS).
B ending elastic m odulus (MPa)
4000 3500
W W-nS W-nS-DAS
3000 2500 2000 1500 1000 500 0 120
130
140
145
150
155
160
170
Structuring temperature (°C)
Figure 8. Effect of structuring temperature on the mechanical properties of biomaterials made from wheat protein II (W) or a mixture of proteins, native starch (nS) and dialdehyde starch (DAS).
The tailoring of protein functionality by physical, chemical and enzymatic methods is a promising method for developing new non-food applications and should be utilized more extensively for leaf proteins. Due to numerous potential glutaminyl and lysyl sites, Rubisco (mostly its large sub-unit) is a good substrate for transglutaminase-directed modifications (Margosiak et al., 1990). This offers new opportunities for solvent stable membranes, biodegradable films and “bioplastics” with different mechanical firmness.
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4 2. Green Juice and Brown Juice as an Fermentation Media and the Products The GJ and BJ are an excellent fermentation media, as such, and mixed with cereal grain flours, molasses or other hexosen-riches substrates (Thomsen et al., 2004). As fermentation medium, BJ has been used for production of ethanol, lactic acid and other organic acids, plus feed proteins, lysine, soil bioactivators. Especially the fermentation products ethanol, lactic acid and other organic acids, amino acids such as lysine are high-values chemical Biorefinery products. Together with the PC levulinic acid these chemicals parent products and substances can be able to establish a biomass industry and a modern green chemistry.
4.2.1. Lactic Acid - Sequence Product Poly(Lactic Acid) Lactic acid has the potential to become a commodity chemical. High growth rates are expected: an annual volume of 1.36 to 1.8 million tons for lactic acid sequence products alone for the U.S.- market (Gruber, 2001).Chemical products of sequence are propylene glycol, propylene oxide, and epoxides. Propylene oxide is a starting material for the production of polyester, polycarbonates, polyurethanes. Further products are acrylic acid as monomer for polyacrylic acid and resins as well as alkyllactates for application as „green solvents“. Furthermore enantiomeric forms of lactic acid are applied in drugs, pharmaceuticals and agrochemicals. Classical areas of application are such as so-called culinary delight lactic acid, e.g. in food industry and technical processes such as tanneries, textile industry, chemical industry (Kamm et al, 2001). Enormously growing amounts are expected for polymeric materials of lactic acid, poly(lactic) acid. Polylactide is a versatile thermoplastic, which can be processed in manifold ways: e.g. spinning fibres, melting spinning fibres, extrusion foils, injection moulding, thermoforming sheets, extrusion coating for paper and board and many other applications. It is fully biodegradable and compostable and does not disturb the normal process of biodegradation in compost. Especially for the market segments of food packaging and food service, e.g. disposable articles) and performance-products for agriculture as well as fibres for textiles PLA is an very interesting material. In 1993, a market volume of 140.000 – 900.000 tons per year for biodegradable polymers on basis of lactic acid was estimated for the U.S.A. (Cargill,1993). Since then efforts were increased to build major industrial capacities. The company Cargill Dow LLC has built a commercial production facility for polylactide (PLA) in Blair Nebraska, U.S.A.. The Blair facility started its operations in late 2002 and has a maximum capacity of 140,000 metric tons of PLA per year (Hovey, 2002). The establishment of further capacities of the company shall follow within the next 10 years up to a capacity of 450,000 metric tons in Asia and Europe. So it is expected that the price will decrease within the next years to the level of petrochemical based thermoplastics (Cargill Dow, 2001). The Polylactid technology starts with the classical variant of lactic acid fermentation (primary production of inorganic salts of lactic acid) via further steps of production of lactic acid and oligomeric lactic acid, subsequently synthesis of cyclic diesters of lactic acid, from which the polylactide is accessible by ring opening reaction. In this technology principle the two processing steps (biotechnological production of lactic acid and the subsequent chemical steps) are clearly separated (Kamm and Kamm, 1998).
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A new technology principle is patented and briefly drafted in Figure 4 (Kamm et al. 1996, Kamm et al. 1997). Aminium lactates act as alternative coupling reagents to connect biotechnological and chemical conversion (synthesis of dilactide). Requirements on amium lactates are low melting points, good crystallinity and good thermal or hydrolytic dissociation ability. Requirements on amines are good water solubility, a pH-value within basic area, sufficient thermal, acid and catalyst stability for the recycling according to the cyclization process, ecological harmlessness and economical availibility. Piperazine dilactate is for example a well investigated model substance (Kamm et al, 2001), (Figure 9).
CH2OH O H H
H HO HO
H
OH H
OH
+
H N
-2 H2O - (H2O)
piperazine
glucose
H N
H
H N
H3C
CH COO
OH piperazinium-dilactate
N H H2SO4 + 2 H3C CH COOH
piperaziniummonosulfate H N
N H
( H2O ) fermentation (lactobacillus)
2
N H
H
+ H2SO4
OH lactic acid + 2 NaOH
N H + 2 H2O + Na2SO4
piperazine (or piperazinium hydrate)
cat. / temp.
H3C O
+ 2 H2O
O
O
O
CH3
dilactide
elektrodialysis H2SO4 + 2 NaOH
Figure 9. Principle of procedure of extremely pure lactic acid and of dilactide based on aminium lactates.
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In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 481-500
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 17
EXPERIMENTAL ANALYSIS OF SMALL COMBUSTION THERMAL SYSTEMS BASED ON PELLETS *
J.C. Morán†1, J.L. Míguez, E. Granada and J. Porteiro Universidad de Vigo - E.T.S. Ingenieros Industriales, Lagoas-Marcosende, s/n. 36200 -Vigo (Pontevedra), Spain
ABSTRACT In this chapter a set joint of experimental techniques for assessing biomass combustion devices is presented. Small scale energy converters such as chimneys, boilers, stoves, etc, producing heat and/or hot water by combustion of biomass (wood, pellets, briquettes, etc.) are especially suited to domestic purposes. However, in regular commercial combustion conditions, this kind of use still has some disadvantages: besides the fact that some emissions (volatile organic carbons, carbon monoxide or NOx) may still be high, it is difficult to compare the quality and performance of equipment working in very different combustion conditions. Due to their relatively low cost and the complexity of combustion in such devices, modelling by numerical analysis is seldom attempted. Controlling operational factors are usually designed and regulated based on the manufacturer’s experience or on handbook values. In order to protect customers, and to assure compliance with minimum requirements for energy performance and maximum limits on pollutant emissions, several national and international regulations have been developed in recent years. Experimental analysis of these devices is a key technique for control and improvement.
1. INTRODUCTION There are numerous discussions in the literature about the uncertainties in the analysis and design of thermal systems, taking into account their stochastic nature. This chapter *
A version of this chapter was also published in Progress in Biomass and Bioenergy Research edited by Steven F. Warnmer published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research. † Universidad de Vigo - E.T.S. Ingenieros Industriales. Lagoas-Marcosende, s/n. 36200 -Vigo (Pontevedra). Spain. e-mail: (1)
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presents a description of the problem in terms of experimental design and subsequent analysis. Although there are also several practical methods for performing relative analysis the authors present here a still relatively unknown technique based on Grey Theory. Particularly, a method based on this theory called the grey relative analysis is a very simple, reliable analysis tool for time sequence and dispersed series. The use of grey relational analysis combined and compared with classical statistical experimental design and analysis applied to the optimising of a pellet combustion device is described as an application of the combination of the techniques. The use of biomass, a renewable energy source, instead of fossil fuels in heat and power generation is increasing, and is a way of reducing global CO2 and sulphur emissions and saving on diminishing fossil fuels. The use of wood pellets in small-scale systems is an increasing alternative for producing heat and hot water in the household sector. In Spain, just over half energy from renewable sources used involves biomass, which is limited almost solely to heat applications. With regard to thermal applications of biomass, the Renewable Energy Promotion Plan in Spain 1999-2010 [1] developed under the recommendations of the European White Paper [2] highlights the need for improvement in domestic equipment (typical residential equipment in a power range of 8 to 30 kW). The regional distribution of consumption is heavily related to the presence of the paper and pulp manufacturing sector, timber and food industries and the household sector. According to estimates from the 3rd National Forest Inventory, the amount of biomass in Galicia (northwest of Spain) exceeds 600,000 tm a year [3]. Residues derived directly from forest waste represented about 40% of the total (of which: Pine 38%, Eucalyptus Branches 22%, Crust of Eucalyptus 28%, Others 12%). The energy use of residual wood is limited because of its low density. Waste from primary and secondary timber processing accounts for 20-30% in volume of all the raw material used. Biomass pelletising is a densification process that improves its handling characteristics, enhances its calorific value per volume, reduces transportation costs and produces a uniform fuel. Therefore, wood pellets are an alternative not only to non-treated wood but also to the traditional fossil fuels used in small-scale house heating systems [4, 5]. Typical characteristics of lignocellulosic pellets are low moisture content (700 kg⋅m-3) and a heating value around 17000 kJ/kg with a diameter between 5 and 12 mm [6]. The previous mentioned specifications make pellets very interesting for ordinary central heating systems. Moreover, they are an alternative to fossil fuels in small and average size boilers, and also in district heating plants and small scale house heating systems [7]. However, this kind of use still has some drawbacks, as emissions of pollutants such as VOC (Volatile Organic Carbons), CO (carbon monoxide) and NOx still tend to be high (Table 1) [8]. Consequently, small-scale biomass pellet combustion technologies need further research to help to develop new equipment to meet current and future demand [9,10, 11]. Pellets burn cleaner than wood because the feeding rate is regulated and coupled with the accurate amount of air in order to obtain an optimum burn rate. Pellet fuel is made mainly of sawdust and shavings, or fine branches and leaves left over after processing trees for lumber and other wood products. Wood pellet handling is well-known and its aptness for boilers is one of its main advantages, especially in small-scale residence heating systems. In such pellet combustion devices, it is important to select appropriate operational parameters to achieve optimal performance. The desired parameters for solid fuels are usually determined on the
Experimental Analysis of Small Combustion Thermal Systems Based on Pellets 483 basis of manufacturer experience or on handbook values [12]. But even with optimal operation parameters, it is difficult to compare the quality and performance of equipment working in such rather different combustion conditions [13, 14, 15]. The main reasons for high pollutant emissions are the relatively low combustion temperatures and the insufficient mixing rate between air and combustible gases resulting from pyrolysis and heterogeneous combustion of solid particles [16]. Table 1. Typical stove emissions Emissions (mg/kWh) CO SO2 NOx Particles NMVOC
Fuel
Gas
Pellet
10 350 350 20 5
150 20 150 0 2
250 20 350 150 10
2. THEORY One important issue would be to control the operational factors to achieve an overall optimal response, or at least some sort of indicator to quantify the gap related to the most possible favourable value. Thus, this kind of problem requires innovative management approaches, such as those that will ensure joint consideration of economic, ecological and social issues. Another growing concern is consumer interest in environmental labels and certificates. Several methods and certification systems exist in Europe [17, 18, 19]. One of the most popular is the Swedish method called P-marking or labelling. From this point of view, integrating and qualifying all performance aspects of a device in a 0 to 1 scale is a very simple and intuitive labelling possibility. Grey relational analysis is part of grey system theory, which is suitable for solving the complicated interrelationships between multiple factors and variables; in this case, how efficiency, emission variables and fuel prices clutch on to control variables. A grey system is defined as a system containing unknown information presented by grey numbers and grey variables [20]. In grey theory, black represents a system devoid of information, while white stands for complete information. Thus, the information that is either incomplete or undetermined is called grey. System theory was initiated by Deng in 1982, and has been widely applied in the last decade in China in several research fields [21, 22]. In many cases the improvement of one performance characteristic may be to the detriment of another. In this research, the successively combination of experimental design classical statistic analysis and the use of grey relational analysis applied to the energetic and economic assessment and optimisation of combustion of wood pellets has been studied [23, 24, 25, 26, 27].
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2.1. Experimental Design In many situations it is desirable to learn something about the association between two attributes of an individual, material, a product, or for instance a complex process like pellet combustion. The problem then consists of determining the nature and degree of the relation. In regression analysis a regression equation is fitted to an observed point cloud of measured variables [28]. The effect caused by a simple variable when many influencing variables change at the same time is not easily to determine [29, 30]. Experimental design and subsequent statistic analysis is useful to find these correlations with minimum test runs and avoiding lost of generality in conclusions [31, 32, 33]. Statistics experimental design demands a minimum number of experiments avoiding a lost of generality in conclusions. These techniques provide valid conclusions and coupled with Anova define which are the most influential factors. This work is focused on the analysis of the response of certain variables as an empirical function of one or more quantitative factors. A general form of this type of response function is y = f ( x 1 , x 2 , x 3 ......)
(1)
where y variable is the response, and x1, x2, x3 are quantitative levels of the factors of interest. Knowledge of the form of the function f, will be found by fitting accurate correlations models to data obtained from designed experiments. When the response is a function of one or two factors, the fitted model is referred as a response surface because it can be graphed in one or two dimensions respectively, and can be explored to determine important characteristics such as optimum operating conditions or relevant tradeoffs. Complete factorial designs require a lot of experiences depending on number of factors, k, and their corresponding number of levels, number of tests points in which the range of a selected variable will be measured. test runs = n = p k
(2)
In order to avoid an unaffordable number of experiences, three level factorial experiments are often conducted in order to fit such response surfaces. Two level factorial would require less tests, but could not detect curvature on the surface (maximums or minimums). As the number of factors increases, even three levels complete factorials become inefficient and impractical. Further, these design do not give equal precision for fitted responses at points (factor level combinations) that are at equal distances from the centre of the factor space, so that the exploration of the response surface would be dependent on the orientation of the design. In this study every experiment set has at least three levels in order to study possible second grade tendencies. A design that has the property of equal precision at equal distances is termed a rotatable design. Rotability is a desirable property for response surfaces models because prior to the collection of data and the fitting of the response surface, the orientation of the design with respect to the surface is unknown. In general rotatable designs can be constructed from equally spaced points on circles or spheres. For more than two factors, design points should
Experimental Analysis of Small Combustion Thermal Systems Based on Pellets 485 lie on a sphere, or a hyper sphere in four or more dimensions. The design points must also form a regular geometric figure. All 2k complete factorials are rotatable but 3k are not. Table 2. Experimental layout examples in coded variables
1
3 factors Central composite design Factor Factor Factor a b c -1 -1 -1
2 factors Complete factorial design Factor Factor a b -1 -1
2
-1
-1
+1
-1
0
3
-1
+1
-1
-1
+1
4
-1
+1
+1
0
-1
5
+1
-1
-1
0
0
6
+1
-1
+1
0
+1
7
+1
+1
-1
+1
-1
8
-1.68
+1
+1
+1
0
9
+1.68
0
0
+1
+1
10
0
0
0
11
0
-1.68
0
12
0
+1.68
0
13
0
0
-1.68
14
0
0
+1.68
15
0
0
0
16
0
0
0
17
0
0
0
Run Test
There are classes of designs for two or more factors that can be used in place of 3k factorials for fitting second order polynomials to response surfaces. One design that makes more efficient use of the test runs is the central composite design, and an extra advantage is, that this design can be made rotatable. The total number of test runs in a central composite design, is based on a complete 2k factorial design, but they only require enough extra observations to estimate the second order effects of the response surface. In this case n = 2 k + 2k + m
(3)
which is less than 3k, so that fewer observations are required than in a 3k factorial design. “m” is the number of repeated observations at the design centre necessary to ignore interaction effects and “a” is the absolute extreme value of the desired studied interval. The central composite design can be made to be rotatable by choosing a = F1/4, where F is the number of factorial points. (F = 2k) In this case five levels of each factor has to be considered, coded (+a, +1,0,-1, -a)
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J.C. Morán, J.L. Míguez, E. Granada et al.
2.2. Contrast of Equations Many times it is difficult to decide which regression or correlation equation is appropriate. In the natural sciences every equation connects only precise quantities and the question of which variable is independent is often irrelevant. But in our case the aim is to find cause, find out which are the actual factors that influence each and every variable. A measure for how well the regression line explains the observed values is the so called coefficient of determination R2. How ever the factual interpretation of any statistical relations, and their testing for possible causal relation, lies outside the scope of statistical methodology. Even when stochastic dependence appears certain, one must bear in mind that the existence of a functional relation says nothing about a causal relation. The recognition of a causal correlation thus follows from the exclusion of other possibilities. Consequently the size of the correlation coefficient will not make any difference in this context. In order to contrast a correlation (mathematical model of the process) an evaluation process is necessary. One common procedure is by the analysis of variance (ANOVA). As result correlations are evaluated and contrasted by ANOVA and validated considering phenomenon like multicollinearity (variance inflation factors, eigenvalues, …) influence factors (Cook distance…), auto-correlation (Durbin Watson…), heterocedasticity, etc.
2.3. Grey Theory The grey system theory, first proposed by Professor Julong Deng in 1982 avoids he inherent defects of conventional statistical methods and only requires a limited amount of data to estimate the behaviour of an uncertain system. The major advantage of Grey theory is that it can handle both incomplete information and unclear problems very precisely. It serves as an analysis tool especially in cases when there is insufficient data [34]. It was recognized that the Grey relational analysis in Grey theory had been largely applied to project selection, prediction analysis, performance evaluation, and factor effect evaluation due to grey relational analysis software development. There are numerous literature discussions regarding the uncertain in the analysis and design of the thermal system taking into account the stochastic nature. There are also several practical methods to perform relative analysis: parameter analytical method in mathematical statistics, orthogonal test analytical method and grey relative analytical method. Of these, the method of grey relative analysis is best suited to the relative analysis of time sequence and dispersed series [35, 36]. Considering a grey system where a set of variables yi depend on certain independent factors xj, all the possible combination of normalized experimental results xij can be expressed if the performance characteristic is the higher the better as: y ij -min y ij x ij =
j
max y ij - min y ij j
j
(4)
Experimental Analysis of Small Combustion Thermal Systems Based on Pellets 487 where yij is the ith experimental result in the jth experiment. Or if the performance characteristic is the lower the better pattern, as: y ij -max y ij x ij =
j
min y ij - max y ij j
(5)
j
The grey relational coefficient, ξij, is calculated to express the relationship between the ideal (best) and the actual normalized experimental results
ξij =
min min x io - x ij + ζ max max x io - x ij i j i j x io - x ij + ζ max max x io - x ij i j
(6)
where xi0 is the ideal standardised result for the ith performance characteristic and ζ is the socalled distinguishing coefficient (0≤ζ ≤1). The overall evaluation of the multiple variables is based on the grey relational grade, which is computed by averaging the grey relational coefficient corresponding to each performance characteristic,
γj =
1 m ∑ξ m i =1 ij
(7)
where γj is the grey relational coefficient for the jth experiment and m is the number of performance characteristics (variables).
2.4. Procedure for the Experiment To reduce the influence of any factors other than those studied here, a strict measurement procedure is applied. A stove of this kind never attains complete steady-state operation, mainly due to its batch feeding system, which in our case is controlled “pellet by pellet”. If the measuring system is fast enough, an appreciable fluctuation may be detected after each pellet falls into the bed, as a result of the stir produced in the particularly thin bed that exists in this kind of fixed bed combustion system (this fluctuation is normally only detected by the CO analyser). For that reason we chose to follow the remaining variables (20 temperature readings, 6 pressure readings, 5 flows and the concentration of the rest of the gas species) until no variation was observed (which in several cases took more than 2 hours). Once the steady state was achieved, data recording was started. This took 20 minutes initially, but was subsequently extended to 60 minutes [37, 38].
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3. EXPERIMENTAL The University of Vigo (Spain) has developed a pilot plant to study pellet combustion in its different configurations and load conditions, taking into consideration both the energy and environmental viewpoints. The core of the plant is a commercial stove which has been modified to allow multiple controlled combustion conditions [39]. As with every complex system, in pellet combustion the effect caused by a single variable is not easily determined when many influential variables change at the same time. Experimental design techniques and subsequent statistical analysis of their results are useful to determine these correlations with a minimum number of test runs with no loss of generality in the conclusions. Many papers on this methodology have been published in many research fields since Box and Wilson developed the idea, some of which have dealt with combustion systems, but none has been reported that applies to pellet combustion in small systems. Previous tests at our experimental plant revealed that the use of flue gases to preheat primary air improves the system’s overall performance. Consequently the use of secondary air and/or gas recirculation, which has been successfully applied in bigger systems, may also be interesting [40]. The planning of the experimental part demands that the number of experiments should be minimised without loss of generality in conclusions. Due to the heterogeneity of the pellet, a minimum number of experiments is needed [41]. The most appropriate type of experiment and also the number of experiments are determined. These experiment design techniques provide valid conclusions and define which the most influential factors are. They also show the predicted tendencies in order to achieve a better efficiency of the general process [42].
3.1. Plant Description An experimental plant has been used for this research (Figure 1). The main parts of this plant are the feeding system and the combustion unit.
Figure 1. Pilot Plant General View.
Experimental Analysis of Small Combustion Thermal Systems Based on Pellets 489 In order to study the combustion of different mixtures of pellets and even potentially cheap forest residues, a new feeding hopper for domestic biomass boilers has been implemented in the plant. This new hopper consists of a 200 mm wide (100 mm per product) band that drags both materials, pellet or forest residues, at the same time. The feeding rate can be regulated by means of a floodgate (0-40 mm height) or by changing the conveyor speed.
Figure 2. Combustion chamber scheme.
The combustion unit can be described as a pellet stove surrounded by a water jacket and vacuum operated, where pellets drop from the hopper into the combustion grate while combustion air is supplied upwards, through the grate. The stove has also a window door for ornamental purposes, maintenance and radiation heating purposes, which is closed for normal heat production. The combustion chamber has been adapted to allow multiple combinations of gas supply (primary and secondary air or already burnt gases, as desired) and also several access ports have been installed in the sidewalls and in all its gas-lines to facilitate the measurement of pressure, temperature, mass flow and gas concentration. The whole combustion device is isolated to calculate energy balance and efficiency.
Control and Analyses Equipment • Pressure: is measured by SIEMENS transducers (Sitrans – P) • Temperature: measured through thermocouples and RTD’s (Pt-100). • Combustion chamber exchangers, air and gas tubes have been isolated with polystyrene. • Pellet flow rate control: moved by a controlled motor that determines the amount of pellet introduced in the combustion chamber. Flow is determinate measuring hopper weigh changes with an extensiometric gauge. • Air flow rate: is controlled pressure drop by means three speed regulated fans. • Water jacket temperature: is fixed with a regulated secondary water flow circuit • Gas composition: gas analyses were carried out using a Horiba PG250 and TESTO-350 to measure gas concentrations of the main components involved: NOx/SO2/CO/CO2/O2
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3.2. Material Typical characteristics of lignocelluloses pellets are low moisture content (700 kg⋅m-3) and a heating value around 17000 kJ/kg with a diameter between 5 and 12 mm, and prices in Galicia are between 25 to 30 €/MWh. The previous mentioned specifications make pellets very interesting for ordinary central heating systems, and especially for single-family houses, which are very common in Galicia. In this work, two relatively different kinds of pellet are tested. Table 3. Pellets properties
Diameter (mm) Length (mm) Density1 (kg⋅m-3) Moisture (% WB) Proximate Analysis (wet % dry basis) Ash (550 ºC) Ultimate Analysis (wet % dry basis Ash free) Carbon Hydrogen Oxygen Nitrogen Sulphur 1 Geometric method.
Pellet 1 7 7-21 1166 8.5
Pellet 2 6.6 10-15 943.4 9.5
0.68
0.90
51.7 6.7 40.7 0.17 < 0.05
52.0 5.3 42.0 0.92 < 0.05
4. RESULTS AND DISCUSSION Previous test analysis shows the dominance of just two main factors mp and n. To study secondary air influence an amount M2 (air flow rate in l/s) of the total air introduced into the stove, MT A, (air flow rate in l/s), is forced through the lateral pipes. The ratio sa = M2 / MT A is selected as the factor for Set SA. The study covers a range from 0 to 0.30 of this factor. Analogously, to study the effect of smoke recirculation part of the flue gas, MR (gas flow rate in l/s), of the combustion chamber MTS (gas flow rate in l/s) is again introduced into the stove, sr = MR / MT S is the third factor selected for Set SR. The study covers a range from 0 to 0.30. Changes in the factors have an effect on variables but there is no simple direct relation in these changes, as each variable also depends on other factors. Therefore, correlations between factors and variables needed a statistical approach.
Experimental Analysis of Small Combustion Thermal Systems Based on Pellets 491
4.1. Variables and Factors In accordance with previous tests, two different experimental designs are used to determine the controlling factors for pellet combustion in such stoves. The variables studied for different combustion conditions are heat in water Qw , heat in flue gases Qs , stove efficiency ηst , combustion efficiency ηc and exhaust gas composition. Statistical experimental design coupled with ANOVA defines which the most influential factors are. Table 4. Factors and variables Factors Stoichiometric ratio Pellet supply Secondary air Recirculation fraction Variables QW (kW) Heat in water QS (kW) Heat in flue gas QT (kW) = QW + QS Liberated heat 1 Supplied heat QA (kW) = mp × LHV Stove efficiency ηst = QW / QA Combustion efficiency ηc = QT / QA CO (g/kWh Pellet) CO emissions (gases) NO (g/kWh Pellet) NO emissions (gases) n mp (gr/s) sa sr
1
LHV = low heating value wet basis
Table 5. SET SA and SET SR factor levels before randomising
Set SA Coded levels mp(gr/s) +1.68 2.0 +1 1.8 0 1.5 -1 1.2 -1.68 1.0
n 2.00 1.84 1.60 1.36 1.20
Set SR sa (%) mp (gr/s) 30 2.0 24 1.8 15 1.5 6 1.2 0 1.0
n 2.00 1.84 1.60 1.36 1.20
sr (%) 30 24 15 6 0
4.1.1. Secondary Air (Set Sa) The heat transferred to water depends on the amount of pellet supplied (mp), and, to a lesser extent, on n. The amount of secondary air used has no significant influence. Heat in smoke increases linearly with the contribution of both mp and n. Secondary air reduces CO emissions, with n still being the critical factor, but the amount of secondary air is also significant even for combustion conditions where CO emissions are at their lowest (n approximately 1.65).
492
J.C. Morán, J.L. Míguez, E. Granada et al. Table 6. Experimental results. Set SA Mp
n
sa
ηst
ηc
Qw
CO
NO
g/s 2.00
1.60
0.15
0.73
0.87
23.25
g/kWh 17.26
g/ kWh 0.63
1.50
1.60
0.30
0.75
0.86
19.97
2.72
0.68
1.80
1.80
0.24
0.72
0.87
21.92
2.92
0.74
1.20
1.40
0.06
0.74
0.81
15.31
40.56
0.45
1.20
1.40
0.24
0.74
0.81
15.15
21.29
0.51
1.20
1.80
0.06
0.77
0.87
15.84
9.90
0.61
1.20
1.80
0.24
0.78
0.89
16.30
3.67
0.64
1.50
1.60
0.15
0.71
0.82
18.66
23.71
0.53
1.50
1.20
0.15
0.62
0.69
16.21
40.45
0.43
1.50
2.00
0.15
0.74
0.88
19.07
4.87
0.67
1.50
1.60
0.15
0.73
0.84
18.65
15.20
0.47
1.00
1.60
0.15
0.80
0.88
12.99
11.12
0.52
1.50
1.60
0.00
0.74
0.85
18.99
17.89
0.53
1.80
1.40
0.24
0.70
0.81
21.21
18.25
0.49
1.80
1.80
0.06
0.68
0.83
21.56
3.55
0.85
1.80
1.40
0.06
0.70
0.81
20.9
23.49
0.45
1.50
1.60
0.15
0.74
0.85
18.6
12.32
0.48
Lowest value
0.62
0.69
12.99
2.72
0.43
Highest value
0.80
0.89
23.25
40.56
0.85
Test
SA -1 SA - 2 SA - 3 SA - 4 SA - 5 SA - 6 SA - 7 SA - 8 SA - 9 SA - 10 SA - 11 SA - 12 SA - 13 SA - 14 SA - 15 SA - 16 SA - 17
4.1.2. Smoke Recirculation (Set SR) The heat transferred to water depends mainly on the two factors mp and n, with mp being the more significant of the two. The amount of recirculation has only a small influence. Heat in smoke (QS) increases linearly with the contribution of both mp and n. Emissions, however, are affected by recirculation. CO can be reduced significantly by ensuring a proper air-fuel rate and with a relatively low degree of recirculation of smoke.
Experimental Analysis of Small Combustion Thermal Systems Based on Pellets 493 Table 7. Experimental results. Set SR Test
Mp
n
sr
ηst
ηc
Qw
g/s
CO
NO
g/kWh
g/ kWh
SR -1
1.2
1.36
0.06
0.81
0.89
17.46
23.84
0.25
SR - 2
1.5
1.20
0.15
0.70
0.79
19.45
27.86
0.21
SR - 3
1.5
1.60
0.15
0.80
0.93
21.40
7.04
0.33
SR - 4
1.2
1.84
0.06
0.82
0.94
17.85
3.45
0.34
SR - 5
1.5
1.60
0.30
0.84
0.99
20.11
2.41
0.40
SR - 6
1.8
1.36
0.06
0.80
0.92
23.81
35.31
0.30
SR - 7
1.5
2.00
0.15
0.73
0.88
20.39
2.90
0.42
SR - 8
1.8
1.84
0.06
0.79
0.95
24.26
4.80
0.42
SR - 9
1.0
1.60
0.15
0.87
0.95
15.49
3.02
0.27
SR - 10
1.2
1.36
0.24
0.83
0.91
17.33
7.05
0.25
SR - 11
2.0
1.60
0.15
0.76
0.91
25.02
3.04
0.39
SR - 12
1.5
1.60
0.15
0.78
0.91
20.47
5.76
0.33
SR - 13
1.8
1.36
0.24
0.72
0.84
23.08
2.37
0.32
SR - 14
1.8
1.84
0.24
0.77
0.94
22.39
1.86
0.42
SR - 15
1.5
1.60
0.00
0.87
0.99
21.50
20.99
0.33
SR - 16
1.5
1.60
0.15
0.83
0.95
21.72
7.21
0.32
SR - 17
1.2
1.84
0.24
0.80
0.92
17.39
1.25
0.35
Lowest value
0.70
0.79
15.49
1.25
0.21
Highest value
0.87
0.99
25.02
35.31
0.42
4.2. Statistical Analysis An extensive statistical analysis of each variable may obtained contrasted correlations for both sets of measures. Relatively high correlation index R2 is obtained in the regressions for both energy and emissions variables. Concerning energy efficiency neither recirculation of air nor smoke has major advantages, at least directly. Best efficiency is obtained with low loads and high air fuel ratio (n = 2). However if CO is an important question recirculation of smoke reduces remarkably the emissions. Greatest reduction is obtained with low air fuel ratios (n < 1.5). In addition, as NO emission increase with the air fuel ratio, recirculation of smoke can help to get an overall optimum combustion as it make possible to work with lower n, low NO emissions, without a big loss in efficiency (only 5%) and lower CO emission as combustion without recirculation and an air fuel ratio of n = 2.
494
J.C. Morán, J.L. Míguez, E. Granada et al. Table 8. Statistical results R2C SET SA QW(kW) = 9.83⋅mp + 2.35⋅n
99.9%
QS(kW) = - 5.62 + 3.39⋅mp + 2.14⋅n
98.6%
CO gr/kWhPellet = 62.68/n - 62.43⋅(sa)
84.1%
NO gr/kWhPellet = 0.135 ⋅ n2 + 0.145⋅mp
98.3%
2
ηC = 0.78 + 0.26⋅n⋅mp-1 - 0.33⋅mp-1 ηst = 0.58 + 0.14⋅(n⋅mp-1)
SET SR QW(kW) = 10.9 ⋅ mp + 2.58⋅n
99.8%
QS(kW)= -5.48 + 3.51⋅mp + 2.17⋅n
98.6%
CO gr/kWhPellet = 51.33/n2 - 76.7⋅ (sr)
81.9%
NO gr/kWhPellet = 0.07 ⋅ n2 + 0.10⋅mp
99.5%
ηC (%) = 82.84 + 27.3⋅n⋅mp-1 - 31.5⋅mp-1 ηst (%) = 62.67 + 14.8⋅(n⋅mp-1)
The optimisation of pellet combustion as a whole means achieving that combination of independent process parameters (factors) that leads to the highest possible values of heat in water, with the best achievable efficiencies, and the lowest attainable emissions of NO and CO. As a result, an improvement of one variable may be in detriment to another variable that depends on the same controlling factor (example SET SA in Table 9). Table 9. Performance characteristics. SET SA Factors
Correlated Variable
Goal
mp
n
QW
↑
↑
↑
ηst
↑
↓
↑
Not coupled
ηc
↑
↑
↑
Not coupled
CO
↓
Not coupled
↑
NO
↓
↓
↓
↓ Not coupled
Sa Not coupled
Optimisation of the multiple variables cannot be as straight-forward as the optimisation of a single variable. Consequently the problem is not only to detect which is the best configuration but also to define the optimal combustion that would involve simultaneous maximal stove and combustion efficiency (highest value) and minimum emissions (lowest value). Thus, the optimal operation conditions cannot be easily established and need the definition of the grey relational grade (GRG). Through this new variable, tests can not only be
Experimental Analysis of Small Combustion Thermal Systems Based on Pellets 495 compared, but also the optimisation studying the correlation of the GRG with the factors means the optimisation of the whole combustion process.
4.3. Grey Relational Grade In the grey relational analysis method, experimental data (combustion efficiency, stove efficiency, CO emissions, NO emissions) are first normalised in the range between zero and one, which is also called the grey relational generation. Subsequently, the grey relational coefficient is calculated from the normalised experimental data to express the relationship between the desired and actual experimental data. The grey relational grade is then computed by averaging the grey relational coefficient corresponding to each process response. The overall evaluation of the multiple process responses is based on the grey relational grade. Experimental results of selected performance characteristics (stove and combustion efficiency and CO and NO emissions) were standardised to calculate the grey relational coefficient of each variable. The grey relational grade (GRG) was calculated by averaging the grey relational coefficient. Certain experimental results are given in Table 10. The influence of each factor using the averaged grey relational grade for each level was analysed. A higher value of the grey relational grade represents a stronger relational degree between the reference sequence x0(k) and the given sequence xi(k). As mentioned before, the reference sequence x0(k) is the best process response in the experimental layout. In other words, optimisation of the complicated multiple process responses can be converted into optimisation of a single grey relational grade. Depending on which group of performance characteristics are included in order to calculate the Grey Relational Grade, different scales are obtained. As the grey relational coefficient, ξij, express the relationship between the ideal (best) and the actual normalized experimental results, so best operational conditions for ηst performance were obtained in tests coded SR-9 and SR-15, those for ηc performance were obtained in tests coded SR-5 and SR-15, those for CO performance in test number SR-17, and those for NO performance was obtained in test number SR-2. Just as classical statistical analysis show, but straightforwardly, the grey relational grade including all tests (SET SA+ SET SR) illustrate that SET SR is better (Figure 3). The influence of each factor on grey relational grade can be studied as each factor is an independent variable. According to this factor analysis, optimum is obtained around mp = 1.00, n = 1.60, sr = 30%. This optimum was verified through a confirmation experiment and recalculation of new relational coefficients and grey relational grades. The inclusion of confirmation test achieved a new highest GRGN on this new scale (SET SA + SET SR + OPTIMUM), higher than previous best value test (former value 0.89, in new scale 0.87). This optimum means that although not all performance characteristics achieved the best values individually, this combination of factors produced the best possible overall averaged values.
496
J.C. Morán, J.L. Míguez, E. Granada et al. Table 10. Grey relational grade SET SA + SET SR Test
mp
n
sa
sr
g/s
ηst
ηc
CO
NO
ξij
ξij
ξij
ξij
GRG
SA-1
2.0
1.6
0.15
-
0.48 0.56 0.55 0.43
0.50
SA-2
1.5
1.6
0.30
-
0.51 0.53 0.93 0.40
0.60
SA-3
1.8
1.8
0.24
-
0.45 0.55 0.92 0.37
0.57
SA-4
1.2
1.4
0.06
-
0.49 0.45 0.33 0.57
0.46
SA-5
1.2
1.4
0.24
-
0.49 0.46 0.50 0.52
0.49
SA-6
1.2
1.8
0.06
-
0.56 0.56 0.69 0.45
0.56
1.2
1.8
0.24
-
0.59 0.60 0.89 0.43
0.63
SA-8
1.5
1.6
0.15
-
0.45 0.47 0.47 0.50
0.47
SA-9
1.5
1.2
0.15
-
0.33 0.33 0.33 0.60
0.40
SA-10
1.5
2.0
0.15
-
0.49 0.58 0.84 0.41
0.58
SA-11
1.5
1.6
0.15
-
0.47 0.50 0.58 0.55
0.53
SA-12
1.0
1.6
0.15
-
0.63 0.57 0.67 0.50
0.59
SA-13
1.5
1.6
0.00
-
0.50 0.52 0.54 0.50
0.51
SA-14
1.8
1.4
0.24
-
0.42 0.46 0.54 0.54
0.49
SA-15
1.8
1.8
0.06
-
0.40 0.48 0.90 0.33
0.53
SA-16
1.8
1.4
0.06
-
0.43 0.45 0.47 0.57
0.48
SA-17
1.5
1.6
0.15
-
0.49 0.51 0.64 0.54
0.55
SR -1
1.2
1.36
-
0.06
0.68 0.60 0.47 0.89
0.66
SR -2
1.5
1.20
-
0.15
0.43 0.43 0.42
0.57
SR -3
1.5
1.60
-
0.15
0.65 0.71 0.77 0.73
0.71
SR -4
1.2
1.84
-
0.06
0.72 0.75 0.90 0.71
0.77
SR -5
1.5
1.60
-
0.30
0.81
0.94 0.62
0.84
SR -6
1.8
1.36
-
0.06
0.65 0.68 0.37 0.79
0.62
SR -7
1.5
2.00
-
0.15
0.48 0.58 0.92 0.60
0.64
SR -8
1.8
1.84
-
0.06
0.61 0.79 0.85 0.60
0.71
SR -9
1.0
1.60
-
0.15
0.79 0.92 0.84
0.89
SR -10
1.2
1.36
-
0.24
0.76 0.65 0.77 0.91
0.77
SR -11
2.0
1.60
-
0.15
0.54 0.65 0.92 0.64
0.69
SR -12
1.5
1.60
-
0.15
0.59 0.65 0.81 0.73
0.70
SR -13
1.8
1.36
-
0.24
0.46 0.50 0.95 0.75
0.66
SR -14
1.8
1.84
-
0.24
0.56 0.75 0.97 0.60
0.72
SR -15
1.5
1.60
-
0.00
0.50 0.73
0.81
SR -16
1.5
1.60
-
0.15
0.76 0.79 0.77 0.74
0.77
SR -17
1.2
1.84
-
0.24
0.65 0.68
0.76
1
1
1
1
1
1
0.70
Experimental Analysis of Small Combustion Thermal Systems Based on Pellets 497 SA GRG (SA+SR)
SR GRG (SA+SR)
1,00 0,90 0,80 0,70
GRG
0,60 0,50 0,40 0,30 0,20 0,10 0,00 1,15
1,25
1,35
1,45
1,55
n
1,65
1,75
1,85
1,95
Figure 3. Grey relational grade. Configuration analysis.
SR GRG (SA+RS) 1,00 0,90 0,80 0,70
GRG
0,60 0,50 0,40 0,30 0,20 0,10 0,00 0,85
1,05
1,25
1,45
1,65 mp
Figure 4. Grey relational grade. Factor dependence analysis.
1,85
2,05
2,05
498
J.C. Morán, J.L. Míguez, E. Granada et al. Table 11. GRGN - SET SA + SET SR + Optimum Test SR -9 Optimum
mp g/s 1.0 2.0
n
sa
sr
ηst
ηc
1.60 1.6
-
0.15 -
0.87 0.88
0.95 0.97
CO g/kWh 3.02 1.23
NO g/ kWh 0.27 0.36
GRGN 0.87 0.89
CONCLUSION This work carried out relative analyses on the multivariable relationships of pellet combustion in an improved domestic pellet boiler by means of the grey relative analytical method. Grey relational analysis is part of a Grey theory and is here applied to evaluate the combustion process. In addition to classical statistic techniques and by means of the grey rational grade, this methodology permits qualifying all the aspects of combustion with just a single variable. Consequently, the optimisation of complicated multiple responses can be converted into the optimisation of a normalized single grey relational grade. Indeed, the confirmation experiment shows that factor dependence analysis of the grey relational grade led to an “optimal combustion”.
REFERENCES [1] [2] [3]
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[7]
[8]
Instituto para la Diversificación y Ahorro de la Energía, IDAE. Plan de Fomento de las Energías Renovables en España. 1999 The European Commission. 97- 599 Energy for the Future: Renewable Sources of Energy. White Paper for a Community Strategy and Action Plan. 1997 Hernandez, C . Biomass in Spain: Activities, policies and strategies. The renewable energy promotion plan. 1st World Conference on Biomass for Energy and Industry. Sevilla. London: James and James Science Publishers Ltd. 2000. pp 1213-1216. OPET Sweden Framework. Refined biomass - a source for climate change and business opportunities Work package: Market development of refined biomass. EM-BM-1. 2001 Gustavsson, L; Tullin, C. and Wrande I. Small-scale biomass combustion in Sweden research towards a sustainable society. Proceedings of the 1st World Conference on Biomass for Energy and Industry. Sevilla. London: James and James Science Publishers Ltd. 2000 pp 1553 - 1555. Rösch, C.; Kaltschmitt, M. and Limbrick A. Standardisation of Solid Biofuels in Europe. Proceedings of the 1st World Conference on Biomass for Energy and Industry. Sevilla. London: James and James Science Publishers Ltd. 2000. pp 609-612. Obernberger, I. and Thek G. The Current State of Austrian Pellet Boiler Technology. BIOS Bioenergiesysteme GmbH. First World Conference on Pellets. Stockholm. Sweden. 2002. pp 45-48. Instituto para la Diversificación y Ahorro de la Energía, IDEA. Biocombustibles para edificios de viviendas.Ministerio de Economía. España M-49974-2002.
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Cotton, R.A and Giffard, A. Introducing wood pellet fuel to the UK. Renewable Heat and Powder Ltd. DTI Sustainable Energy Programmes – Altener Programme. 2001 Frandsen, S. Biomass Survey in Europe. Country Report of Denmark. Danish Technological Institute. Danish Energy Authority. European Bioenergy Networks. 2002. Egger, Ch. and Öhlinger, Ch. Strategies and Methods to Create a New Market. First World Conference on Pellets. Stockholm. Sweden. 2002. pp 35-37 Lasselsberger, L. Quality Marking and Environmental Testing of Small-Scale Biomass Boilers in Austria. Landtechnische Forschung (2000). Skreiberg, O. and Saanum, O. Comparison of Emission Levels of Different Air Pollution Components from Various Biomass Combustion Installations in the IEA Countries. Supplemental Report to the IEA-Project -Emissions from Biomass Combustion. The Norwegian Institute of Technology. Institute of Thermal Energy and Hydropower. 1995. Fiedler, F. The state of the art of small-scale pellet-based heating systems and relevant regulations in Sweden, Austria and Germany. Renewable and Sustainable Energy Reviews. 2004 vol, 8 pp 201 - 221. Dias, J:; Costa, M. and Azevedo, J.L.T. Test of small domestic boiler using different pellets. First World Conference on Pellets. Stockholm. Sweden. 2002. pp 137-141 Sjöstrom E. Wood Chemistry: Fundamentals and Applications. Academic Press. 1993. Oravainen, H. Testing methods and emission requirements for small boilers ( 1 due to activation of Ni and N, two alloying elements of AISI 316L
It is therefore impossible, even with impurity reduction, to reach the clearance goal for this material when irradiated as the plasma chamber constituent of Candor. In conclusion, EUROFER, SiC/SiC and V-Cr-Ti materials have shown the possibility of being declassified to non-radioactive material (clearance) after their irradiation in the reactor plasma chamber wall, if a sufficient interim cooling time is allotted. AISI 316L, on the contrary, suffers the presence of Ni and N (alloying elements) and Nb and Mo (impurities). Table 8. Detailed activation behaviour of AISI316L after 100 y of decay Nuclide Ni-63 C-14 Mo-93 Nb-93m Tc-99 Nb-94
Clearance Index 0.76 0.51 0.47 0.40 0.22 0.20
Original element Ni 99%, Cu 0.64% N Mo Nb 82%, Mo 17.2% Mo Nb 78.4%, Mo 21%
Advanced Fuel Fusion Reactors
839
Table 9. Clearance Indices for pure materials in Candor plasma chamber wall Element Fe Co Ni Mo C Nb N Al Cu Mn Ti Si Cr W B O
CI T = 30 y 0.0951 795000 1270 45 0.23 11000 756 0.553 932 0.1 < 0.001 0.0013 0.001 0.011 103 0.64
CI T = 50 y 0.0012 57000 99 45 0.21 9470 743 0.203 73.6 0.033 < 0.001 < 0.001 < 0.001 0.0059 33 0.63
CI T = 100 y < 0.001 79.5 6.1 45 0.20 8370 734 0.045 4.96 0.002 < 0.001 < 0.001 < 0.001 0.0018 2.0 0.63
CI T = 200 y < 0.001 < 0.001 3.1 45 0.19 8200 725 0.035 2.42 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.0096 0.62
6. CLEARANCE INDEX OF PURE ELEMENTS IN CANDOR It may be interesting to check the activation behaviour, as far as clearance index is concerned, of pure elements in DHe reactors materials. We have simulated the irradiation of an ideal material, containing 100 % of one element, in the Candor vacuum chamber wall. Results may be seen in Table 9. The following comments may be derived from the data reported in Table 9: • • • • • • • • • • •
Pure iron has a quite moderate activation. Cobalt activation is due to Co-60, hence its sudden decay between 100 and 200 y (Co-60 has a half-life of about 5.2 y) Nickel activation at 30 and 50 y is mainly due to Co-60, while Ni-63 is the most responsible nuclide at 100 and 200 y. Molybdenum activation is practically stable, due to Mo-93, Nb-94 and Nb-93m Carbon activation is due to C-14, at shorter term tritium is also important Concerning Nb activation, Nb-94 is the most responsible nuclide at long term, while at 30 y at 50 y Nb-93m is also relevant Nitrogen activation, almost stable too, is totally due to C-14 Aluminium activation is mostly due to tritium. The contribution of Al-26 (CI = 0.035) is evident at 200 y only. Copper activation is quite high. It is mainly due to Co-60 at short term (30 and 50 y) and to Ni-63 at long term (100 and 200 y). Manganese activation is all due to tritium Titanium activation is negligible
840
Massimo Zucchetti • • • • •
Silicon activation is very low, and all due to tritium Chromium activation is very low, and all due to tritium Tungsten activation at 30 y is due to Hf178m (68%), and T (30%) Boron activation is quite high, and all due to tritium Oxygen activation is all due to C-14
7. CONCLUSION Innovative solutions in the field of radioactive waste could be a clear advantage of fusion in view of its ultimate safety and public acceptance: recycling and/or clearance (i.e., declassification to non-radioactive materials) of all components, after a sufficient period of interim decay, should be the goals for an environmentally attractive fusion plant. As a further step towards the waste minimization, the features of fusion devices based on alternative advanced fuel cycles have been examined. In particular, the advanced D-3He fuel cycle offers several environmental advantages, such as the quite low presence of tritium, neutrons, and activated materials. Ignition of D-3He plasmas, however, is more difficult to achieve compared to D-T plasmas and 3He is not available on Earth. Candor is a study of a compact high-magnetic field tokamak, extrapolated from Ignitor technologies. Results obtained for the D-3He Candor experiment show that no environmental problems arise from such a device, from the radiological point of view, even with the presence of D-T plasma triggering: Candor does reach the zero-waste option as all wastes can be cleared within 100 y. Activation behaviour of materials after service in a D-He3 advanced fuel fusion experiment has been investigated. EUROFER, SiC/SiC and V-Cr-Ti materials have show the possibility of being declassified to non-radioactive material (clearance) after their irradiation in the reactor plasma chamber wall, if a sufficient interim cooling time is allotted. AISI 316L, on the contrary, suffers the presence of Ni and N (alloying elements) and Nb and Mo (impurities). Concerning pure elements, it is of particular interest the high activation of Copper, used in the reactors as conducting material for magnets: Cu activation products are Co-60 and Ni63: they could be eliminated from the material after service in the reactor. Activation of pure iron, on the contrary, is quite moderate, and this permits in principle to steels to aim at the clearance goal. The D-3He cycle offers safety advantages and could be the ultimate response to the environmental requirements for future nuclear power plants. Furthermore, the low neutron production helps overcome some of the engineering and material hurdles to fusion development. Studies for the development of advanced fuel cycles should be carried out in parallel with the current mainstream fusion pathway that primarily focuses on D-T tokamaks, such as ITER, test facilities, DEMO, and power plants. In conclusion, a correct choice of materials for DHe reactors permits to select those ones which can be declassified to non-radioactive material: this result is not obtainable in the case of DT reactors.
Advanced Fuel Fusion Reactors
841
REFERENCES [1] [2] [3] [4] [5] [6]
[7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17]
[18] [19]
Taylor, N.; Cheng, E.T; Petti, D.; Zucchetti, M. Fus. Technol. 2001, 39, 350-356. Cheng, E.T.; Rocco, P.; Zucchetti, M.; Seki, Y.; Tabara, T. Fus. Technol., 1998, 34, 721-727. Colombo U. (chair) “Fusion Programme Evaluation”, Commission of the European Communities, July 1990. Rocco, P.; Zucchetti, M. Journ. Nucl. Mater. 283-287 (2000) 1473-1478. IAEA Safety Guide, Report RS-G-1.7, September 2004. Maisonnier, D.; Cook, I.; Sardain P.; et al., “A Conceptual Study of Commercial Fusion Power Plants. Final Report of the European Fusion Power Plant Conceptual Study (PPCS),” Report EFDA-RP-RE-5.0 (2005). Zucchetti, M. Fusion Technol. 1991, 19, 852-858. Coppi, B. Phyisica Scripta 1982, T212, 590-594. Zucchetti, M. “Environmental Advantages of advanced fuel fusion reactors”, Proc. ICENES 98 Meeting, Tel Aviv (Israel), june 1998, pp.304-310. Sved, J.; Kulcinski, G. L.; Miley, G. H. British Interplanetary Soc. J. 2001, 48,1, 5561. Boxman G.J.; et al., “Low and high density operation of Alcator”, Proc. 7th European Conf. Plasma Physics, September 1-5, 1975, Vol. 2, pp.14-18. See FTU Web site: http://ftu.frascati.enea.it/ Coppi, B.; Airoldi, A.; et al., ”Critical Physics Issues for Ignition Experiments'', MIT RLE Report PTP 99/06 (1999) MIT, Cambridge, MA (USA). Coppi, B.; Nassi M.; Sugiyama, L.E. Physica Scripta, 1992, 45, 112-116. See Ignitor web site: http://www.frascati.enea.it/ignitor/ Coppi B.; et al., Fus. Technol. 1994, 25, 353-363. Coppi B.; et al., “Critical Physics Issues for Ignition Experiments: Ignitor”, MIT (RLE) Report PTP 99/06, Cambridge, MA, September 1999, Revised and extended May 2000. Sugiyama L.E., MIT Research Laboratory of Electronics Report, PTP-89/17 (1989). Forrest, R. EASY-2005.1, EURATOM/UKAEA Fusion Association, UKAEA FUS 513, January 2006.
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 843-892
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 29
SOLAR THERMAL POWER GENERATION ON MARS
*
Viorel Badescu† Candida Oancea Institute, Faculty of Mechanical Engineering, Polytechnic University of Bucharest, Bucharest, Romania.
ABSTRACT A "dynamic" solar power plant (which consists of a solar collector - thermal engine combination) is proposed as an alternative for the more usual photovoltaic cells. Upper bounds for the efficiency of solar thermal power plants operating in the Martian environment are first evaluated. A general thermodynamic approach, first presented here, clearly shows which of the three theories usually quoted in literature gives the exergy of thermal radiation. Recent works reporting accurate upper bounds for the efficiency of thermal radiation energy conversion into work are subsequently used in this chapter. The results refer to thermal engines powered by direct or diffuse solar radiation on Mars. Diffuse solar radiation is modeled as diluted or multiply scattered thermal radiation. A more elaborated model uses an endoreversible Carnot cycle to describe solar engine operation. Two strategies to collect solar radiation are analyzed: a solar horizontal collector and a solar collector whose tilt and orientation are continuously adjusted to keep the receiving surface perpendicular on Sun rays. Meteorological data measured at Viking Landers (VL) sites are used in computations. Results show that generally the influence of latitude on performance is important. In some situations the meteorological effects compensate the latitudinal effects and the output power is quite similar at both VL1 and VL2 sites. During a winter dust-storm day the maximum output power is much smaller than during autumn. High efficiency thermal engines should be used in combination with solar collectors kept perpendicular to the Sun’s rays. When a horizontal solar collector is considered, the dependence of the maximum output power on optimum solar efficiency *
A version of this chapter was also published in Nuclear Energy Research Progress edited by Veda B. Durelle published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research. † Candida Oancea Institute, Faculty of Mechanical Engineering, Polytechnic University of Bucharest, Spl. Independentei 313, Bucharest 79590, Romania. Phone: ++40.21.402.9428, Fax: ++40.21.410.4251, email:
[email protected] 844
Viorel Badescu seems to be quadratic at both VL1 and VL2 sites. When a collector perpendicular to the Sun’s rays is considered, this dependence is more complicated, but keeps the quadratic feature. No obvious difference exists between power plant performances in the two years of VL2 operation. A solar Stirling engine based on a horizontal selective flat-plate converter is analyzed in the last part of this chapter. All the computations were performed for a solar collection area similar in size with that of Mars Pathfinder’s Sojourner. The solar efficiency at noon is as high as 18 %. The power provided by the engine is as high as 16 W during autumn and winter. These results suggest that under the Martian environment the performance of properly designed solar Stirling engines is comparable with that of PV cell power systems.
1. INTRODUCTION Mars is a key objective of space exploration. Starting in the 1960s, different missions took place on the surface of the Red Planet with various scientific goals as the determination of the internal structure of the planet, the chemical and mineralogical analyses of Martian rocks and soils and the study of atmospheric circulation and weather patterns. Future missions include both robotic and manned expeditions. They require the availability of power generation units utilising chemical energy, radio-isotopes, solar radiation or nuclear fission as the primary energy source (Aldrich, 1992; Angelino and Invernizzi, 1993). The utilisation of systems, which use internally stored nuclear and chemical energy, implies in many cases limited life and excessive weight. Properly designed solar power systems can offer long life in space. During Mars spacecraft exploration the photovoltaic (PV) cells were almost exclusively envisaged as the main source of energy. They were proposed to power small rovers (Hibbs, 1989), long - endurance, remotely piloted aircraft capable of flight within the Martian environment (Collozza, 1990) and to ensure the life support for a 40 day manned Mars surface scientific expedition (McKissock et al., 1990). More recently, the Sojourner of the Pathfinder mission was powered by PV cells (see, e.g., Golombek et al., 1997). However, for many years researchers realized that in some specific situations solar dynamic power systems with thermal energy storage can provide significant savings in life cycle costs and launch mass when compared with conventional photovoltaic power systems with battery storage (Menetrey (1963), Secunde et al. (1989), Prisnjakov (1991), Prisnjakov et al. (1991)). A standard solar dynamic power system uses a mirror to concentrate solar radiation onto an absorber structure. By conduction through a solid material or circulation of a working fluid, the absorber heat is transferred to a thermal engine (i.e. a turbogenerator, Stirling engine, termocouple or thermionic-emitter). Alternators coupled to these thermal engines may generate electrical energy. Previous practice proved that three different cycles can be used for thermodynamic conversion of solar radiation: Brayton, Rankine and Stirling (Menetrey (1963), Prisnjakov (1991), Prisnjakov et al. (1991)). For continuos operation during dark periods the use of melted materials to store thermal energy is being considered. Among the advantages of dynamic power systems one could quote their ability to provide electrical energy and heat simultaneously, the fact that the power plant may be unified by using either solar or nuclear energy or their relative invulnerability to corpuscular particles
Solar Thermal Power Generation on Mars
845
and to electromagnetic radiation and the possibility of power control according to a given power consumption schedule (Prisnjakov, 1991). Earlier studies reported solar dynamic systems based on thermodynamic cycles and thermionic converters, respectively. Two systems of the former type were described in Menetrey (1963). One of them is a 3 kW solar dynamic system of 10 % overall efficiency consisting of a parabolic concentrator and a turbo-generator unit which uses mercury as working fluid in a Rankine cycle. The other one is a 15 kW system for space vehicle applications. Its working fluid is rubidium while the overall electrical efficiency was 21.7 %. The solar - thermionic system was designed to provide 135 Watts at Mars distance from the Sun with a system weighting about 14 kg. More recent Russian studies are using permanent gases (mainly mixtures of xenon and helium) as working fluid in Brayton cycles. They have output power of 3 to 5 kW, specific weights up to 40-45 kg/kW and overall efficiency of 31.2 % (Prisnjakov (1991), Prisnjakov et al. (1991), Prisnjakov et al. (1994)). Significant efforts to develop solar dynamic power systems (25 kW) for application to a low Earth orbit space station have been conducted by NASA Lewis Research Center (LeRC) as an integral part of the US space station development program (McLallian et al., 1988). The culmination of the LeRC programme demonstration program was a full system test in a thermal/vacuum tank of a Space Station Freedom type solar dynamic system at the 2 kWe size in February 1995. Related reports can be found in (Secunde et al. (1989), Weingartner et al. (1994)). A comparison between the various power systems designed for the Space Station Freedom shows the sun-to-user efficiency is 5.7 to 6.8 % for the PV system and 18.7 to 19.8 % for the dynamic system. If, in addition, the storage subsystem is taken into consideration, the solar dynamic system becomes even more attractive, mainly because the efficiency of the latent heat storage is higher compared to the Ni-Cd batteries of the pV system (for details see Weingartner et al. (1994)). A natural question arising about power systems to be used on Mars surface is: are properly designed dynamic systems comparable in performance with the PV – based power systems? Some of the above references seem to indicate an affirmative answer. However, they all refer to systems operating in the interplanetary space. A solar power system placed on Mars surface has to take into consideration one very important feature of the Martian weather. The period between the areocentric longitude Ls=161 - 326° and variants thereof have been referred to as the “dust storm season”. This period is nearly centered on perihelion, which is the time of maximum insolation on Mars (Martin and Zurek (1993), Hourdin et al. (1995)). In the northern hemisphere, the Martian atmosphere varies greatly from year to year during the dust storm season while at the other seasons, most phenomena are remarkably similar from year to year. Zurek et al. (1992) provide a comprehensive description of Martian meteorology. The dust storm periods are characterized by an almost vanishing direct solar radiation (see e.g. Badescu (1998a) and references therein). The main consequence is that isotropic diffuse solar radiation can not be concentrated and flat plate solar collectors have to be used in this case. The structure of this chapter is as follows. In the next section one gives details on the meteorological data measured at Viking Landers (VL) sites that were subsequently used in computations. Upper bounds for the efficiency of solar thermal power plants operating in the Martian environment are evaluated in section 3. A model of endoreversible Carnot solar power plant is presented in section 4 while section 5 refers to solar Stirling engines based on
846
Viorel Badescu
horizontal selective flat-plate converters. These models provide lower upper limits for the performance of actual thermal solar engines. Section 6 contains the conclusions.
2. METEOROLOGIC AND ACTINOMETRIC DATA ON MARS SURFACE The atmospheric (vertical) optical depth τ is an indicator of solar radiation attenuation in the Martian atmosphere. One can shortly define τ as follows. Let us denote by I top and I ground the direct solar irradiance at the top of the atmosphere and at ground level, respectively. Then, usage of τ allows writing the Beer's law as I top / I ground = e -τ / cos θ 0 where θ 0 is the zenith angle (i.e. the angle between the direction of solar direct radiation and the normal to a horizontal surface). During the Viking mission to Mars, cameras on the two Viking Landers used a Sun diode to measure the direct solar irradiance I ground . Since both I top and the atmospheric path are known when the Sun is viewed, application of the Beer’s law provides directly the vertical column visible dust opacity of the atmosphere above the Viking Lander sites (see Pollack et al. (1990), Badescu (2001) and references therein). Mars may be considered "clear" when the dust content in the atmosphere is low, but when local or global storms occurs the optical depth increases and the direct beam solar radiation decreases drastically. During the next sections we shall use as input data values of ambient pressure and temperature, wind speed and atmospheric optical depth measured at Viking Lander 1 (VL1) (22.3º N, 47.9º W) and Viking Lander 2 (VL2) (47.7º N, 225.7º W) sites. The data were taken from the Viking Lander Meteorology and Atmospheric Opacity Data Set Archive from the Planetary Data System database made publicly available on a compact disc (Lee, 1995). Three electronic files were used here, namely VL_MBIN.DAT and VL_TBIN.DAT (which contain values of atmospheric pressure and temperature and zonal and meridional wind speed, among others) and VL_OPAC.DAT (which contains atmospheric optical depth data). The file VL_MBIN.DAT (8325 records) contains binned and splined data obtained from the Viking Meteorology Instrument System (VMIS) through portions of the Viking Lander 1 mission. The file VL_TBIN.DAT (25750 records) contains binned and splined data obtained from the VMIS through most of the Viking Lander 2 mission and the early days of the Lander 1 mission. In both cases the numbering of the Martian solar days (sols) started at day 0 when each Lander touched down. Both files VL_MBIN.DAT and VL_TBIN.DAT contain mean values of meteorological parameters in each bin. The bin number starts with 0 at local midnight and increments by 1 each 1/25 of a sol. The file VL_OPAC.DAT (1044 records) stores measurements of atmospheric optical depth and associated errors estimates. Each record contains the optical depth value and its associated local solar time (in Earth hours) beginning at midnight. As the files VL_MBIN.DAT and VL_TBIN.DAT are more "dense" than the VL_OPAC.DAT file, a time interpolation procedure was used to obtain the values of the atmospheric pressure and temperature and wind velocity associated to a given record of atmospheric optical depth (for details see Badescu (1998b)). The atmospheric pressure values are missing for eleven records. In these cases the following procedure was adopted:
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847
i)
in case of the record VL2, year 1, areocentric longitude = 229.808 (autumn), sol = 200, hour = 11.41, we used the arithmetic mean of the pressure values corresponding to sol = 199, hour = 13.87 and sol = 201, hour = 11.42, respectively. ii) in case of the record VL2, year 2, areocentric longitude = 19.228 (spring), sol = 454, hour = 9.62, we used the arithmetic mean of the pressure values corresponding to sol = 453, hour = 17.33 and sol = 454, hour = 17.25, respectively. iii) in case of VL2, year 2, the first nine records during summer (areocentric longitudes between 93.363 and 100.510) we used the pressure value corresponding to the tenth record (areocentric longitude = 101.697, sol = 634, hour = 6.98).
A set of complete records was finally obtained. Each complete record associates to a given sol number and a local solar time value a set of four meteorological values, namely optical depth τ and atmospheric temperature T a , atmospheric pressure p a and wind speed
w . The number of complete records is rather small (Table 2.1). Table 2.1. The number of complete meteorological data records available at VL1 and VL2 sites
Year 1
Year 2
Spring Summer Autumn Winter Spring Summer Autumn Winter
Viking Lander 1 Sol Number of numbers complete Records 6 to 155 22 168 to 306 108 307 to 350 56 -
Viking Lander 2 Sol Number of numbers complete records 6 to 111 37 120 to 257 77 269 to 415 55 416 to 608 147 610 to 784 58 792 to 872 25 -
The optical depth values were used to evaluate the incoming fluxes of solar radiation. The resulting file of solar energy data was used as input during the simulation of solar heat engines operation. The three components of global radiation flux (namely direct, diffuse and ground reflected) were computed by using the procedure we previously proposed in Badescu (1998a). The incoming fluxes of solar radiation were evaluated for all the complete records of Table 2.1. A few basic facts about Martian meteorology are now summarized for reader convenience. The near-surface atmospheric temperature at Viking Landers latitude ranges from about -17°C during summer to –107° C in winter. Also, the daily average atmospheric pressure ranges between about 7 and 10 hPa, with a minimum near areocentric longitude Ls=150° and a maximum around Ls=300° (Badescu, 2001). The solar constant at the level of Mars orbit is 590 W/m2. The solar global irradiance on a horizontal surface at ground level could be as high as 400 W/m2 at the noon of a clear summer day and as low as 80 W/m2 at midday during a winter dust storm (Badescu, 1998a).
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3. UPPER LIMITS FOR SOLAR ENERGY CONVERSION EFFICIENCY INTO WORK The purpose of this section is to give information about the upper limits of the maximum efficiency of converting solar energy into mechanical work on the surface of Mars. This subject was already treated in a number of papers in case of solar energy conversion systems placed on Earth surface. Changing the conversion system on Mars does not require a different theoretical framework. However, the characteristics of Mars meteorology is expected to have considerable influence on the numerical results. The upper bounds for the performance presented in this section are obtained by using very idealized models. They have however the advantage of giving a perspective for the results obtained with the more realistic models developed in the next sections.
Exergy of Solar Radiation and Simple Upper Bounds for Conversion Efficiency The exergy of thermal radiation was studied in many papers, starting with the seminal work of Petela (1964). Controversial arguments were presented in literature (see e.g. Bejan (1988) for an early review). Recently, the discussion was re-opened in relation with the exergy of solar radiation (Petela (2003); Candau (2003)). Also, many authors studied the thermodynamics of converting radiation energy into mechanical work (for early reviews see Landsberg and Tonge (1979), Bejan (1988)). Three different theories were proposed by Jeter (1981), by Landsberg, Petela and Press (Petela (1961), Landsberg and Mallison (1976), Press (1976)) and by Spanner (1964), respectively. The three theories were unified by Bejan (1987) while a generalization of Bejan's approach was given in Badescu (1988a). Computing the maximum work obtained by converting the radiation energy, on one hand, and the radiation exergy, on the other one hand, are two different things as also noted in Petela (2003). Usually, in the first case there is a given configuration of the conversion system and one try to improve the design and operation of that configuration. However, the exergy represents the maximum quantity of work that can be produced in some given environment. Therefore, computing the exergy implies a high degree of idealization and is usually associated with the mental construction of a “reversible conversion system”. Two types of difficulties could occur in this last case. The first difficulty appears when treating systems producing power (i.e. work rate) and is finally related to the question whether a Carnot (reversible) engine is allowed to provide a non-null work rate. A second difficulty appears when treating particular irreversible processes whose reversible ideal limit is difficult to imagine as a non-null flux process. Absorption/emission of radiation is such a couple of processes as the associated entropy generation is strictly positive as far as the temperature of the absorber/emitter is different from the radiation source temperature (see e.g. Bejan (1988) p. 483-487). There are a few ways of approaching these difficulties and two are reminded here. The traditional approach assumes that (i) Carnot (reversible) engines are allowed to provide non-null power and (ii) any irreversible (non-null flux) process is allowed to have its own reversible ideal limit. A second, more recent approach assumes (i) but rejects (ii) above and chooses to include the irreversibilities in the treatment as they are, as far as they occur at
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849
the boundary of the conversion system. This is the so called endoreversible approach and its main scope is to minimize the effect of these existing irreversibilities (for example by the minimization of the entropy generation). Both approaches were used in the past when treating thermal radiation energy conversion into work. Now, we derive the exergy of thermal radiation from a simple, general, original thermodynamic argument. Let us consider a system Σ containing a radiation absorber coupled to a heat engine. The temperature outside the system (i.e. the ambient temperature) is T0 . Thermal radiation (carrying properties, like energy and entropy) enters and leaves the system. The absorber converts part of the energy of the incident radiation into heat that is transferred to the engine producing work. The other part of the incident radiation is reradiated by the absorber at its own temperature. Work and heat (transferred by other mechanisms than radiation, e.g. by conduction and/or convection) leave the system Σ . An appropriate temperature Ts and an energy flux ϕ s are associated to the radiation entering the system. The work rate leaving the system is W& . One defines the efficiency of converting the energy of the radiation entering the system into work as exergy flux contained in the radiation energy flux value of η .
η ≡ W& / ϕ s . One asks about the
ϕ s and about the maximum estimated
Various (irreversible) processes take place inside Σ during the conversion of radiation energy into work. One denotes by S& gen ,i (≥ 0) the entropy generation rate of process i. Of course, when the process i is treated (or, in other words, is modeled) as a reversible process the entropy generation vanishes (i.e. S& gen ,i = 0 ). The Gouy-Stodola theorem applied to the system Σ gives (Bejan (1988) p. 113-114)
W& = W& rev − T0 ∑ S& gen,i
(3.1)
i
where W& rev is the work rate leaving the system in case all processes inside Σ are treated as reversible. Use of Eq (3.1) and the efficiency definition yields:
η = η rev − T0
∑ S& gen ,i i
(3.2)
ϕs
where obviously
η rev ≡
W& rev
ϕs
= η Carnot = 1 −
T0 Ts
(3.3)
When all the irreversibilities inside Σ are taken into account, from Eq (3.2) one could compute the real efficiency η of the thermal collector-heat engine combination. When part of
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Viorel Badescu
the processes inside Σ are treated as reversible (i.e. their entropy generation rate S& gen ,i is assumed to vanish), Eq (3.2) allows to obtain upper bounds for the real efficiency
η . When
all processes inside Σ are treated as reversible processes from Eqs (3.1) and (3.3) one finds the “highest” upper bound for the real efficiency η . Thermal radiation exergy was evaluated in the past by both traditional and endoreversible approaches. This is well summarized in Figure 7 of Petela (2003) and briefly described below. (a) When all processes are treated as reversible, there is no entropy generation inside Σ and Eqs (3.2) and (3.3) yield:
ηJ = 1 −
T0 >η Ts
(3.4)
This is the efficiency proposed by Jeter (1981) and applies to Figure 7(1) of Petela (2003). Note that the above assumption implies using a reversible (i.e. Carnot) heat engine. Treating the absortion/emission in the limit case of a reversible process means of course that the absorber and the radiation source have strictly the same temperature. Then, the work rate
W& that leaves that system is given by: ⎛ T ⎞ W& = W& rev = ϕ s ⎜⎜1 − 0 ⎟⎟ ⎝ Ts ⎠
(3.5)
and this is the exergy flux expression proposed by Jeter (1981). (b) When one irreversibility, namely “filling” the system Σ with incident radiation, is taken into account, from Eq (3.2) one obtains (Bejan (1987), Badescu (1999), see also Section 4 of Petela (2003))
ηS = 1 −
4 T0 3 Ts
(3.6)
This is the efficiency proposed by Spanner (1964) and keeping its value positive requires some constraints on temperatures (see Petela, 2003). (c) When two irreversibilities are taken into account (namely “filling” and “emptying” the system Σ with/of radiation) from Eq (3.2) one finds (Bejan (1987), Badescu (1999), see also Section 4 of Petela (2003)):
η LPP
4 T0 1 ⎛ T0 = 1− + ⎜ 3 Ts 3 ⎜⎝ Ts
4
⎞ ⎟⎟ > η ⎠
(3.7)
This is the Landsberg-Petela-Press efficiency and is related to Figure 7(3) of Petela (2003). The same result applies in case the absorber (or the cascade of absorbers, as a limit
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851
case adopted in Candau (2003)) operates at a lower temperature than the radiation source. This treats the absorption/emission as an irreversible process. If the remaining processes are treated as reversible, one shall find the “exergy” expression first proposed by Petela (1964), and later on by Badescu (1988b) (his equation (28)) and Candau (2003) (his equation (9)), among others. The procedure above explains why Bejan (1987) concluded that the efficiencies η J , η S
η LPP do not contradict each other. All these relationships are correct, as they are rigorously derived upper bounds for the real efficiency η (under some temperature limitations however in case of η S ). All of them are equally elegant, being expressed in a
and
Carnot-like style, namely in terms of just the hot and cold heat reservoir temperatures. However: i)
One of the three efficiencies (i.e.
η J ) is obtained in case all processes inside system
Σ are treated as reversible. It predicts a performance similar to that of a Carnot engine and therefore, according to the traditional approach, it gives the exergy flux of thermal radiation (i.e. Eq (3.5)). ii) One of the three efficiencies (i.e. η LPP ) is more accurate, because it considers a larger number of irreversibilities taken place inside Σ and, consequently, it estimates a lower upper limit for the maximum value of η .
Let us apply the above results in case of solar radiation on Mars. The temperature of solar direct radiation is Ts = 5760 K while the average temperature of Mars surface is T0 = 248 K . Then, the efficiency predicted by Jeter efficiency Eq (3.4) is 0.9569 and for a solar direct irradiance at ground level
ϕ s = 400 W / m 2 the exergy flux given by Eq (3.5) is
382.76 W/m2. Using Spanner efficiency Eq (3.6) and Eq (3.4) yield the efficiency 0.9426 and the work flux 377.04 W/m2, respectively. Finally, using Landsberg-Petela-Press efficiency Eq (3.7) and Eq (3.4) yield again the efficiency 0.9426 and the work flux 377.04 W/m2, respectively. Apart from the theoretical divergences these results are very close each other.
Accurate Upper Bounds for Solar Energy Conversion Efficiency All theories in the previous subsection predict efficiencies of converting radiation energy into work too high to be of practical interest. Much more accurate rigorous upper bounds of η were reported in recent years (Badescu, 1998c, 1998d). They are consequences of taking account of additional processes and irreversibilities than those used to derive
η LPP . Some of
these new results are listed below and applied to the special case of solar energy conversion on Mars surface. (i) In case of a smaller than hemispherical blackbody radiation source and a blackbody receiver coupled to a reversible engine the upper bound of η is (Badescu, 1998c):
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Viorel Badescu
4⎛ T ⎞ 1⎛ T ⎞ η i = 1 − ⎜⎜ f 0 ⎟⎟ + ⎜⎜ f 0 ⎟⎟ 3 ⎝ Ts ⎠ 3 ⎝ Ts ⎠
4
>η
(3.8)
where the geometric factor
⎛Ω⎞ f ≡⎜ ⎟ ⎝π ⎠
−1 / 4
Ω⎞ ⎛ ⎜1 − ⎟ ⎝ 4π ⎠
−1 / 4
(3.9)
is a function of the solid angle Ω subtended by the radiation source. In case of a spherical source of radiation (e.g. the Sun) the following simple relation applies:
f = sin −1 / 2 δ
(3.10)
where δ is the half-angle of the cone subtended by the source. Of course, when a hemispherical source of radiation is considered, to
δ = π / 2 and η i given by Eq (3.8) reduces
η LPP given by Eq (3.7). However, generally η i < η LPP . One can see that η i depends on
just two temperatures (namely the temperatures of the heat reservoirs) as any Carnot-like efficiency. But it also takes account of the geometry of the radiation source and this additional information input increases its accuracy. Let us use Eqs (3.8)-(3.10) to solar energy conversion on Mars. The case of direct solar radiation is considered. Then, δ is the half-angle of the cone subtended by the Sun when viewed from Mars. The mean distance Sun to Mars is d Sun − Mars = 227.94 ⋅10 km while 6
Sun radius is Rs = 696 ⋅10 km . Consequently, 3
δ = sin −1 (Rs / d Sun−Mars ) = 0.003053 .
Equation (3.10) yields f = 18.096 . Use of Eq (3.8) gives the upper bound
ηi = 0.08393 .
This is obviously a more accurate upper bound than those predicted in section 2.1. (ii) In case of smaller than hemispherical blackbody radiation source and a blackbody receiver coupled to a Chambadal-Novikov-Curzon-Ahlborn (CNCA) engine the upper bound of η is (Badescu, 1998c)
4⎛ T ⎞ η ii = 1 − ⎜⎜ f 0 ⎟⎟ 3 ⎝ Ts ⎠
1/ 2
1⎛ T ⎞ + ⎜⎜ f 0 ⎟⎟ 3 ⎝ Ts ⎠
2
>η
This is of course a more accurate estimate for
(3.11)
η that η i is, because part of the entropy
generation related to heat engine operation is taken into account (one reminds that the CNCA engine is an endoreversible engine). As an application, using Eq (3.11) in case of solar direct radiation on Mars yields η ii = 0.02542 which is lower than the value derived previously for
η i , as expected.
Solar Thermal Power Generation on Mars Note that a formula corresponding to
853
η LPP , in case the system Σ contains a CNCA
engine, can be obtained from Eq (3.11) by making f = 1 . One finds
4 ⎛T η 'ii ≡ 1 − ⎜⎜ 0 3 ⎝ Ts
⎞ ⎟⎟ ⎠
1/ 2
1⎛T + ⎜⎜ 0 3 ⎝ Ts
⎞ ⎟⎟ ⎠
2
(3.12)
Equation (3.12) is a more accurate estimate for estimate than
η than η LPP is, but a less accurate
η ii is. Using Eq (3.12) in case of solar direct radiation on Mars yields
η 'ii = 0.72395 . This is a rather high upper bound for the real efficiency and this loss in accuracy is the cost of using a simpler upper limit formula. (iii) Repeating the procedure from Bejan (1987) under the framework of endoreversible thermodynamics one finds relationships generalizing Jeter, Spanner and Landsberg-PetelaPress efficiencies, respectively (Badescu, 1999). For example, the relation generalizing the last efficiency is: n
4 ⎛ T0 ⎞ n ⎛ T0 ⎞ ⎜⎜ ⎟⎟ + ⎜ ⎟ ηiii ≡ 1 − 4 − n ⎝ Ts ⎠ 4 − n ⎜⎝ Ts ⎟⎠
4
(3.13)
where n is a parameter related to the type of endoreversible thermal engine. In case of n = 1 (i.e. a Carnot engine) one finds of course from Eq (3.13) the efficiency
η LPP . Let us consider
a CNCA engine ( n = 1 / 2 ) as part of a power system converting the energy of direct solar energy on Mars. Then Eq (3.13) yields the upper limit
ηiii = 0.76286 . This rather high
upper bound is comparable in size to η 'ii . (iv). The case of gray thermal radiation is of special interest, as it is sometimes used as an approximation for diffuse solar radiation. Note that gray radiation is a particular case of diluted radiation. A general theory was first developed by Landsberg and co-workers (see for instance the review paper (Landsberg and Tonge, 1979)). However, important results were derived more recently and they will be summarized now. An accurate upper bound for the conversion efficiency of solar diluted radiation into work is given by (Badescu, 1990)
4⎛ T ⎞ 1⎛ T ⎞ η d ≡ 1 − ⎜⎜ f d 0 ⎟⎟ + ⎜⎜ f d 0 ⎟⎟ 3 ⎝ Ts ⎠ 3 ⎝ Ts ⎠
4
(3.14)
Here the dimensionless factor f d can be obtained from Eqs (10) and (14) of (Badescu, 1990):
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Viorel Badescu
⎛Ω ⎞ f d ≡ χ (ε d )⎜ d ⎟ ⎝ π ⎠
−1 / 4
⎛ Ωd ⎞ ⎜1 − ⎟ ⎝ 4π ⎠
−1 / 4
(3.15)
where Ω d is the solid angle subtended by the source of diluted radiation source while
χ (ε d ) is a function of the radiation dilution factor ε d . This function was calculated in
Landsberg and Tonge (1979). It is such that
χ (1) = 1 and can be approximated for small ε d
by:
χ (ε d ) = 0.9652 − 0.2777 ln ε d + 0.0511ε d
(3.16)
The above general formulation yields elegant results in the particular case of solar scattered radiation. The upper bound for the efficiency of converting into work the energy of multiply scattered solar radiation was derived in Badescu (1991) and is given by
ηd ,i
T ⎞ 1⎛ 4⎛ T ⎞ ≡ 1 − ⎜⎜ f d ,i 0 ⎟⎟ + ⎜⎜ f d ,i 0 ⎟⎟ Ts ⎠ 3 ⎝ 3⎝ Ts ⎠
4
(3.17)
where the factor f d ,i this time depends on the number i of scatterings (i=1,2,3,4). It is computed by
f d ,i
⎛Ω ⎞ ≡ ⎜⎜ d ,i ⎟⎟ ⎝ π ⎠
−1 / 4
⎛ Ω d ,i ⎞ ⎜⎜1 − ⎟ 4π ⎟⎠ ⎝
−1 / 4
∏ χ (ε d ,i ) i
j =1
(i = 1,2,3,4)
(3.18)
In case the scattered radiation is not subsequently concentrated, the following relations apply for the dilution factors and solid angles of i-scattered solar radiation
ε d ,1 =
Ω d ,i
Ωs
π
ε d ,i =
Ω s ⎡ i−1 4 ⎤ ∏ χ (ε j )⎥ ⎢ π ⎣ j =1 ⎦
1 ⎧ ⎫ ⎪ ⎡ Ωs i 4 ⎤2 ⎪ = 2π ⎨1 − ⎢1 − ∏ χ (ε d ,i )⎥ ⎬ π j =1 ⎦ ⎪ ⎪⎩ ⎣ ⎭
(i = 2,3,4)
(3.19)
(i = 1,2,3,4)
(3.20)
where Ω s is the solid angle subtended by the Sun. The half-angle
δ d ,i of the cone subtended
by the source of i-scattered radiation can be easily computed from:
Ω d ,i = 2π (1 − cos δ d ,i )
(3.21)
Solar Thermal Power Generation on Mars
855
The effective temperature Td ,i of i-scattered solar radiation is given by:
Td ,i =
Ts
(3.22)
∏ χ (ε d ,i ) i
j =1
Table 3.1 shows results obtained in case of i-scattered solar radiation on Mars. One can see that after a single scattering (i.e. i=1) solar radiation is still strongly anisotropic (compare δ d ,1 = 3.061° with the half-angle δ s = 0.1749° of the cone subtended by the Sun). After four scatterings solar radiation is isotropic and an observer at the ground would see a uniformly brilliant sky. The effective temperature of the scattered radiation decreases by increasing the number of scatterings, as expected. However, the upper bound efficiency η d, i predicted by Eq (3.10) yields the same value, whatever the number of scatterings. This is a consequence of keeping the energy flux constant during the scattering process. Table 3.1. Upper bounds for the conversion efficiency of i-scattered solar radiation into work on Mars Number i of scatterings 1
Ω d ,i
0.000009 32 0.002851 00 0.128900 00 0.726500 00
2 3 4
ε d ,i
ε d ,i
Td ,i
η d, i
C max,i
η d , conc, i
(deg) 3.06
(K) 1377.0
0.084
350.70
0.760
21.04
531.2
0.084
7.76
0.393
58.47
344.8
0.084
1.38
0.130
90.00
316.0
0.084
1.00
0.084
0.00897 0.41880 2.99700 6.28300
Ω d ,i
and
radiation, respectively.
Td ,i
- dilution factor.
δ d ,i
δ d ,i
- solid angle and half-angle of the cone subtending the source of
- effective temperature. η d, i - upper bound efficiency.
C max,i
-
maximum concentration ratio. η d , conc, i - upper bound efficiency for concentrated i-scattered radiation. Sun temperature
Ts = 5760 K ; average temperature on Mars surface T0 = 248 K .
For small i-values scattered solar radiation is generally anisotropic. Consequently, it can be concentrated. The maximum concentration ratio C max, i is given by:
C max,i
⎡Ω = ⎢ d ,i ⎣ π
⎛ Ω d ,i ⎞⎤ ⎜⎜1 − ⎟⎥ 4π ⎟⎠⎦ ⎝
−1
(3.23)
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Viorel Badescu
The upper bound efficiency η d , conc, i for fully concentrated scattered radiation is given again by Eq (3.17) with f d , i replaced by f ' d , i given by:
f 'd ,i ≡ ∏ χ (ε d ,i ) i
j =1
(i = 1,2,3,4)
(3.24)
The upper bound efficiency η d , conc, i lies between 0.760 and 0.084 for single and four scatterings, respectively (Table 3.1). Generally, the effective temperature of scattered radiation is lower, and the upper bound efficiency are higher, on Mars than on Earth (compare present Table 3.1 with Table 1 of Badescu (1991)). This is mainly caused by the lower ambient temperature on Mars. (v) The upper bounds at (i) to (iii) above apply to any source of blackbody undiluted or diluted radiation. Even more accurate (but also more complex) upper bounds of η were derived in case of solar energy applications (Badescu, 1998d, 2000). These upper bounds are again Carnot-like efficiencies in the sense that they do not involve the absorber temperature but are expressed just in terms of the two heat reservoir temperatures. However, they take into account a large number of details concerning the conversion process as for example, the dilution factors of solar and ambient radiation, the polarization degree of solar and absorber emitted radiation and the thermal and optical properties of the selective absorber (convective and conductive heat loss coefficients, concentration ratio, effective transmittance-absorptance product and emittances). These details increase of course the accuracy of the efficiency formula. As an example we shall use the accurate upper bound efficiency Eq (36) of Badescu (1998d). For the purposes of this chapter we shall simplify it to take account just on the selective properties of the absorber (i.e. its absorptance a and emittance e ). Then, the upper bound efficiency is given by:
⎡ 4 ⎛ T ⎞ 1 ⎛ T ⎞4 ⎤ η v = a ⎢1 − ⎜⎜ f 0 ⎟⎟ + ⎜⎜ f 0 ⎟⎟ ⎥ ⎢⎣ 3 ⎝ Ts ⎠ 3 ⎝ Ts ⎠ ⎥⎦
(3.25)
where 1/ 4
⎛e⎞ f =⎜ ⎟ ⎝a⎠
sin −1 / 2 δ
(3.26)
For an usual selective flat-plate solar collector with a = 0.9 and e = 0.1 , Eq (3.25) yields
η v = 0.3724 which is considerably higher than the upper bound efficiency
η i = 0.08393 we previously found in case of black-body (non-selective) solar collectors. Finally note that the results presented in (i),(ii) and (v) correspond to solar direct radiation at normal incidence (i.e. Sun zenith angle θ 0 = 0 ). In the general case the geometric factors in Eqs (3.9), (3.10) and (3.26) should be multiplied by cos
−1 / 4
θ0
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857
(Landsberg and Badescu, 2000). For oblique radiation incidence ( θ 0 > 0 ) this procedure will yield lower estimates for the upper bound efficiency.
4. ENDOREVERSIBLE CARNOT SOLAR POWER PLANTS In section 3 we presented simple accurate upper bound formulas for the efficiency of solar power plants operating on Mars. Much more involved models are necessary to further increase the accuracy of results. In this section a solar power plant model based on the Carnot endoreversible cycle is presented. This approach keeps the advantage of generality but also takes into account the irreversibilities associated to the heat transfer at the hot and cold components of the plant.
Solar Power Plant Model Generally, a solar power plant consists of a solar collector, a thermal engine and a heat storage system. A solar collector mainly consists in mirror, absorber (receiver), transparent cover(s) and thermal insulation. The mirror is missing in case of flat - plate collectors while for some concentration systems the receiver is not protected by transparent cover(s). The solar power plant analysed in this section is designed to operate during the whole Martian year. Consequently, it consists of a flat-plate selective solar collector coupled to a thermal engine. No heat storage system is considered in this approach.
Figure 4.1. Solar collector. (i) longitudinal section; (ii) transversal section; (iii) lateral view. absorber plate; 2 - carbon dioxide layer; 3 - transparent cover; 4 - bottom thermal insulation.
1-
Solar Collector Model A selective flat - plate solar collector is shown in Figure 4.1. Its main components are: the absorber plate (1) with pipes for the working fluid and a transparent cover (3) of thickness a. The gap between (1) and (3) (thickness s ) is filled with carbon dioxide at the Martian
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Viorel Badescu
atmospheric pressure (carbon dioxide represents 95 % of the Martian atmosphere). The bottom thermal insulation (4) has a thickness b . The collector tilt angle is β . One denotes by T C and T a the absorber plate and ambient temperatures, respectively. Other temperatures related to collector operation are defined in Table 4.1. Table 4.1. Various temperatures related to solar collector operation
TC
absorber plate temperature
Tsi
temperature of lower surface of transparent cover
Tss
temperature of higher surface of transparent cover
Ta
atmosphere temperature
T C,si = (T C + T si ) / 2
T s ,ave = (T si + T ss ) / 2
T ss,a = (T ss + T a ) / 2
T iz = (T C + T a ) / 2
average fluid temperature between absorber plate and lower surface of transparent cover ( see Figure 4.2) average transparent cover temperature average temperature of the atmosphere boundary layer near the collector transparent cover average bottom insulation temperature
Figure 4.2. Solar collector thermal resistances.
Ta
- ambient temperature;
temperature; T si - temperature of lower surface of transparent cover; surface of transparent cover.
T ss
TC
- absorber plate
- temperature of upper
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Direct beam (b), diffuse (d) and ground reflected (r) fluxes of solar energy are incident on the collector. Their magnitude depends upon collector's tilt and orientation. Generally, the incident and absorbed solar energy density fluxes ( ϕ inc and ϕ abs , respectively) are given by
ϕ inc = Gb + G d + G r
(4.1)
ϕ abs = (τα )b Gb + (τα )d (G d + G r )
(4.2)
Here G 's denote solar irradiances at collector level while
(τα ) 's
are effective
transmittance - absorptance products. Table 4.2. Thermal resistances associated to solar collector operation (see Figures 4.1 and 4.2) Thermal Resistance R1 R2
Process Convection and conduction between absorber plate (1) and transparent cover (3) Radiation between absorber plate (1) and the lower surface of the transparent cover (3) Conduction through transparent cover (3) Radiation between the higher transparent cover surface (3) and Martian atmosphere Convection between the higher transparent cover surface (3) and Martian atmosphere Conduction through the bottom thermal insulation(4)
R3 R4 R5 R6
The collector heat losses will be studied by using the thermal resistance method (Eaton and Blum, 1975) (see Figure 4.2 and Table 4.2). Then, the flux of heat losses from the collector towards the ambient is given by:
qtot = U L (T C - T a )= (T C - T a )/ Rtot
(4.3)
where U L is the overall heat losses coefficient while Rtot is the total thermal resistance. U L is given by (see Figure 4.2):
UL =
1 Rtot
=
1 R1-5
+
1 R6
(4.4)
where R1-5 is computed from:
R1-5 =
R1 R 2 + + R 4 R 5 R3 R4 + R5 R1 + R 2
(4.5)
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Details concerning the evaluation of thermal resistances follow. The thermal resistance R1 is computed from
R1 =
s
(4.6)
< λ CO 2 >C,si N u C,si
where < λ CO2 >C,si is thermal conductivity of carbon dioxide and N u C,si is Nusselt number, both of them evaluated at the average fluid temperature T C,si . To compute N u C,si , a number of criterial relationships developed for solar collectors were used (Table 4.3(a)) (Eaton and Blum, 1975). For cases not covered by Table 4.3(a) we used the general relationships from (Stefanescu et al., 1982), (Table 4.3(b)). Prandtl and Grashoff numbers in Table 4.3 were computed with:
Pr =
< c p,CO 2 >C,si < η CO 2 >C,si < λ CO 2 >C,si
g M pCO 2 s3 (T C - T si ) 2
; Gr =
< η CO 2 >C,si RCO 2 T C,si
(4.7)
where g M is gravitational acceleration on Mars while pCO2 and RCO2 are the pressure and gas constant for the carbon dioxide between absorber plate and transparent cover. In Eq. (4.7) the specific heat at constant pressure ( < c p,CO2 >C,si ), the dynamic viscosity ( < η CO2 >C,si ) and the thermal conductivity ( < λ CO2 >C,si ) of carbon dioxide were interpolated at the average temperature T C,si . In computations the thermal properties of carbon dioxide from (Pop et al., 1987) were used. The thermal resistance R 2 is evaluated with:
R2 =
1 / ε1 + 1 / ε 2 − 1 2σ TC2 + Tsi2 TCsi
(
)
(4.8)
ε 1 and ε 2 are the emittance of absorber plate and lower surface of transparent cover, respectively (Duffie and Beckman, 1974) and σ is Stefan-Boltzmann constant.
where
The thermal resistance R 3 is given by:
R3 = a/ λ s
(4.9)
The temperature dependence of transparent cover's thermal conductivity ( λ s ) was described by using an interpolation parabolic function whose coefficients were obtained by using experimental data. The average transparent cover temperature T s,ave was used in computations.
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Table 4.3. (a) Relationships for convection heat transfer between absorber plate and transparent cover (Eaton and Blum, 1975)
β ⎞ β ⎛ N u C,si = ⎜ 1 N uV ⎟N uH + 2π ⎝ 2π ⎠ for 2 ⋅ 10 3 ≤ Gr < 4 ⋅ 10 5 N u H = 0.195 ⋅ Gr 0.25
(a)
(b)
N u H = 0.068 ⋅ Gr 0.33
for Gr ≥ 4 ⋅ 10 5
N uV = 0.180 Gr 0.25 (s / L )0.11
for 1 ⋅ 10 4 ≤ Gr < 2 ⋅ 10 5
N uV = 0.065 Gr 0.33 (s / L )0.11 N uC,si = 1
for 2 ⋅ 10 5 ≤ Gr < 11 ⋅ 106
N u C,si = 0.105 ⋅ (Gr ⋅ Pr )0.30
for 1 ⋅ 10 3 < Gr ⋅ Pr ≤ 1 ⋅ 106
N u C,si = 0.400 ⋅ (Gr ⋅ Pr )0.20
for 1 ⋅ 10 4 ≤ Gr < 2 ⋅ 10 5
N u C,si = 0.180 ⋅ (Gr ⋅ Pr
)0.25
H and V denote a horizontal and vertical solar collector;
for Gr ⋅ Pr ≤ 1 ⋅ 10 3
for Gr ⋅ Pr > 1 ⋅ 1010
β [rad] and L [m] are tilt angle and collector
length, respectively. (b) General relationships for convection heat transfer between two plane parallel surfaces (Stefanescu et al., 1982, p. 160)
The thermal resistance R 4 was evaluated with:
R4 =
1/ ε 2 2σ (T + T 2a )T ss,a 2 ss
(4.10)
where T ss,a is the average temperature of the atmosphere boundary layer near the collector transparent cover. Because of the wind, the heat transfer between the transparent cover and Martian atmosphere is mainly by forced convection. Thus, the thermal resistance R5 was computed from:
R5 =
L < λ CO2 >ss,a N u ss,a
(4.11)
where L is collector's length on wind direction and < λ CO2 >ss,a is carbon dioxide thermal conductivity at temperature T ss,a . In Eq (4.11) N u ss,a depends on the critical length X T which separates the laminar and turbulent wind flows over the collector. The relationships of Table 4.4 were used. The Reynolds and Prandtl numbers were evaluated with:
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Viorel Badescu
Re =
pCO 2 W L < η CO 2 >ss,a RCO 2 T ss,a
,
Pr =
< c p,CO 2 >ss,a < η CO 2 >ss,a < λ CO 2 >ss,a
(4.12)
where W is wind speed and the thermal properties of the atmosphere ( < η CO2 >ss,a ,
< c p,CO2 >ss,a and < λ CO2 >ss,a ) were interpolated at the average temperature T ss,a . The thermal resistance R6 was evaluated with: R6 = b/ λ iz where
(4.13)
λ iz is bottom insulation thermal conductivity, computed at the average temperature
T iz . Table 4.4. Relationships for forced convection heat transfer between transparent cover and atmosphere (Stefanescu et al., 1982, p. 126)
X T = 5 ⋅ 10
5
< η CO 2 >ss,a RCO 2 T ss,a pCO 2 W
N u ss,a = 0.335 ⋅ Re0.50 ⋅ Pr 0.50
for
L ≤ X T (laminar flow)
N u ss,a = 0.036 ⋅ Re0.80 ⋅ Pr 0.75
for
L > X T (turbulent flow)
Figure 4.3. Temperature - entropy diagram for an endoreversible Carnot cycle (for notations see text).
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Endoreversible Carnot engine Model A variety of working fluids were proposed to be used in space solar engines. They include mercury, potassium and rubidium in the early studies (Menetrey, 1963) or organic fluids and mixtures of noble gases more recently (Angelino and Invernizzi (1993), Prisnjakov et al. (1991)). The later seem to be more appropriate in case of Martian solar power plants. The largest and smallest working fluid temperatures are denoted T ′ and T" , respectively (Figure 4.3). Generally, T C > T ′ and T" > T a . Hence, both
X ≡ T C - T ′ and Y ≡ T" - T a are positive quantities. The flux of solar energy
(4.14)
φ abs absorbed by the collector is
φ abs = ϕ abs AC
(4.15)
where AC is collector surface area. Part of this flux is transferred to the working fluid ( Q& C ) while the other part constitutes the flux of thermal losses to the ambient ( Q& L ). Then, the solar collector steady-state energy balance is:
φ abs - Q& C - Q& L = 0
(4.16)
The heat fluxes Q& C and Q& L can be written as:
Q& C = hC AC X and Q& L = U L AC (T C - T a
)
(4.17)
where hC and U L are appropriately defined overall heat transfer coefficients between the solar collector and the working fluid and ambient, respectively. The Carnot engine partially converts the flux Q& C into power. Thus:
Q& C = W& + Q& a
(4.18)
where W& is the output power and Q& a is the thermal energy flux finally reaching the surroundings. There is no further increase of entropy during work production. Consequently
Q& C Q& a + =0 T ′ T '' The heat flux Q& a can be written as
(4.19)
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Viorel Badescu
Q& a = ha Aa Y
(4.20)
where Aa and ha are appropriately defined engine radiator heat transfer area and overall heat transfer coefficient between working fluid and ambient, respectively.
Performance Indicators Four performance indicators may be considered in relation to Martian solar plant operation (Badescu et al., 1999, 2000a, 2000b). First, there is the Carnot engine efficiency defined as:
η
T" T′
≡1-
engine
(4.21)
Second, there is the output power W& , evaluated from:
W& = hC AC X - ha Aa Y
(4.22)
Here we used the Eqs (4.17), (4.18) and (4.20). Third, there is the system efficiency, defined as:
η
system
≡
W&
ϕ abs A C
(4.23)
Finally, the solar (or sun-to-user) efficiency is defined as:
η
solar ≡
W&
φ
abs
AC
(4.24)
Information about some of these indicators is reported in the following.
Optimisation The output power W& will be maximised now. The weight of space power plants should be kept at minimum. Following previous studies (see e.g. Badescu (1994)) we express the mass of the total heat transfer area (i.e. the mass M C of the solar collector and the mass M a of the engine radiator) as a k fraction from the total mass M tot of the space system:
M C + M a = k M tot
(4.25)
One denotes d C and d a the superficial mass density of collector and radiator, respectively. One can simply write:
Solar Thermal Power Generation on Mars
M C = d C AC , M a = d a Aa
865 (4.26)
One can use d C = d a as a reasonable assumption. By using eqs (4.25) and (4.26) one derives the following constraint to be fulfilled:
AC + Aa = A ≡ k
M tot da
(4.27)
Other constraints (say F 1 and F 2 ) are the Eqs (4.16) and (4.19). By using (4.14), (4.17) and (4.20) they become:
F1 ≡
hC AC X - ha ( A - AC ) = 0 T a +Y TC - X
F 2 ≡ ϕ abs - U L ( T C - T a ) - hC X = 0
(4.28)
(4.29)
The power W& is considered here as a function of T C , X , Y and AC . The Lagrange function L associated to W& is:
L ≡ W& + λ 1 F 1 + λ 2 F 2 where
(4.30)
λ 1 and λ 2 are multipliers. The maximum output power is obtained by solving the six
equations shown in Table 4.5. Table 4.5. Equations to be solved for power maximisation (for details see text)
1.
X ∂L = - λ 1 hC AC 2 - λ 2 U L = 0 ∂TC ( TC - X )
2.
∂L h = hC AC + λ 1 C AC T C2 - λ 2 hC = 0 ∂X ( TC - X )
3.
∂L = - ha ∂Y
4.
5. 6.
( A - AC ) - λ 1 ha ( A - AC )2T a = 0 ( T a +Y )
Y ⎞ X ∂L ⎛ + ha ⎟⎟ = 0 = hC X + ha Y + λ 1 ⎜⎜ hC ∂ AC ⎝ TC - X Ta -Y ⎠ ∂ L hC AC X ha ( A - AC ) Y =0 = ∂ λ1 T C - X T a +Y ∂L = ϕ abs - U L ( T C - T a ) - hC X = 0 ∂ λ2
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Viorel Badescu Table 4.6 shows the solution that applies for K > 1 . There, the dimensionless parameters
K and f are defined as: K=
ha hC
⎛ ϕ h ⎞ ⎜⎜1 + C ⎟⎟ , f = abs U L Ta ⎝ UL ⎠
(4.31)
Table 4.6 and Eq (4.22) allow writing the maximum power as:
h A 2 W& max = a Yopt Ta
(4.32)
The optimum solar efficiency
η
solar, opt
can be derived by using Eqs (4.24), (4.32) and
Table 4.6. Table 4.6. Optimum parameters for maximum output power (for details see text)
1.
⎛ 1 + f - ( 1 + f ) 1/ ⎜ = 1 + f T C, opt ⎜ 1/ 2 ( 1 + K 1/ 2 K ⎝
2.
X opt =
3.
Y opt =
4.
AC, opt =
( 1 + f ) - ( 1 + f ) 1/ 2 K
1/ 2
( 1+ K
( 1 + f ) 1/2 - 1 1+ K
1/2
1/ 2
)
2
)
ha ⎞⎟ Ta U L ⎟⎠
ha Ta hC
Ta
1/2
K 1+ K
1/2
A
Results and Discussions One of the goals of this chapter is to perform a rough comparison between the performance of PV cell power systems and dynamic solar power plants. In case of PV cell systems we had in mind the Pathfinder's Sojourner. Sojourner is a small (11.5 kg), six - wheel robotic vehicle built at Jet Propulsion Laboratories. Sojourner was landed on Mars aboard the Pathfinder spacecraft on July 4, 1997. In the same sol she began to traverse the Martian terrain, perform science and technology experiments, and transmit images and data back to the Lander space craft. Sojourner's equipment (computers, motors, radio modem) was mainly powered by a lightweight 0.34 kg solar array of receiving surface area 0.22 m2. The PV cell system was designed to provide Sojourner with around 16 W of electric power at noon on Mars. The landing place was in Ares Vallis at 19.17º N and 33.21º W on the U.S. Geological Survey (USGS) cartographic network (Golombek et al., 1997). Pathfinder landed in late northern summer (areocentric longitude L s = 143° ) and operated for 83 sols.
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To allow comparison with Sojourner performance an appropriately designed dynamic power plant equipped with a flat - plate selective solar collector is analyzed here (see Table 4.7). A number of assumptions are accepted as follows. A simple relation is used for the effective transmittance - absorptance products:
(τ α )b = (τ α )d = τ csα ps where
(4.33)
τ cs and α ps are the transparent cover transmittance and absorber absorptance,
respectively, both of them for short (solar) wavelengths. The collector's transparent cover is made up of crystal (light flint glass). Its thermal conductivity lies between 0.691 W (mK ) -100 °C and 1.025 W (mK )
−1
−1
at
at +100 °C (Lide, 1991). The ratio 0.34/11.5=0.0296 between
the PV array weight and total Sojourner weight can be used as a first estimate for the coefficient k appearing in Eq. (4.27). Preliminary tests were performed to determine an optimum collector area AC, opt close to Sojourner PV cell surface area (0.22 m2). Finally, the value A =0.23 m2 was used in computations. It corresponds to a radiator superficial mass density d a = 1.48 kg/m2 in Eq (4.27). It is rather close to the value d a =2.3 kg/m2 accepted in (Angelo and Buden, 1991) in case of the radiator of a nuclear power satellite but only half of the value d a =3 kg/m2 accepted in (Mozjorine et al., 1991) for a solar space power station. Table 4.7. Details about selective flat - plate solar collector design ( AC = 0.22 m ) 2
Quantity Number of transparent covers Transparent cover thickness Distance between transparent cover and absorber plate Bottom thermal insulation thickness Short wavelengths transparent cover transmittance Short wavelength transparent cover absorptance Long wavelengths (IR) absorber plate emittance Long wavelengths (IR) transparent cover emittance Thermal conductivity of bottom insulation (polyurethane)
Notation N
Value 1 0.003 m 0.045 m 0.1 m
τ cs α ps ε1 ε2 λb
0.82
a s b
0.90 0.10 0.88 0.024
W /(mK )
The distance between VL 1 and Pathfinder Lander is around 815 km. Thus, one expects quite similar meteorological and actinometric features in both places. Four strategies of collecting solar energy were considered in preliminary tests (Badescu, 1998a). The following two strategies will be used in this section: (i) horizontal collector strategy H; (ii) the collector tilt and orientation are continuously adjusted to keep the receiving surface perpendicular on Sun's rays - strategy P. Strategy H is easier to use while strategy P gives the higher power output most time of the year.
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Solar Collector Operation Solar collector thermal losses mainly depend on the heat transfer regime between absorber plate and transparent cover (separated through the layer 2 of thickness s in Figure 4.1). We considered the case of a horizontal solar collector. Three design solutions for the system solar collector - thermal engine were analysed (Table 4.8). They correspond to three different performance levels. For analysis we have chosen the middle of a clear sky autumn sol, when the thermal losses are rather high (sol 301 VL1, 14.04 local solar time (LST)). Table 4.8. Three design solutions for the system solar collector - thermal engine
Case (a) (b) (c)
ha 2 [ W /( m K ) ]
[ W /(m K ) ]
Thermal engine performance level
1 10 500
1 10 50
Low efficiency Medium efficiency High efficiency
hC 2
( ha = heat transfer coefficient between the working fluid passing through the radiator of the heat engine and ambient (see Eq (4.20));
hC =
heat transfer coefficient between solar collector and
working fluid (see Eq (4.17)).
Figure 4.4. Overall heat loss coefficient U L as a function of parameter s (distance between absorber plate and transparent cover - see Figure 4.1). Three design solutions (a), (b) and (c) were considered (see Table 4.8). (VL1 site, Autumn, sol 301, 14.04 LST).
The dependence of the overall heat loss coefficient U L on the distance s between absorber plate and transparent cover is shown in Figure 4.4 for the three cases of Table 4.8. The heat losses decrease by increasing s . This is specific to the conduction heat transfer regime. The thickness s is limited, however, by economic reasons. In the following we use
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s =0.045 m and the high efficiency engine (case (c) in Table 4.8). Note that the chosen value of s is about two times larger than the usual value for Earth placed solar collectors. For Earth placed solar collectors the heat transfer between absorber plate and transparent cover is mainly by convection. This prompted various technical solutions meant to keep convection at local level (the honeycombs and Francia cells are examples of solutions for convection suppression (see Meinel and Meinel, 1976, p. 404)). The convective heat transfer is activated when the product Gr ⋅ Pr exceeds 1000 (see Table 4.3(b)). We analysed the heat transfer above the absorber plate by using the whole set of available meteorological data (Table 2.1). The results show that the product Gr ⋅ Pr varies between 9.65 and 211.2, well below the threshold value of 1000. We draw the important conclusion that on Mars the thermal losses between absorber plate and transparent cover are exclusively by conduction.
Figure 4.5. Critical length X T (see Table 4.4) as a function of optical depth. A high efficiency engine was considered (see Table 4.8). All the available meteorological data were used.
The convection heat losses from transparent cover to atmosphere are mainly controlled by wind speed. The change from laminar to turbulent convection occurs in case the heat transfer surface exceeds a certain critical length X T (see Table 4.4). The flow regime above the transparent cover was analysed by using the whole set of available meteorological data.
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Viorel Badescu
Results are shown in Figure 4.5. The minimum value of the critical length X T is 5.43 m. Consequently, the convection heat transfer above the transparent cover is laminar. The critical length X T is smaller during winter and larger during summer (Badescu et al., 2000a). No significant difference between VL1 and VL2 sites is observed (note that a larger number of meteorological values are available for VL2 - see Table 2.1). The critical length obviously decreases when the optical depth increases. During the "clear sky" days (τ < 1) the critical length values have an important dispersion. Scattering diminishes during the dust storm days (τ > 1) . For the design solution we selected (case (c) in Table 4.8), the values of the overall heat −2
−1
loss coefficient U L range between about 0.5 and 1 Wm K (Figure 4.6). Broadly, these values are comparable with those of Earth located vacuum solar collectors (see e.g. Meinel and Meinel, 1976, p. 387). The dispersion of the U L values is slightly smaller during winter and higher during autumn (Badescu et al., 2000a). No obvious dependence of U L on the optical depth is observed. However, the dispersion of the U L values is larger for values
τ < 1 , i.e. during the "clear" days. Also, Figure 4.6 shows that U L doesn't depend significantly on the latitude of the solar collector.
Figure 4.6. Overall heat loss coefficient U L as a function of optical depth. A high efficiency engine was considered (see Table 4.8). All the available meteorological data were used.
Solar Thermal Power Generation on Mars
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Thermal Engine Operation An important influence on performance have the parameters ha and hC . For analysis we have chosen the middle of a clear sky autumn sol (sol 301 VL1, 14.04 local solar time (LST)). Some results are shown in Figure 4.7 for the maximum power provided by the thermal engine. The influence of both ha and hC is more important on the maximum power provided by the heat engine that on the overall efficiency (Badescu et al., 2000a).
Figure 4.7. Maximum power
W& max provided by the thermal engine as a function of the overall heat hC . Horizontal solar collector (strategy H). Unconcentrated solar
transfer coefficients h a and radiation was considered (VL1 site, Autumn, sol 301, 14.04 LST)
Generally, the influence on performance is strong for low values of both heat transfer −2
−1
coefficients ha and hC (less than 100 Wm K . The performances are practically not dependent on the higher values of hC . The influence of ha on performance is more significant. The strategy of collecting solar radiation has a rather weak influence on the dependence of performance on ha and. hC . As expected, strategy P leads to higher performance (Badescu et al., 2000a). The maximum output power could be as high as 12 W and 13 W in case of strategies H and P of collecting solar radiation, respectively (Badescu et al., 2000a). This is lower than the designed power of Sojourner PV arrays (16 W at noon). However, this comparison put in disadvantage the solar dynamic system as we used input meteorological data from late Autumn at VL1 site while Sojourner was designed to operate during Martian summer. This is a consequence of the fact that none of the 22 complete records available during summer at VL1 site (Table 2.1) corresponds to solar noon.
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Performance Dependence on atMospheric Optical Depth Previous results showed that the dynamic solar power plant performance depends significantly on the heat transfer coefficients hC and ha . Practical situations should normally lye between the cases (b) (i.e. medium efficiency engine) and (c) (i.e. high efficiency engine) in Table 4.8. These two cases will be used to provide lower and upper bounds for actual performance. To test the performance of the thermal engine - solar collector combination we simulated its operation at both VL1 and VL2 sites. We analyzed both the horizontal collector (strategy H) and the collector oriented perpendicularly on sun's rays (strategy P), respectively (Badescu et al., 2001a). At VL1 site we used meteorological data from summer, autumn and winter, year 1. All available data were used to simulate the operation at VL2 site. Some results are shown in Figure 4.8 (for solar efficiency) and Figure 4.9 (for output power).
Figure 4.8. Dependence of solar efficiency η
solar, opt
on the atmospheric optical depth at VL2 site.
High efficiency engine (see Table 4.8) and horizontal solar collector. All the available meteorological data for VL2 site were used.
The influence of latitude on performance is obvious. When the collector is horizontal, the solar efficiency is generally smaller at VL1 site as compared to VL2 site (Figure 4.8). When a P collector is considered, the efficiency increases (at small τ 's) but it is still smaller at VL1 site that at VL2 site (Badescu et al., 2001a). The maximum power provided by a horizontal collector at VL1 site shows some interesting features (Badescu et al., 2001a). Generally, it is smaller than in case of VL2 site. However, there are some situations (for τ ≈ 1) when the meteorological effects compensate the latitudinal effects and the output power is quite similar for both VL1 and VL2. If a P collector is used, the power increases for small τ 's but slighter at VL1 site than at VL2 site (Figure 4.9).
Solar Thermal Power Generation on Mars
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In case the medium efficiency engine is coupled to a horizontal collector, the efficiency does not exceed 0.13 at VL2 site (Badescu et al., 2001a). Generally, it is lower during summer, when the horizontal orientation is surely a good option (Badescu, 1998a). It is higher during winter, when the optical depth is higher, indicating dust storms occurrence. During dust storms the incident solar radiation is mainly diffuse and the horizontal orientation is the best strategy for radiation collection (Badescu, 1998a). In case a medium efficiency engine is coupled to a P collector, the maximum efficiency values lye around 0.13 (Badescu et al., 2001a). The efficiency increases at small optical depth values, which generally correspond to summer. The centre of the output data cloud is placed around 0.09-0.10. The P strategy does not diminish the performance at larger optical depth.
Figure 4.9. The same as Figure 4.8 in case of the maximum output power W& max . High efficiency engine and P solar collector.
For a horizontal collector attached to a high efficiency engine, the solar efficiency is as high as 0.18 (Figure 4.8). The qualitative features pointed out previously maintain. The lower sun-to-user efficiency corresponds to lower optical depth. If a P collector is considered, the solar efficiency increases during summer and spring but does not significantly exceed 0.18 (Badescu et al., 2001a). The centre of the output data cloud is placed around 0.15, higher than in case of the horizontal collector. Again, the P strategy does not diminish the performance. This strategy keeps constant the solar efficiency at higher optical depths but improves the performance as compared to the H strategy at smaller optical depths. The power provided by a system consisting in a horizontal collector and a medium efficiency engine does not exceed 7 W (Badescu et al., 2001a). Generally, it is lower for small optical depth. Indeed, the flux of direct solar energy is higher at smaller optical depth and the horizontal orientation is not recommended in this case. At higher optical depth direct solar radiation diminishes and diffuse radiation increases. As a result, the horizontal orientation is close to optimum. This explains the higher values of W& max around τ =1. For further increase
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of τ the diffuse radiation flux diminishes. Consequently, W& max decreases in this case. If a P collector is considered, the solar efficiency is higher during summer and spring, when the optical depth is small (Badescu et al., 2001a). Generally, the efficiency increases as compared to the H strategy. At high optical depth the solar efficiency is comparable for both H and P strategies. Using a better engine with a horizontal collector leads to output power up to 13 W for τ around 1 (during sols of spring, autumn and winter) (Badescu et al., 2001a). For small values of τ the output power is smaller. The P strategy is recommended in combination with high efficiency engines (Figure 4.9). In this case the sun-to-user efficiency during sols with small optical depth increases strongly, exceeding 25 W. The centre of the output data cloud is placed around 13 W. The P strategy can be used at high optical depth, too.
Performance Dependence on the Level of Solar Irradiance The dependence of solar efficiency on the level of incident global irradiance was studied in Badescu et al. (2001a). In case of a horizontal collector operating at VL2 site, a slightly non-linear relationship exists between solar efficiency and incident global irradiance for both the medium and the high efficiency engines. When the P collector is considered, the dependence is more complicated. When a combination medium efficiency engine - horizontal collector is considered, the efficiency is higher (whatever the incident irradiance is) during autumn and winter and lower during summer. This rather surprising fact is valid for the P collector, too. It is probably due to the influence of the ambient temperature, which is lower during autumn and winter. The situation is different in case of the high efficiency engine. Then, the solar efficiency is higher during summer, even if it corresponds to lower incident irradiance. This remark is even more obvious when a P collector is considered. A more uniform solar efficiency values distribution is obtained in this case. In case of a horizontal collector, the efficiency increases by increasing the irradiance level, whatever the type of engine is. For the P collector, the efficiency depends on the irradiance level in a more interesting manner. Thus, the lower bound of the efficiency increases with the irradiance level, but the upper bound practically does not depend on the irradiance level. This is valid for both the medium and high efficiency engines. During autumn and winter the dependence of η solar on the level of incident global irradiance is nearly similar for both the horizontal and the P collector operating at VL1 site. Important differences exist during summer. The P collector is more effective, as expected. The influence of irradiance level on solar efficiency decreases drastically beyond a certain threshold value (about 300 W/m2). This applies to both types of solar collectors. Figure 4.10 shows some results for the output power at VL1 site. Meteorological data from year 1 were used. In case of a horizontal collector the dependence of the maximum output power on the level of global irradiance is not differentiated upon season (Badescu et al., 2001a). When a P collector is considered, the same incident irradiance value leads to an output power obviously higher during summer. For a horizontal collector the output power increases when the input irradiance increases (Badescu et al., 2001a) This remark maintains for the P collector except for summer results (Figure 4.10).
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Figure 4.10 Dependence of maximum output power W& max on atmospheric optical depth at VL1 site. High efficiency engine (see Table 4.8).and P solar collector. Meteorological data for summer, autumn and winter year 1 were used.
Figure 4.11 Dependence of the maximum output power W& max on the level of solar global irradiance incident on a horizontal surface at VL2 site. High efficiency engine (see Table 4.8) and P solar collector. All the available meteorological data for VL2 site were used.
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The power provided by a system based on a horizontal collector increases at VL2 site with the level of solar irradiance, as expected (Badescu et al., 2001a). The increase is almost proportional in case of the medium efficiency engine and slightly non-linear for the high efficiency engine. Generally, there is no obvious dependence on season. In case of the P collector, the output power obviously depends on season, with a maximum during spring and summer and a minimum during autumn and winter. This is true for both the medium and high efficiency engines (Figure 4.11). The seasonal influence is similar for both solar efficiency and output power in case of a medium efficiency engine - horizontal collector combination (Badescu et al., 2001a). This is still valid when the collector is connected to a high efficiency engine. However, in this case the power values have a larger dispersion, which increases slightly with increasing the irradiance. In case of a medium efficiency engine and a P collector, the influence of the season is stronger on power than on solar efficiency (Badescu et al., 2001a). This is even more obvious if one connects a P collector to a high efficiency engine. The high solar efficiency values during spring and autumn at smaller irradiance values are not the main cause of the higher output power (which is obtained in summer (Figure 4.11)). For a medium efficiency engine, a P collector is recommended mainly during summer and spring (which are dust storm - free seasons) (Badescu et al., 2001a). One finds higher output power values as compared to the case when a horizontal collector is used. If the summer and spring values would be neglected, one can see that choosing a P instead of an H collector leads to a relatively small increase in power during the other two seasons (autumn and winter). This is valid for the high efficiency engine, too (Figure 4.11). However, the increase in power by using a P collector during seasons without dust storms is more spectacular. Compare the power values as high as 20 W obtained at lower input irradiance by using a P collector (Figure 4.11) with the power values of at most 12-13 W obtained at high irradiance values by using a horizontal collector (Badescu et al., 2001a).
Diurnal Variation of Performances The input data file we prepared in Section 2 contains only a few sols with complete records covering appropriately the whole daylight time. The most part of the sols has one to three records only associated to time periods close to sunrise, noon or sunset. In particular, no summer sol with complete records covering the whole day was found either for VL1 or for the VL2 site. For each season, we selected those sols that are richer in available data. In case of VL1 these sols are 301 (autumn) and 328 (winter). Note that no available data refers to spring (Table 2.1). In case of VL2 the sols selected are 420 (spring) and 872 (autumn). The sol 406 (winter) is also available but no reference to it will be made here, as the winter conditions are relatively similar for both Viking Lander sites. Various efficiencies defined in Section 4.1.3 were reported in Badescu et al. (2000b) in case of sol 301 (Martian autumn) at VL1 site. During most of the time the optimum engine efficiency η engine, opt lies around 33 %. The efficiency is decreasing suddenly near sunset. Generally, the optimum engine efficiency is less dependent on the type of engine and on the strategy of collecting solar radiation. In exchange, the system efficiency η system, opt is strongly dependent on engine quality and less dependent on the strategy of solar collection. It lies around 0.2 for the high efficiency engine and around 0.15 for the medium efficiency engine.
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When the high efficiency engine is considered, the decrease in performance is more abrupt near sunset. The optimum solar efficiency η solar, opt is smaller than the optimum system efficiency (Figure 4.12) but exhibits the same qualitative features. Generally, it doesn't exceed 15 % for the high efficiency engine and 10 % for the medium efficiency engine. The strategy of collecting solar radiation has not a strong influence on η solar, opt . In exchange, the strategy significantly influences the maximum output power W& max (Figure 4.13). If the optimum solar efficiency is rather constant during the day, the maximum power’s time variation is closely related to the temporal variation of solar irradiance. This is more obvious for the high efficiency engine. The maximum output power can exceed 15 W for the high efficiency engine and doesn't exceed 8 W for the medium efficiency engine. This proves that properly designed thermal power plants are comparable in performance with PV-based power systems (one reminds that Sojourner’s design output power is 16 W at solar noon). Moreover, the previous analysis puts in disadvantage the solar dynamic system as we used here input meteorological data from late autumn at VL1 site while Sojourner was designed to operate during Martian summer.
Figure 4.12 Optimum solar efficiency
η solar, opt
during sol 301 (autumn) at VL1 site. Medium
efficiency engine (ME) and high efficiency engine (HE) (see Table 4.8). Strategy H - horizontal collector; Strategy P - collector permanently kept perpendicular on Sun’s rays.
The hourly variation of solar collector’s optimum temperature is shown in Figure 4.14. It is less dependent on the strategy of collecting solar radiation and a little more dependent on engine quality. The high efficiency engine leads to a smaller optimum collector temperature. Generally, the collector temperature exceeds with more than 100 K the ambient temperature. The hourly variation of T C, opt is stronger than that of the ambient temperature. This proves that T C, opt is mainly controlled by the level of incident solar radiation.
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Figure 4.13. The maximum output power Figure 4.12.
W& max
during sol 301 (autumn) at VL1 site. For details see
Figure 4.14. Optimum solar collector temperature T C, opt associated to solar thermal power plant operation during sol 301 (autumn) at VL1 site. For details concerning the power plant see Figure 4.12.
The optimum temperature of the working fluid in the cold part of the engine ( T ' opt ) is well correlated with the time variation of the ambient temperature (Badescu et al., 2000b).
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T ' opt is smaller in case of the high efficiency engine, when the influence of the strategy of collecting solar radiation is obvious. This influence is less important in case of the medium efficiency engine. In exchange, the optimum temperature of the working fluid in the worm part of the engine ( T ' 'opt ) is better correlated with the hourly variation of the solar radiation (Badescu et al., 2000b). Both the engine quality and the strategy of collecting solar radiation are important factors. Generally, T ' 'opt t is close to T C, opt . Sol 328 belongs to winter at VL1 site. The main indicators of the solar thermal power plant are shown in Badescu et al. (2000b). The optimum solar efficiency values are rather close to the autumn values. The quality of the engine is very important and the strategy of collecting solar radiation is less important. This is due to the fact that sol 328 belongs to a dust storm period (Badescu, 1998a). The maximum output power is, however, much smaller than during autumn. At noon it reaches 10 W in case of the high efficiency thermal engine but doesn't exceed 5 W in case of the medium efficiency engine. The maximum output power time variation is stronger than that of solar efficiency but this is less obvious than in autumn. The daily variation of the optimum collector temperature is rather weak. Generally, the high efficiency engine leads to a lower optimum collector temperature. Also, the optimum temperature is lower for a collector perpendicular on Sun's rays. Sol 420 belongs to springtime at VL2 site. In this case, the optimum solar efficiency depends significantly both on engine quality and on the strategy of collecting solar radiation (Badescu et al., 2000b). In case of a P collector, the optimum solar efficiency is nearly constant during the day. It varies rather much for the horizontal collector (with a maximum at noon). The optimum solar efficiency values are quite close to those from autumn and summer at VL1 site. The maximum output power shows features similar to those of the optimum solar efficiency. Generally, the P collector assures a more constant maximum output power during the day. The engine quality is very important. The high efficiency engine connected to a P collector can ensure a maximum output power around 15 W during most part of the day. This is close to the design power of the PV system of Mars Pathfinder’s Sojourner. When a P solar collector is considered, the optimum collector temperature shows a remarkable constancy during the day. Sol 872 corresponds to autumn at VL2 site. The optimum solar efficiency shows an interesting variation during the day. This is more obvious for a P collector (Badescu et al., 2000b). In case of the horizontal collector, the optimum solar efficiency has a maximum around the noon. The optimum solar efficiency is higher in case of the high efficiency engine, as expected. It ranges from 8 to 16 %. The maximum output power shows similar features. Generally, the better performance in the morning corresponds to the stronger solar irradiance during that part of day (Badescu, 1998a). Note that a horizontal collector assures a constant power during the day. The high efficiency engine should be used in combination with a P collector. A maximum output power of 15 W can be provided only a short time period during the day. In case of a P collector, the optimum temperature is rather constant until 14.00 local solar time (LST). When a horizontal collector is considered, the optimum temperature has a maximum reached between 12.00 and 14.00 LST. Generally, T C opt is lower than in the cases above and this can be correlated to the smaller ambient temperature value.
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Correlation between Maximum Output Power and Optimum Solar Efficiency The dependence of the maximum output power on the optimum solar efficiency at VL1 site is shown in Badescu et al. (2000b). Meteorological data from year 1 were used. Let us consider the case of the medium efficiency engine. The maximum output power increases when the optimum solar efficiency increases, as expected. There is little dependence on season, except for a few summer values in case of the P collector, when the solar efficiency is obviously higher. Broadly speaking, there is little difference between the maximum output power provided by systems based on H and P collectors, respectively. The highest optimum solar efficiency is 0.11 and the maximum output power doesn’t exceed 10 W. When the high efficiency engine is considered, the influence of optimum solar efficiency on the maximum output power is important. The highest optimum solar efficiency is 0.16 and the output power can be as high as 15 W for an H collector and 17 W for a P solar collector.
Figure 4.15 Dependence of the maximum output power
η solar, opt
W& max
on the optimum solar efficiency
at VL2 site. High efficiency engine (see Table 4.8) and horizontal solar collector. Meteorological data for summer, autumn and winter (year 1) and spring, summer and autumn (year 2) were used.
Figure 4.15 shows some results obtained at VL2 site (Badescu et al., 2000b). All the available data for the two years of VL2 operation were used in computations. Generally, the dependence of the maximum output power on the optimum solar efficiency is non-linear. In
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case of a horizontal collector, the dependence seems to indicate a quadratic dependence ( W& max ∝ η solar, opt ). The coefficient of proportionality is smaller in case of the medium 2
efficiency engine (Badescu et al., 2000b). When the P collector is considered, the dependence W& max η solar, opt is more complicate, but keeps the quadratic feature. The P collector has a
(
)
more compact dispersion of the optimum solar efficiency values. It ranges from 8 to 12 % in case of the medium efficiency engine and between 13 and 19 % in case of the high efficiency engine. In all cases a certain optimum solar efficiency threshold (around 5 %) must be exceeded in order the system provide useful power. The dependence of the maximum output power on optimum solar efficiency is stronger in case of the high efficiency thermal engine than in case of the medium efficiency engine, on one hand, and in case of the P collector than for the horizontal collector, on the other one hand. It seems no obvious difference exists between the performances of the power plant in the two years of VL2 operation.
5. SOLAR STIRLING ENGINE A more realistic solar thermal engine is considered in this section. It consists of a solar collector - Stirling engine combination. The Stirling engine is indeed very attractive due to its operation at low temperature difference between the two heat reservoirs. This could enable power production during the Martian dust storm period, when both the incoming solar energy flux and collector temperature are small. Preliminary results were briefly reported in Badescu et al. (2001b) where the diurnal solar plant operation was studied. One concluded that the efficiency of a usual (Earth based designed) Stirling solar engine diminishes with about 8% when operates under Martian weather conditions. However, the recommended volumetric ratio lies between 1 and 2.6 and the best thermal agent is helium, in agreement with conclusions based on Earth made experiments. The model previously proposed in Badescu et al. (2001b) is now presented. A number of improvements are also included (Badescu, 2004).
Solar Engine Model The solar engine consists of a selective flat-plate solar collector coupled to a Stirling engine with partial heat regeneration. No heat storage system is considered in this approach.
Solar Collector Model First, we shall consider the flat-plate solar collector (Figure 5.1). Its main components are the collector plate and a transparent cover of thickness a . The gap of thickness s between these two components is filled with carbon dioxide at Martian atmospheric pressure. Solar direct and diffuse radiation penetrates the transparent cover and is absorbed by the collector plate. The thermal energy generated in the solar collector plate is transferred to the thermal agent at the hot head of the Stirling engine and later-on part of it is converted into work.
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Figure 5.1. The solar collector of the Stirling engine.
Steady state energy balance for the solar collector yields
Q& abs − Q& '−Q& lost = 0
(5.1)
Here Q& abs is the thermal energy flux generated into solar collector plate, Q& lost is the heat flux lost towards the ambient and Q& ' is the heat flux transferred to the thermal fluid inside the Stirling engine. The thermal energy flux generated into the solar collector plate is given by
Q& abs = ϕ abs Ac
(5.2)
where Ac is the area of collector plate surface. The heat flux lost towards the ambient is given by the usual Newton relationship:
Q& lost = U L AC (TC − Ta )
(5.3)
where U L is the overall heat loss coefficient, while TC and Ta are collector and ambient temperature, respectively. Note that TC is an averaged value over collector surface and normally is not constant in time. Seven temperatures are associated to solar collector operation (Badescu, 2004). With a single except (i.e. the average temperature of bottom insulation) they have the meaning explained in Section 4.1.1 (Tables 4.1 and 4.2). The collector heat losses could be studied by using the thermal resistance method (see section 4.1.1). Then, the flux of heat losses q& lost per unit collector surface area is defined by:
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q&lost ≡
T − Ta Q& lost = U L (TC − Ta ) = C Rtot Ac
883
(5.4)
where Rtot is the total thermal resistance given by
Rtot =
R 4 R5 R1 R2 + R3 + R1 + R2 R4 + R5
(5.5)
Note that Rtot here is equivalent to R1−5 in the model of solar collector of section 4.1.1. Therefore, Figure 4.2 and Table 4.2 show the meaning of the thermal resistances R1 to R5 . Details concerning the computation of these thermal resistances are similar to those presented in Section 4.1.1 and will be not repeated here.
Stirling Engine Model During the 1980s Prof. I. Kolin at the University of Zagreb and Prof. J. Senft at the University of Wisconsin started research on low temperature differential Stirling engines and developed the first Stirling engine running with a temperature difference below 20 degrees Celsius (Senft, 1996). Meanwhile a rather large number of research or commercial Stirling engines using unconcentrated solar radiation were built, with powers from a few to tens of Watts (Badescu, 2004). A simple Stirling engine model is used at this stage of the analysis. It was first developed in Howell and Bannerot (1977) and sligthly improved in Badescu (1992). The model is based on two simplifying assumptions. First, one neglects the heat losses during the thermal transfer from the solar collector to the working fluid inside the engine. Second, one neglects the friction of the moving parts. These make of course the results reported below to be upper bounds for the performance of a real solar Stirling system. The Stirling cycle efficiency η Stirling is defined as:
η Stirling =
η max P = Q& ' 1 + Dη max
(5.6)
where P is the output mechanical power while η max = 1 − Ta / TC is the maximum efficiency of the cycle in case of perfect heat regeneration. In case the thermal agent is an ideal gas the parameter D is given by (Howell and Bannerot (1977), Badescu (1992)):
D=
x ( k − 1) ln ε V
(5.7)
Here x(∈ [0,1]) is the heat regeneration factor, k is the adiabatic exponent of the thermal agent and
εV is the volumic ratio (i.e. the ratio of the extreme values of the thermal agent
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total volume). x = 0 means ideal heat regeneration. In this case the efficiency of the Stirling engine Eq (5.6) equals the Carnot efficiency. Use of Eqs (5.1),(5.2),(5.3) and (5.6) yields the following dependence of the power provided P on the collector plate temperature TC :
P (TC ) =
1 − Ta / TC [ϕ abs − U L (TC − Tc )] AC 1 + D(1 − Ta / TC )
(5.8)
Note that U L is not a constant but depends on TC (among other variables) (see Figure 5.4). Consequently, a simple numerical procedure to maximize directly the power P given by Eq (5.8) was used here, as follows. One monotonously increases the plate temperature TC starting from the ambient temperature. For any value of TC one evaluates first the overall heat loss coefficient U L (Eq (5.4)) and then the output power P (Eq (5.8)). The maximum power Pmax and the appropriate optimum plate temperature TC ,opt are finally selected from the series of results. The way of using the output power of the Stirling engine is not relevant for this study as the key aspect here is the comparison with the output power of a similarly sized PV-based system. Consequently, electric generators and/or gear boxes are not considered, neither efficiencies for these (possible) components are included in the model. Use of the power P allows to define the solar energy conversion efficiency (or solar-touser efficiency) as η sol ≡ P /(ϕ inc AC ) . The maximum solar efficiency is of course given by
η sol ,max = Pmax /(ϕ inc AC )
(5.9)
Note that in the case analysed here both η sol and P have their maximum for the same value TC ,opt .
Results and Discussions A horizontal solar collector will be considered. This is the easier-to-use strategy, that gives for many periods of time a performance less than 10% smaller than the strategies involving more sophisticated, orientable, solar collectors (Badescu et al., 2000a, 2000b, 2001a). Details about solar collector design are given in Table 4.7 (where the information about the bottom insulation should be omitted of course). The values of the effective transmittance- absorptance products were computed with (τα )dir = (τα )dif = τα . Three Stirling engine thermal agents are usually considered: carbon dioxide (adiabatic exponent k = 1.33 ), air ( k = 1.4 ) and helium ( k = 1.66 ). Helium gives the best performance and is our choice for this section. A simple analysis proves that the Stirling engine efficiency increases by increasing the compression ratio ε V . Here the value ε V = 2 is adopted as a good
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compromise between better performance and smaller engine size. Increasing the heat regeneration parameter x from the ideal value x = 0 diminishes the engine output power. Here the value x = 0.2 is accepted, in agreement with current terrestrial practice. Results of computations performed by using the meteorological data during the autumn and winter of the first year at VL1 site are shown in Figure 5.2. It is obvious that both the maximum power Pmax and the maximum solar efficiency η sol ,max increase around the solar noon. However, η sol ,max seems to be less dependent on solar time than Pmax . The maximum power of the solar Stirling engine around the noon is comparable in magnitude with the designed power of Sojourner’s PV cells system (i.e. 16 W). Also, the solar efficiency is as large as 18 %, which is close to the design value of Sojourner’s PV cells efficiency (about 18 %). Note, however, that the horizontally placed collector is a good solar energy collection strategy especially during autumn and winter. Indeed, results not shown here prove that during spring and summer the solar Stirling engine performance is slightly worse. During the warm season other strategies of collecting solar energy are much more effective (Badescu, 1998a).
Figure 5.2. Dependence of maximum power Pmax and maximum solar efficiency
η sol ,max on local
solar time (in Earth hours). Results obtained by using the meteorological data during the autumn and winter in the first year at VL1 site.
The large dispersion of the results in Figure 5.2 is mainly due to the influence of optical depth. The performances of solar Stirling engine obviously decrease by increasing the atmospheric optical depth (Badescu, 2004). The maximum efficiency η sol ,max is less dependent on the optical depth than the maximum power Pmax . Note than under-unitary optical depth values are usually associated with “clear sky” conditions while during the dust storm the optical depth has larger values (Badescu, 2001).
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Figure 5.3. Dependence of the maximum power Pmax and optimum collector temperature maximum solar efficiency
TC ,opt
on
η sol ,max . All available meteorological data were used (see Table 2.1).
The dependence of the maximum output power Pmax on optimum solar efficiency
η sol ,max is shown in Figure 5.3. All the meteorological data of Table 2.1 were used. The maximum output power increases when the optimum solar efficiency increases. Generally, the dependence of Pmax on η sol ,max seems to indicate a quadratic relationship. This is in agreement with previous results obtained in case of solar Carnot engines. A certain optimum solar efficiency threshold (around 5 %) must be exceeded in order the system provide useful power. Again, this confirms previous results reported in section 4. The optimum solar collector temperature TC ,opt increases by increasing the solar efficiency, as expected. The larger dispersion of the TC ,opt values for the same value of the solar efficiency is mainly due to the difference in the solar time. Figure 5.4 shows that the overall heat loss coefficient U L increases by increasing the collector temperature. The same set of meteorological data as in case of Figure 5.3 was used. −2
The values of U L range between 0.3 and 0.7 Wm K
−1
. Broadly, these values are smaller
than those of Earth located flat-plate vacuum solar collectors (see e.g. Benz and Beikircher (1999) where the experimentally derived overall heat loss coefficient is about 1.25
Wm −2 K −1 ) during a rather heavy utilization as steam production). They are slightly smaller than the results obtained during simulation of the Carnot solar engine in section 4 ( U L values −2
−1
between 0.5 and 1 Wm K ). This is to be expected as an (ideal) Carnot engine normally operates at higher collector temperature than the Stirling engine considered here. The dependence of U L on collector temperature justifies a posteriori the numerical optimization procedure we used in this section.
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Figure 5.4. Dependence of overall heat loss coefficient U L on collector temperature. All available meteorological data were used (see Table 2.1).
6. CONCLUSION The chapter focuses on solar power generation on Mars surface. A "dynamic" solar power plant (which consists in a solar collector - thermal engine combination) is proposed as an alternative for the more usual photovoltaic cells. Upper bounds for the efficiency of solar thermal power plants operating in the Martian environment are evaluated in section 3. Three different theories are usually quoted in literature to compute the maximum work that can be extracted from a given amount of thermal radiation energy. Using an original thermodynamic argument here we showed that these theories do not contradict each other but they predict upper bounds of different accuracy degree for the amount of work provided by a real conversion system. As far as the traditional thermodynamic approach is considered, the theory proposed by Jeter gives the exergy of thermal radiation. The above theories predict too high efficiencies for radiation energy conversion into work to be of practical interest. Much more accurate simple upper bounds were already proposed in literature. For reader convenience they are summarized in section 3.2 and applied to power plants operating on Mars under both direct and diffuse solar illumination. Both black-body and selective absorbers were considered. A more elaborated model uses an endoreversible Carnot cycle to describe solar engine operation in section 4. The solar power plant is designed to operate during the whole Martian year. Consequently, it contains a selective flat - plate solar collector. A detailed model of collector heat losses towards the ambient is developed. The optimization procedure developed in section 4.1 is based of finite-time thermodynamics methods. The following two strategies of collecting solar energy were analysed in this chapter: (i) horizontal collector - strategy H;
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(ii) the collector tilt and orientation are continuously adjusted to keep the receiving surface perpendicular on Sun's rays - strategy P. The first strategy is easier to built and use while the later strategy provides higher collected solar energy most time of the year. A medium and a high efficiency thermal engine were analysed. Practical situations should normally lye between these two cases. All the computations were performed for a solar collector comparable in size with Pathfinder’s Sojourner (solar energy collection area of 0.22 m2). During the application we used as input data values of atmospheric pressure and temperature, wind speed and atmospheric optical depth measured at Viking Landers sites. The main results are: (1) The heat losses between the solar collector absorber plate and transparent cover are exclusively by conduction. This differs from the Earth-based solar collector where the main heat loss mechanism is convection. (2) The convection heat transfer above the transparent cover is laminar. This differs from the Earth-based solar collectors where turbulence is the main convection mechanism. (3) For the design solution we selected, the values of the overall heat loss coefficient −2 −1 U L range between about 0.5 and 1 Wm K . Roughly, these values are
comparable with those of Earth located vacuum solar collectors. The dispersion of the U L values is slightly smaller during winter and higher during autumn. No obvious dependence of U L on the optical depth is observed. However, the dispersion of the U L values is larger for values during the "clear" days. U L does not depend significantly on the latitude of the solar collector. (4) Two parameters are used to quantify the heat transfer inside the thermal engine. They are ha (the heat transfer coefficient between the working fluid passing through the radiator of the heat engine and ambient; see Eq. (4.20)) and hC ( the heat transfer coefficient between solar collector and working fluid (see Eq (4.17)). The influence of ha on performance is more significant. (5) The strategy of collecting solar radiation has a rather weak influence on the dependence of performances on ha and hC . As expected, strategy P leads to higher performances. (6) The dynamic solar power plants equipped with selective flat - plate collectors could provide power comparable to that of similar-size PV cell systems. (7) The influence of latitude on performance is obvious. Generally, the solar efficiency is smaller at VL1 site as compared to VL2 site for both strategies of collecting solar radiation. In most cases the maximum power provided by a horizontal collector at VL1 site is smaller than at VL2 site. However, in some situations the meteorological effects compensate the latitudinal effects and the output power is quite similar at both VL1 and VL2 sites. (8) In case a medium efficiency engine is coupled to a horizontal collector, the solar efficiency does not exceed 0.13 at VL2 site. Generally, it is lower during summer and higher during winter's dust storms. In case the medium efficiency engine is coupled to a P collector, the solar efficiency increases during summer.
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(9) The solar efficiency is as high as 0.18 in case of a horizontal collector attached to a high efficiency engine. If the high efficiency thermal engine is connected to a P collector the solar efficiency increases significantly during summer and spring but does not exceed 0.18. (10) Using a high efficiency engine coupled to a horizontal collector leads to output power up to 13 W during spring, autumn and winter. (11) The P strategy is recommended mainly during summer and spring in combination with high efficiency engines. In this case the output power could be as high as 25 W. (12) During an autumn day at VL1 site (sol 301) the optimum engine efficiency is around 33 %. The system efficiency lies around 20 % for the high efficiency engine and around 15 % for the medium efficiency engine. The optimum solar efficiency doesn't exceed 15 % and 10 %, respectively, in the two cases. The maximum output power can exceed 15 W and doesn't exceed 8 W for the high and medium efficiency engine, respectively. . (13) During a winter dust-storm day at VL1 site (sol 328) the maximum output power is much smaller than during autumn. At noon it reaches 10 W in case of the high efficiency thermal engine but doesn't exceed 5 W in case of the medium efficiency engine. (14) During a spring day at VL2 site (sol 420) the optimum solar efficiency values are quite close to those from autumn and summer. The high efficiency engine connected to a solar collector kept perpendicular on Sun’s rays can ensure a maximum output power around 15 W during most part of the day. This is close to the design power of the PV system of Mars Pathfinder’s Sojourner. (15) During an autumn day at VL2 site (sol 872) the optimum solar efficiency ranges from 8 to 16 % in case of a good quality engine. The high efficiency thermal engine should be used in combination with a solar collector kept perpendicular on Sun’s rays. A maximum output power of 15 W might be provided a short time period during the day. (16) When a horizontal solar collector is considered, the dependence of the maximum output power on optimum solar efficiency seems to be quadratic at both VL1 and VL2 sites. When a collector perpendicular on Sun’s rays is considered, this dependence is more complicate, but keeps the quadratic feature. (17) A certain optimum solar efficiency threshold (around 5 %) must be exceeded in order the system provide useful power. (18) The dependence of the maximum output power on the optimum solar efficiency is stronger in case of a high efficiency thermal engine than in case of a medium efficiency engine, on one hand, and in case of a collector kept perpendicular on Sun’s rays than in case of a horizontal collector, on the other one hand. (19) No obvious difference exists between power plant performances in the two years of VL2 operation. A solar Stirling engine based on a horizontal selective flat-plate converter is analyzed in section 5. A numerical optimization procedure was used to maximize the power provided by the engine. The main results are as follows:
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Wm −2 K −1 . (2) The solar energy conversion efficiency at noon could be as high as 0.18 at VL2 site during autumn and winter. Generally, it is lower during spring and summer. (3) The output power at noon produced by the Stirling engine at VL2 site was as high as 16 W during autumn and winter. It obviously decreases during the dust storm periods. (4) Properly designed solar Stirling engines equipped with horizontal flat-plate collectors could provide output power comparable in magnitude to that of PV cell systems. However, this conclusion should be treated with caution as it is based on figures referring to an existing PV system, on one hand, and to a simplified solar Stirling engine model, on the other one hand. (5) To increase the output power and the efficiency, the design parameters of Stirling engines operating on Mars should be different from those of terrestrial engines. For example, one expects the compression ratio to exceed the usual value ε V = 2 while a smaller regeneration factor than x = 0.2 to be implemented.
ACKNOWLEDGMENTS I am indebt to my father, Mihail (Misu) Badescu, who first showed me the rules. I thank Prof. Gheorghe Popescu and Dr. Monica Costea (Polytechnic University of Bucharest) and Prof. Michel Feidt (University of Nancy) for previous collaboration.
REFERENCES Aldrich, A.D. In Mars: Past, present and future; Pritchard E.B.; Ed.; Progress in Astronautics and Aeronautics; AIAA: Washington, DC, 1992; Vol 145, pp 3-11. Angelino G.; Invernizzi C. J Solar Energy Engng. 1993, 115, 130-137. Angelo J.A.; Buden D. Jr, The nuclear power satellite (NPS) - key to a sustainable global energy economy and solar system civilization; Proc. SPS 91; Paris, 1991; pp 117 - 124. Badescu V.; J. Sol. Energy Engng. 1988a, 110, 349. Badescu V.; Entropie 1988b, 145, 41-45. Badescu V.; J Phys D 1990, 23, 289-292 . Badescu V.; J Phys D 1991, 24, 1882-1885. Badescu V.; Int J Energy 1992, 17(6), 601-607. Badescu V.; Space Technol 1994, 14(5), 331-337. Badescu V.; Acta Astronautica 1998a, 43 (7-8), 409-421. Badescu V.; Acta Astronautica 1998b, 43(9-10), 443-453. Badescu V.; Phys Lett A 1998c, 244, 31-34. Badescu V.; J Phys D 1998d, 31, 820-825. Badescu V.; J. Non-Equilib. Thermodyn. 1999, 24, 196-202. Badescu V.; Int. J Solar Energy 2000, 20, 149-160. Badescu V.; Renewable Energy 2001, 24, 45-57.
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Badescu V.; J. Sol. Energy Engng. 2004, 126, 812-818. Badescu V.; Popescu G.; Feidt M.; Model of optimized solar heat engine operating on Mars, Proc of ECOS98; Bejan A.; Feidt M., Moran M. J.; Tsatsaronis G.; Eds.; Nancy, France, 1998; pp 813-819. Badescu V.; Popescu G.; Feidt M.; Energy Conv Mngmnt. 1999, 40, 1713-1721. Badescu V.; Popescu G.; Feidt M.; Renewable Energy 2000a, 21, 1-22. Badescu V.; Popescu G.; Feidt M.; J British Interplanetary Soc. 2000b, 53 (3/4), 131-144. Badescu V.; Popescu G.; Feidt M.; Acta Astronautica 2001a, 49 (12), 667-679. Badescu V.; Popescu G.; Feidt M.; Costea M.; Termotehnica 2001b, 5(1), 24-28. Bejan A.; Advanced engineering thermodynamics; Wiley: New York, 1988. Bejan A.; J Sol Energy Engng. 1987, 109, 46-51. Benz N.; Beikircher T.; Solar Energy 1999, 65, 111-118. Candau Y.; Solar Energy 2003, 75, 241-247. Collozza, A.J.; Preliminary design of a long - endurance Mars aircraft, NASA CR185243, Sverdrup Technology Inc., Aerospace Technology Park, Brookpark, Ohio 44135, prepared for Lewis Research Center under Contract NAS 3-25266, April 1990. Duffie J. A.; Beckmann W. A.; Solar Energy Thermal Processes; Wiley: New York, 1974. Eaton C.B.; Blum H.A.; Solar Energy 1975, 17, 151-158. Golombek M. P.; Cook R. A.; Economou T.; Folkner W. M.; Haldermann A. F. C.; Kallemeyn P. H.; Knudsen J. M.; Manning R. M.; Moore H. J.; Parker T. J.; Rieder R.; Schofield J. T.; Smith P. H.; Vaughan R. M.; Science 1997, 278 (5344), 1743-1748. Hibbs B.D.; Mars rover feasibility study, Final Report Aero Vironement, Inc, Report AV -FR 89/7011, October 1989. Hourdin F.; Forget F.; Talagrand O.; J. Geophys. Res.1995, 100(E3), 5501-5523. . Howell J. R.; Bannerot, R.B.; Solar Energy 1977, 19, 149-153. Jeter S. J.; Solar Energy 1981, 26, 231-236. Landsberg P. T., Tonge G.; J Appl Phys 1979, 51, R1-R20. Landsberg P.T.; Mallinson, J. R.; Thermodynamic constraints, effective temperatures and solar cells, In Coll. Int. sur l'Electricite Solaire, CNES: Toulouse, 1976, pp 27-35. Landsberg P. T.; Badescu V.; Europhys Lett. 2000, 50(6), 816-822. Lee S.W.; Viking Lander Meteorology and Atmospheric Opacity Data Set Archive, Volume VL-1001, Laboratory for Atmospheric and Space Physics, Campus Box 392, University of Colorado, CO 80309-0392, (10 July 1995). Lide D. R.; Ed.; Handbook of chemistry and physics, 71st Edition; C.R.C. Press, 1991, pp 1539. Martin L. J.; Zurek R. W.; J. Geophys. Res.1993, 98(E2), 3221-3246. McKissock, B.I.; Kohout L.L.; Schmitz P.C.; A solar power system for an early Mars expedition, NASA Technical Memorandum 103219, Lewis Research Center, Cleveland, Ohio, American Institute of Chemical Engineers, Summer National Meeting, August 1923, 1990. McLallian K.L. et al., The solar dynamic radiator with a historical perspective, Proceedings of the 23rd International Energy Conversion Engineering Conference, Denver, CO, vol 3, ASME, July 31-Aug 5 1988, pp. 335-340. Meinel A. B.; Meinel M. P.; Applied Solar Energy, Addison-Wesley Publishing Company: Reading, 1976.
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Menetrey W. R.; In Introduction to the utilization of solar energy; Zarem A. M.; Erway D. D.; Eds.; Mc Graw Hill: New York, 1963, p. 326. Mozjorine Y.A.; Senkevich V.P.; Koval A.D.; Narimanov E.A.; Small - scale space power stations: feasibility and usage prospects; Proc. SPS 91, Paris, 1991, pp. 381 - 392. Petela R.; J Heat Transfer 1964, 86, 187-192. Petela R.; Solar Energy 2003, 74, 469-488. Pop M. G.; Leca A.; Prisecaru I.; Neaga C.; Zidaru G.; Musatescu V.; Isbasoiu E. C.; Indrumar -Tabele, monograme si formule termotehnice; Editura Tehnica: Bucuresti, 1987, vol 1. Pollack J. B.; Haberle R. M.; Murphy J. R.; Shaeffer J.; Lee H.; J. Geophys. Res.1990, 95, 1447-1473. Press W. H.; Nature 1976, 264, 734-735 . Prisnjakov V.; SPS interest and studies in USSR, In Proc. SPS 91, Power from space, Paris 27-30 August 1991, p 36. Prisnjakov V. F.; Statsenko I. N.; Kondratjev A. I.; Markov V. L.; Petrov B. E.; Gabrinets V. A.; Developing space power Brayton systems with solar heat input. Research of working process of high temperature latent heat storage system, In Proc. SPS 91, Power from space, Paris 27-30 August 1991, p. 465-470. Prisnjakov V. F.; Statsenko I. N.; Kondratjev A. I.; Markov V. L.; Petrov B. E.; Gabrinets V. A.; Space Power 1994, 13(3&4), pp. 135-144. Secunde R.; Labus T. L.; Lovely R. G.; Solar dynamic power module design, In Proc 24th International Energy Conversion Conf., IEEE: Piscataway NJ, 1989, Vol. 1, pp 299-307. Senft J. R.; An introduction to low temperature differential Stirling engines; Moriya Press: River Falls, WI, 1996. Spanner D. C.; Introduction to thermodynamics, Academic Press: London, 1964, p 218. Stefanescu D.; Marinescu M.; Danescu A.; Transferul de caldura în tehnica; Editura Tehnica: Bucuresti, 1982, Vol. 1. Weingartner S.; Blumenberg J.; Ruppe H. O.; Space Power 1994, 13 (1&2), 103-120. Zurek R. W.; Barnes J. R.; Haberle R. M.; Pollack J. B.; Tillman J. E.; Leovy C. B.; In Mars; Kieffer H. H. et al; Eds.; University of Arizona Press, 1992, pp 835-933.
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 893-914
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 30
EQUILIBRIUM PHASES IN ZIRCONIUM ALLOYS OF CONCERN TO THE NUCLEAR INDUSTRY: ISOTHERMAL SECTIONS OF THE ZR-CR-SN AND ZR-CR-TI SYSTEMS* S.F. Aricóa, R.O. Gonzáleza and L.M. Gribaudoa,b a
Departamento Materiales, Centro Atómico Constituyentes, Comisión Nacional de Energía Atómica, Avda. Gral. Paz 1499, B1650KNA, San Martín, Argentina b Consejo Nacional de Investigaciones Científicas y Tecnológicas, Avda. Rivadavia 1917, C1033AAJ, Buenos Aires, Argentina
ABSTRACT Zirconium has a low neutron capture cross-section and it is used in alloys for internal components of nuclear reactors, the currently named Zircaloy, Zr-Nb, ZIRLO, etc. In Zircaloy-2 and Zircaloy-4, chromium is an important component in order to assure good corrosion performance, and tin is one of the strengthening elements. On the other hand, titanium, in spite of its poor neutron transparency, has sometimes been considered an element, which could substitute zirconium in this kind of alloy. The present experimental study concerns two ternary systems Zr-Cr-X (being the X component Sn or Ti). Published data on phase equilibriums of these systems are very scarce and found only in Russian works. Many contributions to the knowledge of phase equilibriums in ternary and quaternary systems involving zirconium as the principal component were assessed by Ivanov O.S. et al. and published by the Metallurgical Institute of Moscow in the monograph Zirconium Alloys Structures in 1973. Stability domains of phases at different temperatures of those two ternaries were presented, especially as isothermal sections of the equilibrium diagram. *
A version of this chapter was also published in Nuclear Energy Research Progress edited by Veda B. Durelle published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research.
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S.F. Aricó, R.O. González and L.M. Gribaudo The knowledge of transformations through equilibrium diagrams is essential in order to design or improve technological applications, especially in the temperature range where the Zr rich hcp/bcc solid solution reaction is possible. Alloys were prepared by melting the metal components in a non-consumable tungsten electrode arc furnace with a copper crucible under a high purity argon atmosphere. Phase characterizations and determination of their compositions were carried out by metallographic observations and electron microprobe analysis. X-ray diffraction was performed on some samples. The study of the Zr-Cr-Sn system involves alloys with compositions between 0 and 15 at. % Cr and 0 to 15 at. % Sn and heat treatments at temperatures of 860, 900, 960 and 980 ºC. Three alloys of the Zr-Cr-Ti system with 40 at. % Cr and different Zr/Ti ratios and one more, richer in Cr, were elaborated. Specimens were heat treated at 900 and 1100 ºC respectively. Results of equilibrium between the solid solutions and the intermetallic compounds are presented as tie lines and isothermal sections where the phase boundaries are also sketched.
INTRODUCTION Phase diagrams and phase transformations of several multicomponent Zr-based systems have been studied in the last years in the Phase Transformations Group of the Centro Atómico Constituyentes of the Comisión Nacional de Energía Atómica from Argentina. Experimental determinations, especially in the Zr rich zone were done in the Zr-Sn-O [1-2], Zr-Nb-Sn [3], Zr-Nb-Sn-O [4], Zr-Sn-Ti [5-6], Zr-Sn-Nb-Fe [7], Zr-Sn-Fe [8], Zr-Nb-Fe [9-10], Zr-Cr-O [11] and Zr-Sn-Hf [12] or thermodynamically modeled for the Zr-Ti-Nb system [13]. Knowledge of the properties of these systems are important in the nuclear technology because their components are the corresponding to the principal alloys used nowadays in internals of reactors (Zircaloy-2, Zircaloy-4, Zr-2.5Nb) or of possible use in the future (ZIRLO, E635) or new hypothetical designed materials where some of the elements, i.e. zirconium by titanium, could be partially changed. In this chapter, experimental results about phases in equilibrium in two ternary systems concerning the above considerations, i.e. Zr-Cr-Sn and Zr-Cr-Ti, are presented. The following is an outlook of the published works found in the technical literature about both systems. The comments are intended to justify the reason of performing the present work. The more recent studies on the ternary Zr-Cr-Sn system are the works published in the Soviet Union between 1959 and 1963. During this period, three isothermal sections of the equilibrium diagram in the Zr rich zone at 850 ºC, 960 ºC and 1000 ºC respectively were presented in works where Ivanov O.S. is one of the authors. Ivanov et al. then assembled these works in the second chapter State diagrams of the ternary systems of the compiled book Zirconium Alloy Structure, in Russian language [14]. The corresponding three limiting binary systems Zr-Cr, Cr-Sn and Zr-Sn, which confine the ternary Zr-Cr-Sn, have been relatively well studied during the past decades. There exist critical assessments of the three systems, by Arias et al. for Zr-Cr [15], by Venkatraman et al.
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for Cr-Sn [16] and by Abriata et al. for Zr-Sn [17] then compiled by Massalski et al. in reference [18]. Thermodynamic modeling of phases with diagrams computationally calculated for the three subsystems is also found in the specialized literature [19-21]. On the other hand, more recently, new contributions were made regarding the conditions of the phase transformations in the Zr-Cr and Zr-Sn system. Especially important are those related to equilibriums in the zirconium rich zone made by González et al. [11] and by Roberti [22] for these systems. Taking into account the posterior discussion of the present results in this chapter it is important to mention that three types of Laves phases ZrCr2 are found in the Zr-Cr system with the following stability temperature ranges [15]: the cubic C15 αZrCr2 ( from room temperature to 1592 ºC ), the hexagonal C36 βZrCr2 ( from 1582 ºC to 1622 ºC ) and the hexagonal C14 γZrCr2 ( from 1622 ºC to 1673 ºC ). The relatively wide range of composition of these intermetallic compounds starts from 64 up to 69 at. % Cr. The compositions of the alloys ZCS1, ZCS2, ZCS3, ZCS4, ZCS5 and ZCS6 were chosen fundamentally in order to know the equilibriums of the Zr rich solid solutions α and β phases, and those of alloys ZCS7 and ZCS8 to investigate if a ternary compound like the θ phase of about 68 at. % Zr and 24.5 at. % Sn in the Zr-Fe-Sn system would be formed [23]. In order to study equilibriums between the zirconium rich solid solutions and the intermetallic compounds richest in this element in the Zr-Cr-Sn system, i.e. αZrCr2 and Zr4Sn, six alloys were elaborated. Compositions in Zr were between 91.1 at. % and 92.9 at. % with different Cr/Sn relations ( between 0 at. % and 6.6 at. % Cr and Sn decreasing from 8.4 at. % to 0 at. % ). In order to investigate if a ternary compound could be formed in this region, two other alloys, with 4 at. % Cr -15 at. % Sn and with 15 at. % Cr - 7.5 at. % Sn were obtained as well. The previous studies related to the ternary system Zr-Cr-Ti were published in the sixties of the last century. In a first work Kornilov et al. [24] traced projections of the liquid and the solid boundaries at temperatures between 1200 and 1800 ºC ( level lines ). The same authors in 1969 [25] presented partial isothermal sections of the equilibrium diagram at various temperatures between 650 ºC and 1400 ºC. In the figures of that work, the boundaries of the stable phases, liquid, solid solutions and the intermetallic compound are suggested but no tie line for compositions of the conjugated phases in equilibrium is mentioned. An early work, from 1995, by Kornilov I.I. et al. [26] deals with the equilibrium phase diagram in the pseudo-binary ZrCr2-TiCr2 system. In this work, the stability domains of two Laves phases types ( with an AB2 stoichiometry ) which are formed in the system, i.e. the cubic C15 α(Zr,Ti)Cr2 and the hexagonal C14 γ(Zr,Ti)Cr2, are presented. The hexagonal type, C36 β(Zr,Ti)Cr2, which is stable at intermediate temperature, is not mentioned. Similarly to the Zr-Cr-Sn, the corresponding three limiting binary systems of the Zr-CrTi have been well studied during the past decades. The Zr-Cr was already considered here above; the Cr-Ti was first evaluated by Murray J.L. in 1981 [27]. The same author published a new assessment in 1987 [28] with changes in the diagram in the zone where the formation or transformations of the intermetallic compound are present. Three types of Laves phases are mentioned to be present in the Cr-Ti system with the following stability temperature ranges [28]: the cubic C15 αTiCr2 ( from room temperature to 1220 ºC ), the hexagonal βTiCr2 ( from 800 to 1270 ºC ) and γTiCr2 ( from 1270 to 1370 ºC ). The author names βTiCr2 as the C14 and γTiCr2 as the C36 for the Pearson symbol of the crystal structures. The range of
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composition for these compounds is 63 - 66 at. % Cr. At 900 and 1100 ºC it would exist equilibrium between αTiCr2 and βTiCr2. The Zr-Ti is a system where both elements are mutually interchanged in the liquid, in the bcc β and in the hcp α solid phases. The diagram with congruent phase transitions, assessed by Murray [28], presents minimum temperatures for L ⇔ β and β ⇔ α phase transformations. In reference [26] the corresponding limiting intermetallic compounds ZrCr2 and TiCr2 are considered as line compounds and both capable of interchange the transition metal ( as in the hexagonal α and cubic β solid solutions ) forming ternary Laves compounds (Zr,Ti)Cr2 type. Lattice parameters for different compositions of (ZrxTi1-x)Cr2 are mentioned in [26] for alloys quenched from 800 and 1350 ºC. In order to study the Zr-Cr-Ti system, three alloys were elaborated with a composition lower than 67 at. % Cr and different Zr/Ti relationships, and another one richer than 67 at. % Cr with the purpose to know the equilibrium with the solid solution rich in chromium.
EXPERIMENTAL PROCEDURES
Materials Pure elements were used in order to manufacture the alloys. Zirconium 99.8 wt. % (1000 - 1100 ppm O, 500 - 600 ppm Fe ) of nuclear purity, zirconium from Oremet-Wah Chang 99.85 wt. % ( 420 ppm O, 105 - 170 ppm Fe ), titanium 99.9 % ( 400-500 ppm O, 400 - 500 ppm Fe ), chromium of at least 99.85 wt. % ( 50 ppm Fe as the main impurity ) and tin 99.999 wt. % were used.
Alloy Elaboration and Sample Conditionings The whole compositions of the studied alloys are listed on Table 1 and Table 2. They were elaborated in an arc-furnace with a copper chill under atmosphere of high purity argon (about 0.8 bar ). Buttons of about 15 g of each alloy were made by turning over the solid piece many times, at least four, for composition homogenization via successive remeltings without opening the furnace. Table 1. Composition of alloys of the Zr-Cr-Sn system ( zirconium balances 100 at. % ) Alloy ZCS1 ZCS2 ZCS3 ZCS4 ZCS5 ZCS6 ZCS7 ZCS8
Elements Cr ( at. % ) 6.6 5.4 3.5 2.0 1.2 0.5 4.0 15.0
Sn ( at. % ) 0.5 2.0 4.5 6.4 7.4 8.4 15.0 7.5
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Table 2. Composition of alloys of the Zr-Cr-Ti system ( zirconium balances 100 at. % ) Alloy ZCT1 ZCT2 ZCT3 ZCT4
Elements Cr ( at. % ) 40.0 40.0 40.0 82.0
Ti ( at. % ) 12.0 30.0 49.9 9.0
Specimens of each alloy, previously conditioned and wrapped in tantalum foils, were encapsulated in sealed quartz tubes with an argon atmosphere and heat treated 960 h at 860 ºC, 900 ºC, 960 ºC and 980 ºC for the Zr-Cr-Sn alloys and 800 h at 900 ºC and 1100 ºC for the Zr-Cr-Ti series. At the end of the treatments, the tubes were quenched in water without breakage. Samples of the alloys were suitably polished ( finished with diamond powder of 0.5 μm ) and, when necessary in order to reveal microstructures, etched by means of a water solution of HNO3 and HF ( 45:5:50 vol. % ) or glycerol solution of HNO3 and HF ( 45:5:50 vol. % ).
Measurement Techniques Three characterization techniques were employed in order to determine structures, lattice parameters and phase compositions: optical microscopy ( Olympus BX60M ), electron probe microanalysis in the electronic probe ( CAMECA SX50 ) and X-ray diffraction ( Philips PW3710 ). Phase compositions were determined by quantitative microanalysis ( EPMA ) with the electron microprobe equipment. Two ways to perform the microanalysis were implemented: a) on a number of convenient random points of a given massive phase, b) on many continuous points uniformly distributed, scanning across different phases. The last one is useful to delineate qualitatively the presence of small size phases and determine quasi quantitatively their compositions, by measuring the composition of many ( about 100 or 200 ) points aligned consecutively in 1 μm steps, see two examples in Figure 1. Quantitative composition microanalysis was performed under an accelerating potential of 20 kV. The equipment was recalibrated before each analysis session using pure 99.99 wt. % Zr, 99,999 wt. % Cr, 99.99 wt. % Sn and 99.999 wt. % Ti standards. All the elements were simultaneously analyzed. Characterization of phases in some selected interesting specimens was also performed from X-ray diffraction patterns ( XRD ) using monochromatic Cu Kα radiation in an X-ray equipment. Two examples of the evaluated diffractograms are shown in Figure 2. The first one for a cast bulk sample of the alloy Zr-Cr-Sn where βt and two intermetallic compounds are formed in freezing. βt means the crystal structure of the Zr rich hcp solid solution with the composition of the solute elements of β, phase which is the real stable phase at the temperature from where the quenching is performed. The second example corresponds to a sample of the system Zr-Cr-Ti where the equilibrium between the Cr rich solid solution and the cubic Laves phase is observed.
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Figure 1. Identified phases in Zr-Cr-Sn alloys after continuous path microanalysis. ( a )Tie lines between βZr and Zr4Sn and ( b ) three-phase equilibrium triangle between βZr, αZrCr2 and Zr4Sn.
Figure 2. ( a ) Analyzed diffractograms of the Zr-Cr-Sn as-cast Alloy ZCS8 where the volume percents of the solidified phases βt, ZrCr2 and Zr5Sn3 are calculated. ( b ) three heat treatment conditions of the Zr-Cr-Ti Alloy ZCT4 showing peaks only of αZrCr2 Laves phase, peaks of βZrCr2, indicated by the mark “?” are not found.
ABOUT THE ZR-CR-SN SYSTEM General This ternary system is composed by the limiting binary Zr-Cr, Zr-Sn and Cr-Sn systems. Schemes of the zones of interest in this study for both Zr-Cr and Zr-Sn diagrams, which include modifications in both Zr rich zones in order to take into account the new experimental results of González R.O. et al. [11] and Roberti. L [22] when they are compared to the assessed diagrams of Arias D. et al. [15] and Abriata J.P. et al. [17]. In Figure 3, the composition vs. temperature diagrams in the region of the experimental interest of this work are presented.
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Figure 3. Modified equilibrium values of the Zr-Cr ( a ) and Zr-Sn ( b ) systems in the Zr rich zone after [11] and [22]
These changes, related to the invariant transformations ( liquid and solid solution phase compositions in at. % ) are: In the Zr-Cr system, L( XCr = 26.5 ) ⇔ βZr( XCr = 4.7 ) + αZrCr2 at T = 1380 ºC (not drawn in Figure 3) instead of L( XCr = 22 ) ⇔ βZr( XCr = 8 ) + αZrCr2 at T = 1332 ºC
βZr( XCr = 1.3 ) ⇔ αZr( XCr ≤ 0.1 ) + αZrCr2 at T = 840 ºC instead of βZr( XCr = 1.65 ) ⇔ αZr( XCr ≤ 0.49 ) + αZrCr2 at T = 836 ºC In the Zr-Sn system, L( XSn = 19.4 ) ⇔ βZr( XSn = 16.2 ) + Zr5Sn3 at T > 1650 ºC (not drawn in Figure 3) instead of L( XSn = 19.1 ) ⇔ βZr( XSn = 17 ) + Zr5Sn3 at T = 1592 ºC
βZr( XSn = 12.2 ) + Zr5Sn3 ⇔ Zr4Sn at T = 1340 ºC instead of βZr( XSn = 11.8 ) + Zr5Sn3 ⇔ Zr4Sn at T = 1327 ºC βZr( XSn = 5.7 ) + Zr4Sn ⇔ αZr( XSn = 7.5 ) at T = 955 ºC instead of βZr( XSn = 4.9 ) + Zr4Sn⇔ αZr( XSn = 7.3 ) at T = 982 ºC All these modifications are necessary in order to discuss the present results of the ternary systems.
Liquidus Surface in the Zr Rich Zone Figure 4 shows typical or representative micrographs of the as-cast alloys. Three phases can be found according to the whole composition of the alloys. In Figure 4-a, ZCS2 Alloy, a typical Widmanstäten microstructure of the βt phase is present in the matrix and small ZrCr2 precipitates are in grain boundaries. In Figure 4-b, ZCS4 Alloy, the acicular type of βt is more developed and the faceted Zr5Sn3 compounds are visible. This intermetallic compound is in a
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greater amount in ZCS7 Alloy, Figure 4-c. Last Figure 4-d presents the microstructure of the three mentioned solidified phases, ZCS8 Alloy. Phases were also characterized via X-ray analysis on massive samples. Table 3 presents results of the analyzed diffractograms by the PCw software [29], where the volume percentages are also calculated in each case. These percentages can be only treated as estimative given the sample characteristics.
Figure 4. Micrographs of as-cast Alloys ZCS2 ( a ), ZCS4 ( b ), ZCS7 ( c ) and ZCS8 ( d ) showing the phases βt, αZrCr2 and Zr5Sn3 related to its own crystallization path ( without etching )
Table 3. Identified phases ( √ ) and volumetric percents (M major, i intermediate, m minor) after analysis of X-ray diffractograms in as-cast Zr-Cr-Sn alloys Alloy ZCS1 ZCS2 ZCS3 ZCS4 ZCS5 ZCS6 ZCS7 ZCS8
α ( βt ) √M √M √M √M √M √M √M √M
Phases αZrCr2 √m √m √m
Zr5Sn3 √m √m √m √m √m √i
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The above results, together with data from the binary systems Zr-Cr [11] and Zr-Sn [22], are used for drawing the schematic projection on the partial Gibbs diagram of the liquidus surface. In Figure 5, representative solidification paths of the studied alloys are included. Whole compositions of all the studied alloys are placed on the primary solidification surface of the βZr phase. Going down in temperature, the crystallization path of each alloy depends upon its concentration and the univariant valley it founds in its way.
Figure 5. Schematic projection of the liquidus surface in the Zr rich zone of the Zr-Cr-Sn system, and approximate representative crystallization paths of the studied alloys ( o )
The solidification paths of ZCS1 and ZCS2 begin with the precipitation of βZr and then, when the composition of the liquid reaches the univariant valley βZr – αZrCr2, βZr and αZrCr2 is formed up to the liquid extinction. Alloys ZCS3, ZCS4, ZCS5, ZCS6 and ZCS7 form firstly βZr and, when the liquid arrives to the composition of the univariant valley βZr – Zr5Sn3, these two phases precipitate up to the extinction of the liquid. Alloy ZCS8 precipitates, at first, the solid solution βZr, in a second step when the composition is on the univariant valley βZr – Zr5Sn3, Zr5Sn3 is added; the solidification finishes in the invariant eutectic point βZr – Zr5Sn3 –ZrCr2, adding ZrCr2 and going to the extinction of the liquid.
Phases in Equilibrium Optical micrographs of representative structures of phases in equilibrium of the studied alloys are presented in Figure 6.
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Figure 6. Microstructure of ZCS3 Alloy heat treated at 860 °C ( αZr + αZrCr2 ) (a) – ZCS4 Alloy heat treated at 960 °C ( βZr + αZrCr2 + Zr4Sn ) (b) – ZCS5 Alloy heat treated at 900 °C ( αZr + αZrCr2 + Zr4Sn ) (c) – ZCS2 Alloy heat treated at 900 °C ( αZr + βZr + αZrCr2 ) (d) - ZCS1 heat treated at 900 °C ( βZr + αZrCr2 ) (e) - ZCS6 heat treated at 980 °C ( βZr + Zr4Sn ) (f)
The solid solution αZr and small αZrCr2 precipitates in the ZCS3 Alloy treated at 860 °C are perceived in Figure 6-a. Alloy ZCS4 treated at 960 °C forms the solid solution βt and the compounds αZrCr2 and Zr4Sn like small and large precipitates respectively, Figure 6-b. Three phases are present in the microstructure of the ZCS5 Alloy treated at 900 °C, the solid solution αZr and the intermetallic compounds αZrCr2 and Zr4Sn in small and large amounts as it is shown in Figure 6-c. Figure 6-d presents the microstructure of the ZCS2 Alloy treated at 900°C where the two solid solutions αZr and βt together with the intermetallic compound αZrCr2 are visible. βZr matrix and αZrCr2 precipitates of ZCS1 Alloy after the 900 ºC treatment are observed in Figure 6-e. Figure 6-f shows βZr matrix grains and Zr4Sn precipitates in equilibrium at 980 ºC of ZCS6 Alloy.
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After ascertainment of compositions of the phases in equilibrium with the microprobe quantitative results, tie lines and triangle of conjugated compositions are determined. They are presented in Tables 4 – 7. In these tables, XZr balances 100 at. % and αZrCr2 and Zr4Sn are considered stoichiometric compounds i.e. having XCr = 66.7 at. % and XSn = 0 at. % and XSn = 20 at. % and XCr = 0 at. % respectively. Table 4. Conjugated compositions of phase in equilibrium at 860 ºC in the Zr-Cr-Sn system – Zirconium balances 100 % Compositions (at. % ) XCr XSn XCr XSn XCr XSn XCr XSn XCr XSn
Phases αZr 0.103 0.634 0.126 1.97 0.125 4.764 0.118 6.71 0.119 6.70
βZr
Additional phases in equilibrium
-
αZrCr2
-
αZrCr2
-
αZrCr2
-
αZrCr2
-
αZrCr2 Zr4Sn
Table 5. Conjugated compositions of phase in equilibrium at 900 ºC in the Zr-Cr-Sn system - Zirconium balances 100 % Compositions (at. % ) XCr XSn XCr XSn XCr XSn XCr XSn
Phases αZr
βZr 1.606 0.583 1.44 2.143
0.137 3.143 0.131 4.81 0.136 6.41
Additional phases in equilibrium αZrCr2 αZrCr2
-
αZrCr2
-
αZrCr2 Zr4Sn
Table 6. Conjugated compositions of phase in equilibrium at 960 ºC in the Zr-Cr-Sn system- Zirconium balances 100 % Compositions (at. % ) XCr XSn XCr XSn XCr XSn XCr XSn XCr XSn XCr XSn
Phases αZr
-
βZr 1.91 0.57 1.626 2.05 1.74 4.55 1.57 5.93 1.52 5.56 0.692 5.47
Additional phases in equilibrium αZrCr2 αZrCr2 αZrCr2 αZrCr2 Zr4Sn
Zr4Sn Zr4Sn
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Table 7. Conjugated compositions of phase in equilibrium at 980 ºC in the Zr-Cr-Sn system - Zirconium balances 100 % Compositions ( at. % ) XCr XSn XCr XSn XCr XSn XCr XSn XCr XSn XCr XSn
Phases
αZr -
βZr 2.13 0.55 1.98 2.15 1.91 4.78 1.724 6.06 1.33 6.19 0.585 5.784
Additional phases in equilibrium
αZrCr2 αZrCr2 αZrCr2 αZrCr2 Zr4Sn Zr4Sn Zr4Sn
Phase Boundaries Taking into account the above results and the phase boundaries in the limiting binary systems Zr-Cr and Zr-Sn, isothermal sections of the phase diagram of the Zr-Cr-Sn system at 860, 900, 960 and 980 ºC at the Zr rich corner are outlined in Figures 7-10. At 860 ºC small regions where βZr, βZr + αZr, βZr + αZrCr2 and αZr + βZr + αZrCr2 are stable can be drawn at low tin concentrations. A two-phase equilibrium αZr + αZrCr2 appears at higher tin concentrations and when XSn ≥ 6.71 at. %. A biphasic region αZr + ZrSn4 is stable at low chromium concentrations. Comparing with the boundaries proposed in [14] at 850 ºC, the more significant differences are placed in the βZr phase limits and the extensions of the composition domains where βZr, βZr + αZr, βZr +αZrCr2 and αZr + βZr + αZrCr2 are stable. At 900 ºC the βZr domain is now more extended and the αZr phase is not present for high Zr compositions. Biphasic equilibriums are stable between βZr - αZr, βZr - αZrCr2, αZr - αZrCr2 and αZr - Zr4Sn domains and two zones of triphasic equilibriums are found, βZr + αZr + αZrCr2 and αZr + Zr4Sn + αZrCr2. At 960 ºC an extended composition region of the βZr phase is found, and this phase forms equilibriums with αZrCr2 at relatively low tin concentrations, with Zr4Sn at relatively low chromium concentrations and with both αZrCr2 and Zr4Sn in an invariant triangle domain. In reference [14], at this temperature, equilibrium of phases αZr + βZr, αZr + βZr + αZrCr2, αZr + αZrCr2 are added at this isothermal section. At 980 ºC an isothermal section similar to that obtained for 960 ºC is perceived with an extended composition region of the βZr phase and equilibriums βZr + αZrCr2 and βZr + αZrCr2 + Zr4Sn. This section resembles the one proposed by Ivanov O.S. et al. [14] for the 1000 ºC section.
Equilibrium Phases in Zirconium Alloys of Concern to the Nuclear Industry
Figure 7. Isothermal section of the Zr-Cr-Sn ternary system at 860 ºC in the Zr rich corner superimposed with the tie lines ( x ) of the examined Alloys ZCS1 to ZCS6 ( o )
Figure 8. Isothermal section of the Zr-Cr-Sn ternary system at 900 ºC in the Zr rich corner superimposed with the tie lines ( x ) of the examined Alloys ZCS1 to ZCS6 ( o )
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Figure 9. Isothermal section of the Zr-Cr-Sn ternary system at 960 ºC in the Zr rich corner superimposed with the tie lines ( x ) of the examined Alloys ZCS1 to ZCS6 ( o )
Figure 10. Isothermal section of the Zr-Cr-Sn ternary system at 980 ºC in the Zr rich corner superimposed with the tie lines ( x ) of the examined Alloys ZCS1 to ZCS6 ( o )
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Solid Phase Transformations – Projection of Solid Transformation Valleys Considering results of the equilibriums of phases the hypothetical solvus projection of the Zr rich zone in Figure 11 can be proposed. Here, the possible invariant quasi-peritectoid type transformation would be: βZr + Zr5Sn3 ⇔ Zr4Sn + αZrCr2 at 960 ºC < T combining the invariant transformations βZr + Zr5Sn3 ⇔ αZrCr2 and βZr + Zr5Sn3 ⇔ Zr4Sn. At lowest temperatures but higher than ∼ 900 ºC an invariant peritectic transformation, which begins at 955 ºC and XZrβ = 94.3 in the binary Zr-Cr, βZr + Zr4Sn ⇔ αZrCr2 is found. In reference [14] this valley begins in the binary Zr-Cr at T > 970 ºC and XSnβ ~ 6.2 at. %. The next invariant quasi-peritectoid type transformation would be: βZr + Zr4Sn ⇔ αZr + αZrCr2 at 900 ºC < T < 955 ºC and Xcrβ ~ 1.5 , XSnβ~ 4.5 at. % arising from the invariant βZr + Zr4Sn ⇔ αZr and βZr + Zr4Sn ⇔ αZrCr2 transformations.
Figure 11. Projected space diagram in the zirconium rich zone of the Zr-Cr-Sn system - Tentative projection of valleys of solid transformations from βZr phase - Different variance transformations are indicated – ( o ) indicates alloy compositions of this study
The invariant point in the proposed projection of the liquidus in [14] where the transformation is βZr + Zr4Sn ⇔ αZrCr2 + αZr occurs at 970 ºC and at 6.5 at. % Sn and 2.2 at. % Cr. After that, a univariant eutectic transformation takes place βZr ⇔ αZr + αZrCr2 ending to the eutectic transformation at T = 840 ºC and Xcrβ ~ 1.3 in the binary system Zr-Cr. In [14] the end of this valley in the binary Zr-Cr is at XCrβ ~ 3.1 at. %.
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ABOUT THE ZR-CR-TI SYSTEM General This system is composed by the binary Zr-Cr, Cr-Ti and Zr-Ti systems. The Cr-Ti and Zr-Ti phase diagrams here considered for the posterior discussion were both assessed by Murray J.L. and compiled in a Monograph Series on Alloy Phase Diagrams for Titanium Alloys [28]. In this chapter the results of reference [11] for the Zr rich and data of reference [15] for the Cr rich zone of the phase diagram Zr-Cr are used.
Liquidus surface The liquidus surface can be imagined containing a minimum congruent solidification temperature valley L ⇒ β(Zr,Ti) being β(Zr,Ti) the representation of the bcc solid solution with different compositions beginning in the Zr-Ti binary system and splitting in two similar valleys, one of them arriving to the Cr-Ti system.
Figure 12. Tentative liquidus surface of the Zr-Cr-Ti system – dashed lines indicate congruent solidification points of the transformation L ⇒ β type
The second one most probably transforms itself in the eutectic valley L ⇒ β(Zr,Ti) + γ(Zr,Ti)Cr2 which arrives to the binary Zr-Cr system. Other eutectic valley which begins in the Zr-Cr system at the chromium rich side L ⇒ βCr + γ(Zr,Ti)Cr2 joins somewhere the congruent liquid-solid valley which ends in the Cr-Ti binary system (see Figure 12).
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Phases in Equilibrium Figure 13 (a) and Figure 13 (b) show typical microstructures of the Zr-Ti-Cr alloys where the β(Zr,Ti) solid solution and the intermetallic α(Zr,Ti)Cr2 are found.
Figure 13. Microstructures of heat treated specimens without etching. (a) ZCT2 Alloy at 1100 ºC, β(Zr,Ti) gray matrix and α(Zr,Ti)Cr2 clear grains. (b) ZCT4 Alloy at 900 ºC, βCr(Ti) dendrites and Laves phase in the interdendritic spaces.
The compositions of the conjugated phases in equilibrium in each alloy and at the two temperatures 900 and 1100 ºC are shown in Tables 8 and 9. Table 8. Conjugated compositions of phase in equilibrium at 900 ºC in the Zr-Cr-Ti system – Zirconium balances 100 % - * indicates βt Compositions at. % XCr XTi XCr XTi XCr XTi XCr XTi
β(Zr,Ti) 1.8 * 20.0 * 4.5 56.1 11.7 77.9
-
Phases α(Zr,Ti)Cr2 60.4 9.3 60.2 17.3 62.4 27.6 66.4 18.1
βCr(Ti)
93.0 6.9
Table 9. Conjugated compositions of phase in equilibrium at 1100 ºC in the Zr-Cr-Ti system – Zirconium balances 100 % - ( * ) indicates βt Compositions at. % XCr XTi XCr XTi XCr XTi XCr XTi
β(Zr,Ti) 0.7* 17.8* 2.3 53.3 11.5 80.9
-
Phases α(Zr,Ti)Cr2 64.2 7.3 62.5 14.3 65.4 28.7 66.1 14.1
βCr(Ti)
93.8 6.1
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Phase Boundaries Taking into account the above results and the boundaries in the limiting binary systems, isothermal sections of the phase diagram of the Zr-Cr-Ti system at 900 and 1100 ºC are presented in Figure 14 and Figure15.
Figure 14. Isothermal section of the phase diagram of the Zr-Ti-Cr system at 900 ºC. Studied alloys are included.
Figure 15. Isothermal section of the phase diagram of the Zr-Ti-Cr system at 1100 ºC. Studied alloys are included.
Equilibrium Phases in Zirconium Alloys of Concern to the Nuclear Industry
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CRYSTAL LATTICES β(Zr,Ti) Phase As it was reported in [30] the characterization of the bcc phase is related to the concentration of the alloy. In ZCT1 alloy, at room temperature, only βt ( hcp ) is observed. In ZCT2 and ZCT3 alloys the characterized structure is retained β(Zr,Ti). The variation of lattice parameter of the β(Zr,Ti) phase in the Zr-Ti system with the atomic concentration , following [30] may be regarded as linear. The straight line drawn trough the parameters of the cubic β(Zr,Ti) phase extrapolates to 3.27 Å for Ti and 3.58 Å for Zr [31] even if thermal expansion corrections were not made for both metals these values could be compared quantitatively with those measured around 900 ºC. The straight line for the lattice parameters of the cubic phase characterized as retained β(Zr,Ti) in quenching from 980 ºC can be represented by a = 0.0327 + 0.0031 XZr ( Å ) where XZr is the atomic percentage of zirconium. For the Ti/Ti+Zr composition ratios of the β(Zr,Ti) solid solution in equilibrium with the αZrCr2 in alloys ZCT2 and ZCT3 ( 58.7 %, and 88.2 % ) the lattice parameter a would be: 3.43 and 3.305 Å respectively. Figure 16 shows experimental results together with determined values in [30] and those of the pure elements [31]. It can be observed that a better accordance of the parameter results for the β(Zr,Ti) with 56.1 at. % Ti and 4.5 at. % Cr, Alloy ZCT2, in contrast with β(Zr,Ti) with 77.9 at. % Ti and 11.7 at.% Cr, Alloy ZCT3 ( see Table 8 ). This difference can be explained by the influence of the chromium composition in solution following Figure 6 of quotation [28].
Figure 16. Lattice parameter a as function of the Zr and Ti of the β phase in the ternary system – ( ○ ) Duwez et al. [30], ( ∆ ) pure elements [31], ( • ) measured in this study
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Laves Phase In Figure 17 the experimental determinations of Kornilov et al. are shown together with the present results. Samples in [26] were of a stoichiometric AB2 compound where A represents the partial or totally substituted transition elements (Zr,Ti) and B is the chromium element. In ZCT1 and ZCT2 alloys the identified Laves phase was the cubic α(Zr,Ti)Cr2, and the lattice parameters are slightly higher ( about 2 % ) than those published.
Figure 17. Lattice parameter of the Laves phase function of the Ti/Ti+Zr % composition - ( Kornilov et al. [30], ( • ) measured in this study
)
On the other hand, the lattice parameter for the Laves phase in Alloy ZCT2 with 62.5 at. % Cr which is in equilibrium with the β(Zr,Ti) phase is 7.20 Å; for the Laves phase in Alloy ZCT4 with 66.1 at. % Cr which is in equilibrium with the βCr(Ti), is 7.06 Å. This decrement of the parameter increasing the chromium content was observed in the ZrCr2 [32] [15].
CONCLUSION − − − − −
In this chapter experimental results about the Zr-Cr-Sn and Zr-Cr-Ti systems were exposed. Tie lines and conjugated compositions in biphasic and triphasic equilibriums were determined. Phase boundaries in isothermal sections of the equilibrium diagrams at different temperatures were drawn. Projections of the liquidus surface with hypothetical transformation lines of this phase were sketched. A tentative projection of the valleys of the solid transformations from βZr phase in the Zr-Cr-Sn system in the Zr rich zone was proposed.
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Other properties of the phases, as the lattice parameters of the β(Zr,Ti) solid solution and α(Zr,Ti)Cr2 compound, were calculated.
ACKNOWLEDGMENTS Financial support from Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET, PIP 5062 ) and Comisión Nacional de Energía Atómica (CNEA, P5-PID-35-2) are gratefully acknowledged.
REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14]
[15] [16] [17] [18]
[19] [20] [21] [22]
[23]
Aricó S.; Gribaudo L.; Roberti L. J. Mater. Sci. 1996, 31, 5587-5597. Aricó S.; Gribaudo L. Scr. Mater. 1999, 41, 159-165. Canay M.; Arias D. An. Asoc. Qca. Arg. 1996, 84, 343-347. Canay M.; Arias D. An. Asoc. Fis. Arg. 1997, 9, 280-283. Aricó S.; Gribaudo L. J. Alloys Compd. 2000, 306, 245-248. Aricó S.; Gribaudo L. J. Nucl. Mater. 2001, 288, 217-221. Canay M.; Danón A.; Arias D. J. Nucl. Mater. 2000, 280, 365-371. Nieva N., Arias D. J. Nucl. Mater. 2000, 277, 120-122. Granovsky M.S.; Canay M.; Lena E.; Arias D. J. Nucl. Mater. 2002, 302, 1-8. Ramos C.; Saragovi C.; Arias D.; Granovsky M. An. Soc. Arg. Mat. 2003, 327-329. González R.; Gribaudo L. J. Nucl. Mater. 2005, 342, 14-19. Ruiz D.; Monti A.; Ortiz Albuixech M.; Gribaudo L. J. Nucl. Mater. 2006, 348, 45-50. Gribaudo L. An. Asoc. Qca. Arg. 1996, 84, 359-362. Ivanov O.S.; Adamova A.S.; Tarataeva E.M.; Tregubov I.A. Zirconium Alloys Structures; Edition Scientific, AN SSSR, Moscow, RUSSIA, 1973; pp 71-72 (Zr-CrSn), pp 85-86 (Zr-Cr-Ti) Arias D.; Abriata J.P. Bull. Alloy Phase Diagrams 1986, 7, 237-243. Venkatraman M.; Neuman J.P. Bull. Alloy Phase Diagrams 1988, 9, 2, 159-162. Abriata J.P.; Bolcich J.C.; Arias D. Bull. Alloy Phase Diagrams 1983, 4, 147-154. Massalski T.B.; H. Okamoto H.; Subramanian P.R.; Kacprzak L. Binary alloy phase diagrams; ASM International, Metals Park, Third printing, OH, 1996; pp1335, 13371338 ( Cr-Sn ), pp 1359-1360 ( Cr-Zr ), pp 3416, 3418-3419 (Sn-Zr), pp 1345, 13471348 ( Cr-Ti ), pp 3502-3503 (Ti-Zr) Zeng K.; Hämäläinen M.; Luoma R. Z. Metallkd. 1993, 84, 23-28. Pérez R.J.; Sundman B. Calphad J. 2001, 25, 59-66. Dupin N.; Ansara I.; Servant C.; Toffolon C.; Lemaignan C.; Bracket J.C. J. Nucl. Mater. 1999, 275, 287-295. Roberti, L. Sistema Circonio-Estaño – Diagrama de Fases y Transformaciones Asociadas; PhD Thesis, FCEyN, Universidad Nacional de Buenos Aires, ARGENTINA 1992. Kornilov I.I.; Belousov O.K.; Musayev R.S. Izv. Akad. Nauk SSSR, Met., 2, 1967, 201 in Russian (English abstract in Russ. Metall., 1967, 2, 108-109)
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[24] Kornilov I.I.; Belousov O.K.; Musayev R.S. Russ. Metall. (abridged english translation), 1969, 135-137. [25] Kornilov I.I.; Budberg P.B.; Shakhova K.I. Dokl. Akad. N SSSR, 161, 6, 1965, 13781381 ( in Russian ) [26] Murray J.L. Bull. Alloy Phase Diagrams 2, 2, 1981, 174-181. [27] Murray J.L. Phase Diagrams of Binary Titanium Alloys; ASM International: Metals Park, OH, 1987; pp 68-77 (Cr-Ti), pp 340-345 (Ti-Zr) [28] Tanner L.E.; Levinson D.W. Trans. ASM, 52, 1960, 1115-1136. [29] Kraus W.; Nolze G.; Müller U. ( 2000 ). PowderCell 2.3. - Pulverdiffraktogramme aus Einkristalldaten und Anpassung experimenteller Beugungsaufnahmen. http://www.bam.de/de/service/publikationen/powder_cell_a.htm [30] Duwez P. J. Inst. Met. 1951-52, 80, 525-527. [31] Villars P., Calvert L.D. Pearson’s Handbook of Crystallographic Data for Intermetallic Phases, ASM International: Metals Park, 2nd. Edition, OH, 1991, p 5366 (βZr), p 5338 (βTi ), p 2759 ( αZrCr2 ), pp 2754-2755 (αTiCr2) [32] Pet’kov V.V.; Prima S.B.; Tret’yachenko L.A.; Kocherzhinskii Metallofiz.,46, 80, 1973, 80 (in Russian)
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 915-937
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 31
NUCLEAR NONPROLIFERATION: IAEA SAFEGUARDS AND OTHER MEASURES TO HALT THE SPREAD OF NUCLEAR WEAPONS AND MATERIAL* Gene Aloise WHY GAO DID THIS STUDY The International Atomic Energy Agency’s (IAEA) safeguards system has been a cornerstone of U.S. efforts to prevent nuclear weapons proliferation since the Treaty on the Non-Proliferation of Nuclear Weapons (NPT) was adopted in 1970. Safeguards allow IAEA to verify countries’ compliance with the NPT. Since the discovery in 1991 of a clandestine nuclear weapons program in Iraq, IAEA has strengthened its safeguards system. In addition to IAEA’s strengthened safeguards program, there are other U.S. and international efforts that have helped stem the spread of nuclear materials and technology that could be used for nuclear weapons programs. This testimony is based on the U.S. Government Accountability Office’s (GAO’s) report on IAEA safeguards issued in October 2005 (Nuclear Nonproliferation: IAEA Has Strengthened Its Safeguards and Nuclear Security Programs, but Weaknesses Need to Be Addressed, GAO-06-93 [Washington, D.C.: Oct. 7, 2005]). This testimony is also based on previous GAO work related to the Nuclear Suppliers Group—a group of more than 40 countries that have pledged to limit trade in nuclear materials, equipment, and technology to only countries that are engaged in peaceful nuclear activities— and U.S. assistance to Russia and other countries of the former Soviet Union for the destruction, protection, and detection of nuclear material and weapons. www.gao.gov/cgibin/getrpt?GAO-06-1128T. To view the full product, including the scope and methodology, click on the link above. For more information, contact Gene Aloise at (202) 512-3841 or
[email protected].
*
A version of this chapter was also published in Nuclear Energy Research Progress edited by Veda B. Durelle published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research.
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WHAT GAO FOUND IAEA has taken steps to strengthen safeguards, including conducting more intrusive inspections, to seek assurances that countries are not developing clandestine weapons programs. IAEA has begun to develop the capability to independently evaluate all aspects of a country’s nuclear activities. This is a radical departure from the past practice of only verifying the peaceful use of a country’s declared nuclear material. However, despite successes in uncovering some countries’ undeclared nuclear activities, safeguards experts cautioned that a determined country can still conceal a nuclear weapons program. In addition, there are a number of weaknesses that limit IAEA’s ability to implement strengthened safeguards. First, IAEA has a limited ability to assess the nuclear activities of 4 key countries that are not NPT members—India, Israel, North Korea, and Pakistan. Second, more than half of the NPT signatories have not yet brought the Additional Protocol, which is designed to give IAEA new authority to search for clandestine nuclear activities, into force. Third, safeguards are significantly limited or not applied to about 60 percent of NPT signatories because they possess small quantities of nuclear material, and are exempt from inspections, or they have not concluded a comprehensive safeguards agreement. Finally, IAEA faces a looming human capital crisis caused by the large number of inspectors and safeguards management personnel expected to retire in the next 5 years. In addition to IAEA’s strengthened safeguards program, there are other U.S. and international efforts that have helped stem the spread of nuclear materials and technology. The Nuclear Suppliers Group has helped to constrain trade in nuclear material and technology that could be used to develop nuclear weapons. However, there are a number of weaknesses that could limit the Nuclear Suppliers Group’s ability to curb proliferation. For example, members of the Suppliers Group do not always share information about licenses they have approved or denied for the sale of controversial items to nonmember states. Without this shared information, a member country could inadvertently license a controversial item to a country that has already been denied a license from another member state. Since the early 1990s, U.S. nonproliferation programs have helped Russia and other former Soviet countries to, among other things, secure nuclear material and warheads, detect illicitly trafficked nuclear material, and eliminate excess stockpiles of weapons-usable nuclear material. However, these programs face a number of challenges which could compromise their ongoing effectiveness. For example, a lack of access to many sites in Russia’s nuclear weapons complex has significantly impeded the Department of Energy’s progress in helping Russia secure its nuclear material. U.S. radiation detection assistance efforts also face challenges, including corruption of some foreign border security officials, technical limitations of some radiation detection equipment, and inadequate maintenance of some equipment.
Mr. Chairman and Members of the Subcommittee: I am pleased to be here today to discuss the International Atomic Energy Agency’s (IAEA) safeguards program and other measures to halt the spread of nuclear weapons and material. Revelations about the clandestine nuclear programs of North Korea, Iran, and Libya,
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as well as clandestine nuclear trafficking networks, have significantly increased international concerns about the spread of weapons of mass destruction. Since the Treaty on the NonProliferation of Nuclear Weapons (NPT) came into force in 1970, IAEA’s safeguards system has been a cornerstone of U.S. and international efforts to prevent nuclear weapons proliferation. The NPT expanded IAEA’s original inspection responsibilities by requiring signatory non-nuclear weapons states—countries that had not manufactured and detonated a nuclear device before January 1, 1967—to agree not to acquire nuclear weapons and to accept IAEA safeguards on all nuclear material used in peaceful activities.1 Most countries have negotiated an agreement with IAEA, known as a comprehensive safeguards agreement. Safeguards allow the agency to independently verify that non-nuclear weapons states that signed the NPT are complying with its requirements. Under the safeguards system, IAEA, among other things, inspects all facilities and locations containing nuclear material, as declared by each country, to verify its peaceful use. However, the discovery in 1991 of a clandestine nuclear weapons program in Iraq confirmed the need for a broader and more effective approach to safeguards. As a result, IAEA began to strengthen its safeguards system in the mid-1990s to provide assurance that non-nuclear weapons states were not engaged in undeclared nuclear activities. In addition to IAEA’s strengthened safeguards program, other U.S. and international efforts to prevent nuclear weapons proliferation have included the Nuclear Supplier’s Group—a group of more than 40 countries that have pledged to limit trade in nuclear materials, equipment, and technology to only countries that are engaged in peaceful nuclear activities—and U.S. assistance to Russia and other states of the former Soviet Union to, among other things, secure nuclear material and warheads. My remarks will focus on our report on IAEA safeguards issued in October 2005.2 I will also address issues related to previous GAO work on the Nuclear Suppliers Group’s restrictions on nuclear trade3 and U.S. assistance to Russia and other countries of the former Soviet Union for the destruction, protection, and detection of nuclear weapons and material.
SUMMARY IAEA has taken steps to strengthen safeguards by more aggressively seeking assurances that countries have not engaged in clandestine nuclear activities, but the agency still cannot be certain that countries are not developing secret weapons programs. In a radical departure from the past practice of only verifying the peaceful use of a country’s declared nuclear material at declared facilities, IAEA has begun to develop the capability to independently evaluate all aspects of a country’s nuclear activities by, among other things, conducting more intrusive inspections and collecting and analyzing environmental samples to detect traces of nuclear material at facilities and other locations. Department of State and IAEA officials told us that IAEA’s strengthened safeguards measures have successfully revealed previously undisclosed nuclear activities in Iran, South Korea, and Egypt. In the case of Iran, IAEA and Department of State officials noted that strengthened safeguards measures, such as collecting and analyzing environmental samples, helped the agency verify some of Iran’s nuclear activities. The measures also allowed IAEA to conclude in September 2005 that Iran was not complying with its safeguards obligations because it failed to report all of its nuclear activities to IAEA. As a result, in July 2006, Iran was referred to the U.N. Security Council, which in turn
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demanded that Iran suspend its uranium enrichment activities or face possible diplomatic and economic sanctions. Despite these successes, a group of safeguards experts recently cautioned that a determined country can still conceal a nuclear weapons program. For example, IAEA does not have unfettered inspection rights and cannot make visits to suspected sites anywhere at any time. There are a number of weaknesses that hamper IAEA’s ability to effectively implement strengthened safeguards. First, IAEA has a limited ability to assess the nuclear activities of 4 key countries that are not NPT members—India, Israel, North Korea, and Pakistan. Second, more than half, or 111 out of 189, of the NPT signatories have not yet brought the Additional Protocol into force, including the United States. A third weakness in implementing strengthened safeguards is that safeguards are significantly limited or not applied in about 60 percent, or 112 out of 189, of the NPT signatory countries—either because they have an agreement (known as a small quantities protocol) with IAEA, and are not subject to most safeguards measures, or because they have not concluded a comprehensive safeguards agreement with IAEA. IAEA cannot verify that these countries are not diverting nuclear material for nonpeaceful purposes or engaging in secret nuclear activities. Fourth, while IAEA is increasingly relying on the analytical skills of its staff to detect countries’ undeclared nuclear activities, the agency is facing a looming human capital crisis. In the next 5 years, IAEA will experience a large turnover of senior safeguards inspectors and high-level management officials. Delays in filling critical safeguards positions limit IAEA’s ability to implement strengthened safeguards. In addition to IAEA’s strengthened safeguards program, there are other U.S. and international efforts that have helped stem the spread of nuclear materials and technology. The Nuclear Suppliers Group has helped to constrain the trade in nuclear material and technology that could be used to develop nuclear weapons. There are currently 45 countries that participate in this voluntary, nonbinding regime and they have pledged to limit trade in nuclear materials, equipment, and technology to only countries that are engaged in peaceful nuclear activities. The Nuclear Suppliers Group has also helped IAEA verify compliance with the NPT. For example, it helped convince Argentina and Brazil to place their nuclear programs under IAEA safeguards in exchange for international cooperation to enhance their nuclear programs for peaceful purposes. Since 1992, the Nuclear Suppliers Group has required that other countries have comprehensive safeguards agreements with IAEA as a condition of supply for nuclear-related items. Despite these benefits, there are a number of weaknesses that could limit the Nuclear Suppliers Group’s ability to curb proliferation. We found that members of the Nuclear Suppliers Group do not always share information about licenses they have approved or denied for the sale of controversial items to nonmember states. Without this shared information, a member country could inadvertently license a controversial item to a country that has already been denied a license from another Nuclear Suppliers Group member state. We also found that Nuclear Suppliers Group members did not promptly review and agree upon common lists of items to control and approaches to controlling them. Without this agreement, sensitive items may still be traded to countries of concern. Since the early 1990s, U.S. nonproliferation programs have helped Russia and other former Soviet countries secure nuclear material and warheads, detect illicitly trafficked nuclear material, eliminate excess stockpiles of weapons-usable nuclear material,4 and halt the continued production of weapons-grade plutonium.5 While these programs have had some
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successes, they also face a number of challenges which could compromise their ongoing effectiveness. For example, a lack of access to many sites in Russia’s nuclear weapons complex has significantly impeded the Department of Energy’s (DOE) progress in helping Russia secure its nuclear material. We reported in 2003 that DOE had completed work at only a limited number of buildings in Russia’s nuclear weapons complex, a network of sites involved in the construction of nuclear weapons where most of the nuclear material in Russia is stored. While DOE has reported progress on gaining access to many of these sites, we are currently reexamining DOE’s efforts in this area and the challenges the agency faces in completing its program. Furthermore, to combat nuclear smuggling, since 1994, the Departments of Energy, Defense, and State have provided radiation detection equipment to 36 countries, including many countries of the former Soviet Union. However, as we reported in March 2006, U.S. radiation detection assistance efforts also face challenges, including corruption of some foreign border security officials, technical limitations of some radiation detection equipment, and inadequate maintenance of some equipment.
BACKGROUND IAEA is an independent organization affiliated with the United Nations. Its governing bodies include the General Conference, composed of representatives of the 138 IAEA member states, and the 35-member Board of Governors, which provides overall policy direction and oversight. The Secretariat, headed by the Director General, is responsible for implementing the policies and programs of the General Conference and Board of Governors. The United States is a permanent member of the Board of Governors. IAEA derives its authority to establish and administer safeguards from its statute, the Treaty on the Non-proliferation of Nuclear Weapons and regional nonproliferation treaties, bilateral commitments between states, and project agreements with states.6 Since the NPT came into force in 1970, it has been subject to review by signatory states every 5 years. The 1995 NPT Review and Extension conference extended the life of the treaty indefinitely, and the latest review conference occurred in May 2005. Article III of the NPT binds each of the treaty’s 184 signatory states that had not manufactured and exploded a nuclear device prior to January 1, 1967 (referred to in the treaty as non-nuclear weapon states) to conclude an agreement with IAEA that applies safeguards to all source and special nuclear material in all peaceful nuclear activities within the state’s territory, under its jurisdiction, or carried out anywhere under its control.7 The five nuclear weapons states that are parties to the NPT—China, France, the Russian Federation, the United Kingdom, and the United States—are not obligated by the NPT to accept IAEA safeguards. However, each nuclear weapons state has voluntarily entered into legally binding safeguards agreements with IAEA, and has submitted designated nuclear materials and facilities to IAEA safeguards to demonstrate to the nonnuclear weapon states their willingness to share in the administrative and commercial costs of safeguards. (App. I lists states that are subject to safeguards, as of August 2006.) India, Israel, and Pakistan are not parties to the NPT or other regional nonproliferation treaties. India and Pakistan are known to have nuclear weapons programs and to have detonated several nuclear devices during May 1998. Israel is also believed to have produced nuclear weapons. Additionally, North Korea joined the NPT in 1985 and briefly accepted
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safeguards in 1992 and 1993, but expelled inspectors and threatened to withdraw from the NPT when IAEA inspections uncovered evidence of undeclared plutonium production. North Korea announced its withdrawal from the NPT in early 2003, which under the terms of the treaty, terminated its comprehensive safeguards agreement. IAEA’s safeguards objectives, as traditionally applied under comprehensive safeguards agreements, are to account for the amount of a specific type of material necessary to produce a nuclear weapon, and the time it would take a state to divert this material from peaceful use and produce a nuclear weapon. IAEA attempts to meet these objectives by using a set of activities by which it seeks to verify that nuclear material subject to safeguards is not diverted to nuclear weapons or other proscribed purposes. For example, IAEA inspectors visit a facility at certain intervals to ensure that any diversion of nuclear material is detected before a state has had time to produce a nuclear weapon. IAEA also uses material-accounting measures to verify quantities of nuclear material declared to the agency and any changes in the quantities over time. Additionally, containment measures are used to control access to and the movement of nuclear material. Finally, IAEA deploys surveillance devices, such as video cameras, to detect the movements of nuclear material and discourage tampering with IAEA’s containment measures. The Nuclear Suppliers Group was established in 1975 after India tested a nuclear explosive device. In 1978, the Suppliers Group published its first set of guidelines governing the exports of nuclear materials and equipment. These guidelines established several requirements for Suppliers Group members, including the acceptance of IAEA safeguards at facilities using controlled nuclear-related items. In 1992, the Suppliers Group broadened its guidelines by requiring countries receiving nuclear exports to agree to IAEA’s safeguards as a condition of supply. As of August 2006, the Nuclear Suppliers Group had 45 members, including the United States. (See app. II for a list of signatory countries.)
IAEA HAS STRENGTHENED ITS SAFEGUARDS PROGRAM, BUT WEAKNESSES NEED TO BE ADDRESSED IAEA has taken steps to strengthen safeguards by more aggressively seeking assurances that a country is not pursuing a clandestine nuclear program. In a radical departure from past practices of only verifying the peaceful use of a country’s declared nuclear material at declared facilities, IAEA has begun to develop the capability to independently evaluate all aspects of a country’s nuclear activities. The first strengthened safeguards steps, which began in the early 1990s, increased the agency’s ability to monitor declared and undeclared activities at nuclear facilities. These measures were implemented under the agency’s existing legal authority under comprehensive safeguards agreements and include (1) conducting short notice and unannounced inspections, (2) collecting and analyzing environmental samples to detect traces of nuclear material, and (3) using measurement and surveillance systems that operate unattended and can be used to transmit data about the status of nuclear materials directly to IAEA headquarters. The second series of steps began in 1997 when IAEA’s Board of Governors approved the Additional Protocol.8 Under the Additional Protocol, IAEA has the right, among other things, to (1) receive more comprehensive information about a country’s nuclear activities, such as
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research and development activities, and (2) conduct “complementary access,” which enables IAEA to expand its inspection rights for the purpose of ensuring the absence of undeclared nuclear material and activities. Because the Additional Protocol broadens IAEA’s authority and the requirements on countries under existing safeguards agreements, each country must take certain actions to bring it into force. For each country with a safeguards agreement, IAEA independently evaluates all information available about the country’s nuclear activities and draws conclusions regarding a country’s compliance with its safeguards commitments. A major source of information available to the agency is data submitted by countries to IAEA under their safeguards agreements, referred to as state declarations. Countries are required to provide an expanded declaration of their nuclear activities within 180 days of bringing the Additional Protocol into force. Examples of information provided in an Additional Protocol declaration include the manufacturing of key nuclear-related equipment; research and development activities related to the nuclear fuel cycle; the use and contents of buildings on a nuclear site; and the location and operational status of uranium mines. The agency uses the state declarations as a starting point to determine if the information provided by the country is consistent and accurate with all other information available based on its own review. IAEA uses various types of information to verify the state declaration. Inspections of nuclear facilities and other locations with nuclear material are the cornerstone of the agency’s data collection efforts. Under the Additional Protocol, IAEA has the authority to conduct complementary access at any place on a site or other location with nuclear material in order to ensure the absence of undeclared nuclear material and activities, confirm the decommissioned status of facilities where nuclear material was used or stored, and resolve questions or inconsistencies related to the correctness and completeness of the information provided by a country on activities at other declared or undeclared locations. During complementary access, IAEA inspectors may carry out a number of activities, including (1) making visual observations, (2) collecting environmental samples, (3) using radiation detection equipment and measurement devices, and (4) applying seals. In 2004, IAEA conducted 124 complementary access in 27 countries. In addition to its verification activities, IAEA uses other sources of information to evaluate countries’ declarations. These sources include information from the agency’s internal databases, open sources, satellite imagery, and outside groups. The agency established two new offices within the Department of Safeguards to focus primarily on open source and satellite imagery data collection. Analysts use Internet searches to acquire information generally available to the public from open sources, such as scientific literature, trade and export publications, commercial companies, and the news media. In addition, the agency uses commercially available satellite imagery to supplement the information it receives through its open source information. Satellite imagery is used to monitor the status and condition of declared nuclear facilities and verify state declarations of certain sites. The agency also uses its own databases, such as those for nuclear safety, nuclear waste, and technical cooperation, to expand its general knowledge about countries’ nuclear and nuclearrelated activities. In some cases, IAEA receives information from third parties, including other countries.
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IAEA Has Taken Steps to Strengthen Safeguards, but Detection of Clandestine Nuclear Weapons Programs Is Not Assured Department of State and IAEA officials told us that strengthened safeguards measures have successfully revealed previously undisclosed nuclear activities in Iran, South Korea, and Egypt. Specifically,
•
•
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IAEA and Department of State officials noted that strengthened safeguards measures, such as collecting and analyzing environmental samples, helped the agency verify some of Iran’s nuclear activities. The measures also allowed IAEA to conclude in September 2005 that Iran was not complying with its safeguards obligations because it failed to report all of its nuclear activities to IAEA. As a result, in July 2006, Iran was referred to the U.N. Security Council, which in turn demanded that Iran suspend its uranium enrichment activities or face possible diplomatic and economic sanctions. In August 2004, as a result of preparations to submit its initial declaration under the Additional Protocol, South Korea notified IAEA that it had not previously disclosed nuclear experiments involving the enrichment of uranium and plutonium separation. IAEA sent a team of inspectors to South Korea to investigate this case. In November 2004, IAEA’s Director General reported to the Board of Governors that although the quantities of nuclear material involved were not significant, the nature of the activities and South Korea’s failure to report these activities in a timely manner posed a serious concern. IAEA is continuing to verify the correctness and completeness of South Korea’s declarations. IAEA inspectors have investigated evidence of past undeclared nuclear activities in Egypt based on the agency’s review of open source information that had been published by current and former Egyptian nuclear officials. Specifically, in late 2004, the agency found evidence that Egypt had engaged in undeclared activities at least 20 years ago by using small amounts of nuclear material to conduct experiments related to producing plutonium and highly enriched uranium. In January 2005, the Egyptian government announced that it was fully cooperating with IAEA and that the matter was limited in scope. IAEA inspectors have made several visits to Egypt to investigate this matter. IAEA’s Secretariat reported these activities to its Board of Governors.
Despite these successes, a group of safeguards experts recently cautioned that a determined country can still conceal a nuclear weapons program. IAEA faces a number of limitations that impact its ability to draw conclusions—with absolute assurance—about whether a country is developing a clandestine nuclear weapons program. For example, IAEA does not have unfettered inspection rights and cannot make visits to suspected sites anywhere at any time. According to the Additional Protocol, complementary access to resolve questions related to the correctness and completeness of the information provided by the country or to resolve inconsistencies must usually be arranged with at least 24-hours advanced notice. Complementary access to buildings on sites where IAEA inspectors are already present are usually conducted with a 2-hour advanced notice. Furthermore, IAEA officials told us that there are practical problems that restrict access. For example, inspectors must be issued a visa
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to visit certain countries, a process which cannot normally be completed in less than 24 hours. In some cases, nuclear sites are in remote locations and IAEA inspectors need to make travel arrangements, such as helicopter transportation, in advance, which requires that the country be notified prior to the visit. A November 2004 study by a group of safeguards experts appointed by IAEA’s Director General evaluated the agency’s safeguards program to examine how effectively and efficiently strengthened safeguards measures were being implemented. Specifically, the group’s mission was to evaluate the progress, effectiveness, and impact of implementing measures to enhance the agency’s ability to draw conclusions about the non-diversion of nuclear material placed under safeguards and, for relevant countries, the absence of undeclared nuclear material and activities. The group concluded that generally IAEA had done a very good job implementing strengthened safeguards despite budgetary and other constraints. However, the group noted that IAEA’s ability to detect undeclared activities remains largely untested. If a country decides to divert nuclear material or conduct undeclared activities, it will deliberately work to prevent IAEA from discovering this. Furthermore, IAEA and member states should be clear that the conclusions drawn by the agency cannot be regarded as absolute. This view has been reinforced by the former Deputy Director General for Safeguards who has stated that even for countries with strengthened safeguards in force, there are limitations on the types of information and locations accessible to IAEA inspectors.
A Number of Weaknesses Impede IAEA’s Ability to Effectively Implement Strengthened Safeguards There are a number of weaknesses that hamper IAEA’s ability to effectively implement strengthened safeguards. IAEA has only limited information about the nuclear activities of 4 key countries that are not members of the NPT—India, Israel, North Korea, and Pakistan. India, Israel, and Pakistan have special agreements with IAEA that limit the agency’s activities to monitoring only specific material, equipment, and facilities. However, since these countries are not signatories to the NPT, they do not have comprehensive safeguards agreements with IAEA, and are not required to declare all of their nuclear material to the agency. In addition, these countries are only required to declare exports of nuclear material previously declared to IAEA. With the recent revelations of the illicit international trade in nuclear material and equipment, IAEA officials stated that they need more information on these countries’ nuclear exports. For North Korea, IAEA has even less information, since the country expelled IAEA inspectors and removed surveillance equipment at nuclear facilities in December 2002 and withdrew from the NPT in January 2003. These actions have raised widespread concern that North Korea diverted some of its nuclear material to produce nuclear weapons. Another major weakness is that more than half, or 111 out of 189, of the NPT signatories have not yet brought the Additional Protocol into force, as of August 2006. (App. I lists the status of countries’ safeguards agreements with IAEA). Without the Additional Protocol, IAEA must limit its inspection efforts to declared nuclear material and facilities, making it harder to detect clandestine nuclear programs. Of the 111 countries that have not adopted the Additional Protocol, 21 are engaged in significant nuclear activities,9 including Egypt, North Korea, and Syria.
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In addition, safeguards are significantly limited or not applied in about 60 percent, or 112 out of 189, of the NPT signatory countries—either because they have an agreement (known as a small quantities protocol) with IAEA, and are not subject to most safeguards measures, or because they have not concluded a comprehensive safeguards agreement with IAEA. Countries with small quantities of nuclear material make up about 41 percent of the NPT signatories and about one-third of the countries that have the Additional Protocol in force. Since 1971, IAEA’s Board of Governors has authorized the Director General to conclude an agreement, known as a small quantities protocol, with 90 countries and, as of August 2006, 78 of these agreements were in force. IAEA’s Board of Governors has approved the protocols for these countries without having IAEA verify that they met the requirements for it. Even if these countries bring the Additional Protocol into force, IAEA does not have the right to conduct inspections or install surveillance equipment at certain nuclear facilities. According to IAEA and Department of State officials, this is a weakness in the agency’s ability to detect clandestine nuclear activities or transshipments of nuclear material and equipment through the country. In September 2005, the Board of Governors directed IAEA to negotiate with countries to make changes to the protocols, including reinstating the agency’s right to conduct inspections. As of August 2006, IAEA amended the protocols for 4 countries—Ecuador, Mali, Palau, and Tajikistan. The application of safeguards is further limited because 31 countries that have signed the NPT have not brought into force a comprehensive safeguards agreement with IAEA. The NPT requires non-nuclear weapons states to conclude comprehensive safeguards agreements with IAEA within 18 months of becoming a party to the Treaty. However, IAEA’s Director General has stated that these 31 countries have failed to fulfill their legal obligations. Moreover, 27 of the 31 have not yet brought comprehensive safeguards agreements into force more than 10 years after becoming party to the NPT, including Chad, Kenya, and Saudi Arabia. Last, IAEA is facing a looming human capital crisis that may hamper the agency’s ability to meet its safeguards mission. In 2005, we reported that about 51 percent, or 38 out of 75, of IAEA’s senior safeguards inspectors and high-level management officials, such as the head of the Department of Safeguards and the directors responsible for overseeing all inspection activities of nuclear programs, are retiring in the next 5 years.10 According to U.S. officials, this significant loss of knowledge and expertise could compromise the quality of analysis of countries’ nuclear programs. For example, several inspectors with expertise in uranium enrichment techniques, which is a primary means to produce nuclear weapons material, are retiring at a time when demand for their skills in detecting clandestine nuclear activities is growing. While IAEA has taken a number of steps to address these human capital issues, officials from the Department of State and the U.S. Mission to the U.N. System Organizations in Vienna have expressed concern that IAEA is not adequately planning to replace staff with critical skills needed to fulfill its strengthened safeguards mission.
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THE NUCLEAR SUPPLIERS GROUP HAS HELPED STEM NUCLEAR PROLIFERATION, BUT LACK OF INFORMATION SHARING ON NUCLEAR EXPORTS BETWEEN MEMBERS COULD UNDERMINE ITS EFFORTS The Nuclear Suppliers Group, along with other multilateral export control groups, has helped stop, slow, or raise the costs of nuclear proliferation, according to nonproliferation experts. For example, as we reported in 2002, the Suppliers Group helped convince Argentina and Brazil to accept IAEA safeguards on their nuclear programs in exchange for expanded access to international cooperation for peaceful nuclear purposes.11 The Suppliers Group, along with other multilateral export control groups, has significantly reduced the availability of technology and equipment available to countries of concern, according to a State Department official. Moreover, nuclear export controls have made it more difficult, more costly, and more time consuming for proliferators to obtain the expertise and material needed to advance their nuclear program. The Nuclear Suppliers Group has also helped IAEA verify compliance with the NPT. In 1978, the Suppliers Group published the first guidelines governing exports of nuclear materials and equipment. These guidelines established several member requirements, including the requirement that members adhere to IAEA safeguards standards at facilities using controlled nuclear-related items. Subsequently, in 1992, the Nuclear Suppliers Group broadened its guidelines by requiring that members insist that non-member states have IAEA safeguards on all nuclear material and facilities as a condition of supply for their nuclear exports. With the revelation of Iraq’s nuclear weapons program, the Suppliers Group also created an export control system for dual-use items that established new controls for items that did not automatically fall under IAEA safeguards requirements.12 Despite these benefits, there are a number of weaknesses that could limit the Nuclear Suppliers Group’s ability to curb nuclear proliferation. Members of the Suppliers Group do not share complete export licensing information. Specifically, members do not always share information about licenses they have approved or denied for the sale of controversial items to nonmember states. Without this shared information, a member country could inadvertently license a controversial item to a country that has already been denied a license from another Suppliers Group member state. Furthermore, Suppliers Group members did not promptly review and agree upon common lists of items to control and approaches to controlling them. Each member must make changes to its national export control policies after members agree to change items on the control list. If agreed-upon changes to control lists are not adopted at the same time by all members, proliferators could exploit these time lags to obtain sensitive technologies by focusing on members that are slowest to incorporate the changes and sensitive items may still be traded to countries of concern. In addition, there are a number of obstacles to efforts aimed at strengthening the Nuclear Suppliers Group and other multilateral export control regimes. First, efforts to strengthen export controls have been hampered by a requirement that all members reach consensus about every decision made. Under the current process, a single member can block new reforms.
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U.S. and foreign government officials and nonproliferation experts all stressed that the regimes are consensus-based organizations and depend on the like-mindedness or cohesion of their members to be effective. However, members have found it especially difficult to reach consensus on such issues as making changes to procedures and control lists. The Suppliers Group reliance on consensus decision making will be tested by the United States request to exempt India from the Suppliers Group requirements to accept IAEA safeguards at all nuclear facilities. Second, since membership with the Suppliers Group is voluntary and nonbinding, there are no means to enforce compliance with members’ nonproliferation commitments. For example, the Suppliers Group has no direct means to impede Russia’s export of nuclear fuel to India, an act that the U.S. government said violated Russia’s commitment. Third, the rapid pace of nuclear technological change and the growing trade of sensitive items among proliferators complicate efforts to keep control lists current because these lists need to be updated more frequently. To help strengthen these regimes, GAO recommended in October 2002, that the Secretary of State establish a strategy that includes ways for Nuclear Suppliers Group members to improve information sharing, implement changes to export controls more consistently, and identify organizational changes that could help reform its activities. As of June 2006, the Nuclear Suppliers Group announced that it has revised its guidelines to improve information sharing. However, despite our recommendation, it has not yet agreed to share greater and more detailed information on approved exports of sensitive transfers to nonmember countries. Nevertheless, the Suppliers Group is examining changes to its procedures that assist IAEA’s efforts to strengthen safeguards. For example, at the 2005 Nuclear Suppliers Group plenary meeting, members discussed changing the requirements for exporting nuclear material and equipment by requiring nonmember countries to adopt IAEA’s Additional Protocol as a condition of supply. If approved by the Suppliers Group, the action would complement IAEA’s efforts to verify compliance with the NPT.
U.S. BILATERAL ASSISTANCE PROGRAMS ARE WORKING TO SECURE NUCLEAR MATERIALS AND WARHEADS, DETECT NUCLEAR SMUGGLING, ELIMINATE EXCESS NUCLEAR MATERIAL, AND HALT PRODUCTION OF PLUTONIUM, BUT CHALLENGES REMAIN Reducing the formidable proliferation risks posed by former Soviet weapons of mass destruction (WMD) assets is a U.S. national security interest. Since the fall of the Soviet Union, the United States, through a variety of programs, managed by the Departments of Energy, Defense (DOD), and State, has helped Russia and other former Soviet countries to secure nuclear material and warheads, detect illicitly trafficked nuclear material, eliminate excess stockpiles of weapons-usable nuclear material, and halt the continued production of weapons-grade plutonium. From fiscal year 1992 through fiscal year 2006, the Congress appropriated about $7 billion for nuclear nonproliferation efforts.13 However, U.S. assistance programs have faced a number of challenges, such as a lack of access to key sites and corruption of foreign officials, which could compromise the effectiveness of U.S. assistance.
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DOE’s Material Protection, Control, and Accounting (MPC&A) program has worked with Russia and other former Soviet countries since 1994 to provide enhanced physical protection systems at sites with weapons-usable nuclear material and warheads, implement material control and accounting upgrades to help keep track of the quantities of nuclear materials at sites, and consolidate material into fewer, more secure buildings. GAO last reported on the MPC&A program in 2003.14 At that time, a lack of access to many sites in Russia’s nuclear weapons complex had significantly impeded DOE’s progress in helping Russia to secure its nuclear material. We reported that DOE had completed work at only a limited number of buildings in Russia’s nuclear weapons complex, a network of sites involved in the construction of nuclear weapons where most of the nuclear material in Russia is stored. According to DOE, by the end of September 2006, the agency will have helped to secure 175 buildings with weapons-usable nuclear material in Russia and the former Soviet Union and 39 Russian Navy nuclear warhead sites. GAO is currently re-examining DOE’s efforts, including the progress DOE has made since 2003 in securing nuclear material and warheads in Russia and other countries and the challenges DOE faces in completing its work. While securing nuclear materials and warheads where they are stored is considered to be the first layer of defense against nuclear theft, there is no guarantee that such items will not be stolen or lost. Recognizing this fact, DOE, DOD, and State, through seven different programs, have provided radiation detection equipment since 1994 to 36 countries, including many countries of the former Soviet Union. These programs seek to combat nuclear smuggling and are seen as a second line of defense against nuclear theft. The largest and most successful of these efforts is DOE’s Second Line of Defense program (SLD). We reported in March 2006 that, through the SLD program, DOE had provided radiation detection equipment and training at 83 sites in Russia, Greece, and Lithuania since 1998. However, we also noted that U.S. radiation detection assistance efforts faced challenges, including corruption of some foreign border security officials, technical limitations of some radiation detection equipment, and inadequate maintenance of some equipment. To address these challenges, U.S. agencies plan to take a number of steps, including combating corruption by installing communications links between individual border sites and national command centers so that detection alarm data can be simultaneously evaluated by multiple officials. The United States is also helping Russia to eliminate excess stockpiles of nuclear material (highly enriched uranium and plutonium). In February 1993, the United States agreed to purchase from Russia 500 metric tons of highly enriched uranium (HEU) extracted from dismantled Russian nuclear weapons over a 20-year period. Russia agreed to dilute, or blend-down, the material into low enriched uranium (LEU), which is of significantly less proliferation risk, so that it could be made into fuel for commercial nuclear power reactors before shipping it to the United States.15 As of June 27, 2006, 276 metric tons of Russian HEU—derived from more than 11,000 dismantled nuclear weapons—have been downblended into LEU for use in U.S. commercial nuclear reactors. Similarly, in 2000, the United States and Russia committed to the transparent disposition of 34 metric tons each of weapon-grade plutonium. The plutonium will be converted into a more proliferation-resistant form called mixed-oxide (MOX) fuel that will be used in commercial nuclear power plants. In addition to constructing a MOX fuel fabrication plant at its Savannah River Site, DOE is also assisting Russia in constructing a similar facility for the Russian plutonium. Russia’s continued operation of three plutonium production reactors poses a serious proliferation threat. These reactors produce about 1.2 metric tons of plutonium each year—
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enough for about 300 nuclear weapons. DOE’s Elimination of Weapons-Grade Plutonium Production program seeks to facilitate the reactors’ closure by building or refurbishing two fossil fuel plants that will replace the heat and electricity that will be lost with the shutdown of Russia’s three plutonium production reactors. DOE plans to complete the first of the two replacement plants in 2008 and the second in 2011. When we reported on this program in June 2004,16 we noted that DOE faced challenges in implementing its program, including ensuring Russia’s commitment to shutting down the reactors, the rising cost of building the replacement fossil fuel plants, and concerns about the thousands of Russian nuclear workers who will lose their jobs when the reactors are shut down. We made a number of recommendations, which DOE has implemented, including reaching agreement with Russia on the specific steps to be taken to shut down the reactors and development of a plan to work with other U.S. government programs to assist Russia in finding alternate employment for the skilled nuclear workers who will lose their jobs when the reactors are shut down. Mr. Chairman, this concludes my prepared statement. I would be pleased to respond to any questions you or other Members of the Subcommittee may have at this time.
CONTACTS AND STAFF ACKNOWLEDGMENTS For future contacts regarding this testimony, please contact Gene Aloise at (202) 5123841 or Joseph Christoff at (202) 512-8979. R. Stockton Butler, Miriam A. Carroll, Leland Cogliani, Lynn Cothern, Muriel J. Forster, Jeffrey Phillips, and Jim Shafer made key contributions to this testimony. Beth Hoffman León, Stephen Lord, Audrey Solis, and Pierre Toureille provided technical assistance.
APPENDIX I: COUNTRIES’ SAFEGUARDS AGREEMENTS WITH IAEA, AS OF AUGUST 2006 State
Comprehensive Safeguards Agreement
Additional Protocol
Small Quantities Protocol
Afghanistan
X
X
X
Albania
X
Algeria
X
Non-nuclear weapons state
Andorra Angola Antigua and Barbuda
X
X
Argentina
X
Armenia
X
X
Australia
X
X
Austria
X
X
Azerbaijan
X
X
Bahamas
X
X X
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Appendix I. (Continued) State
Comprehensive Safeguards Agreement
Additional Protocol
Bangladesh
X
X
Barbados
X
Small Quantities Protocol
Bahrain X
Belarus
X
Belgium
X
Belize
X
X
Bhutan
X
X
Bolivia
X
X
Bosnia and Herzegovina
X
Botswana
X
Brazil
X
X
Benin
X
Brunei Darussalam
X
Bulgaria
X
X
X
Burkina Faso
X
X
X
Burundi Cambodia
X
X
Cameroon
X
X
Canada
X
X
Chile
X
X
Colombia
X
Cape Verde Central African Republic Chad
Comoros Costa Rica
X
Cote d’Ivoire
X
X
Croatia
X
X
Cuba
X
X
Cyprus
X
X X
Czech Republic
X
Democratic People’s Republic of Koreaa
X
Democratic Republic of the Congo
X
X
Denmark
X
X
X X
Djibouti Dominica
X
X
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State
Additional Protocol
Dominican Republic
Comprehensive Safeguards Agreement X
Small Quantities Protocol
Ecuador
X
X
X
Egypt
X
El Salvador
X
X
X
Estonia
X
X
Ethiopia
X
X
Equatorial Guinea Eritrea X
Federated States of Micronesia Fiji
X
X
Finland
X
X
X
The Former Yugoslav Republic of Macedonia
X
X
Gambia
X
X
Georgia
X
X
Germany
X
X
Ghana
X
X
Greece
X
X
Grenada
X
X
Guatemala
X
X
Guyana
X
X
Haiti
X
X
Holy See
X
X
Honduras
X
Hungary
X
X
Iceland
X
X
Indonesia
X
X
Gabon
Guinea Guinea-Bissau
Iraq
X
Ireland
X
X X X X
X
Islamic Republic of Iran
X
Italy
X
X
Jamaica
X
X
Japan
X
X
Jordan
X
X
X
Kazakhstan
X
State
Comprehensive
Additional
Small Quantities
Nuclear Nonproliferation: IAEA Safeguards and Other Measures… Safeguards Agreement
Protocol
Protocol
Kenya Kiribati
X
X
Kuwait
X
Kyrgyzstan
X
Latvia
X
Lebanon
X
X
Lesotho
X
X
X
X X
X
Liberia Libyan Arab Jamahiriya
X
Liechtenstein
X
X
Lithuania
X
X
Luxembourg
X
X
Madagascar
X
X
Malawi
X
Malaysia
X
Maldives
X
Mali
X
X
X
Malta
X
X
X
Marshall Islands
X
X
X X X
Mauritania Mauritius
X
Mexico
X
X
Monaco
X
X
X
Mongolia
X
X
X
Montenegro Morocco
X
Mozambique Myanmar
X
X
Namibia
X
X
Nauru
X
X
Nepal
X
Netherlands
X
X
X
New Zealand
X
X
X
Nicaragua
X
X
X
Niger
X
Nigeria
X
Norway
X
X
X
X
Oman Palau
X
931
932
Gene Aloise Appendix I. Continued
State
Panama
Comprehensive Safeguards Agreement X
Papua New Guinea
X
Paraguay
X
People’s Democratic Republic of Laos
X
Additional Protocol
Small Quantities Protocol
X
X
X
X
X X
Peru
X
Philippines
X
X
Poland
X
X
Portugal
X
X
Republic of Korea
X
X
Republic of Moldova
X
X
Republic of Yemen
X
X
Romania
X
Qatar Republic of the Congo
X
Rwanda St. Kitts and Nevis
X
X
St. Lucia
X
X
St. Vincent and the Grenadines
X
X
Samoa
X
X
San Marino
X
X
Senegal
X
X
Serbia
X
Seychelles
X
Sao Tome and Principe Saudi Arabia
X
X
Sierra Leone Singapore
X
Slovakia
X
X
X
Slovenia
X
X
Solomon Islands
X
X
Somalia South Africa
X
X
Spain
X
X
Sri Lanka
X
Sudan
X
X
Suriname
X
X
Swaziland
X
X
Nuclear Nonproliferation: IAEA Safeguards and Other Measures… State
Sweden
Comprehensive Safeguards Agreement X
X
Switzerland
X
X
Syrian Arab Republic
X
Tajikistan
X
Thailand
X
Additional Protocol
X
933
Small Quantities Protocol
X
Timor-Leste Togo Tonga
X
X
Trinidad and Tobago
X
X
Tunisia
X
Turkey
X
X
Turkmenistan
X
X
Tuvalu
X
Uganda
X
X
Ukraine
X
X
United Arab Emirates
X
United Republic of Tanzania
X
X X X X
Uruguay
X
X
Uzbekistan
X
X
X
Vanuatu Venezuela
X
Vietnam
X
Zambia
X
X
Zimbabwe
X
X
Nuclear weapons states with safeguards agreements in force
China
X
X
France
X
X
Russian Federation
X
United Kingdom
X
United States of America
X
X
States with special safeguards agreements
India Israel Pakistan a
Although North Korea concluded a comprehensive safeguards agreement with IAEA in 1992, it announced its withdrawal from the NPT in January 2003.
934
Gene Aloise
APPENDIX II: MEMBERS OF THE NUCLEAR SUPPLIERS GROUP, AS OF JUNE 2006 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Argentina Australia Austria Belarus Belgium Brazil Bulgaria Canada China Croatia Cyprus Czech Republic Denmark Estonia Finland France Germany Greece Hungary Ireland Italy Japan Kazakhstan
24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45
Latvia Lithuania Luxembourg Malta Netherlands New Zealand Norway Poland Portugal Romania Russia Slovakia Slovenia South Africa South Korea Spain Sweden Switzerland Turkey Ukraine United Kingdom United States
Source: Nuclear Suppliers Group Statement, Nuclear Suppliers Group Strengthening the Nuclear NonProliferation Regime, Brasilia, June 2, 2006.
APPENDIX III: ADDITIONAL INFORMATION ON U.S. NUCLEAR NONPROLIFERATION PROGRAMS Project Department of Energy Projects
Description
Global Radiological Threat Reduction Secures radiological sources no longer needed in the U.S. and locates, identifies, recovers, consolidates, and enhances the security of radioactive materials outside the U.S. Global Nuclear Material Threat Reduction
Eliminates Russia’s use of highly enriched uranium (HEU) in civilian nuclear facilities; returns U.S. and Russian-origin HEU and spent nuclear fuel from research reactors around the world; secures plutonium-bearing spent nuclear fuel from reactors in Kazakhstan; and addresses nuclear and radiological materials at vulnerable locations throughout the world.
Elimination of Weapons-Grade Plutonium Production project International Safeguards project
Provides replacement fossil-fuel energy that will allow Russia to shutdown its three remaining weapons-grade plutonium production reactors. Develops and delivers technology applications to strengthen capabilities to detect and verify undeclared nuclear programs; enhances the physical protection and proper accounting of nuclear material; and assists foreign national partners to meet safeguards commitments.
Nuclear Nonproliferation: IAEA Safeguards and Other Measures…
935
Project Department of Energy Projects
Description
Russian Transition Initiatives project
Provides meaningful employment for former weapons of mass destruction weapons scientists. Provides material protection, control, and accounting upgrades to enhance the security of Navy HEU fuel and nuclear material.
Nuclear Warhead Protection project Weapons Material Protection project
Provides material protection, control, and accounting upgrades to nuclear weapons, uranium enrichment, and material processing and storage sites.
Material Consolidation & Civilian Sites Enhances the security of proliferation-attractive nuclear material in Russia by supporting material protection, control, and accounting upgrade projects project at Russian civilian nuclear facilities. National Infrastructure & Sustainability Develops national and regional resources in the Russian Federation to help project establish and sustain effective operation of upgraded nuclear material protection, control and accounting systems. Second Line of Defense & Megaports Negotiates cooperative efforts with the Russian Federation and other key Initiative project countries to strengthen the capability of enforcement officials to detect and deter illicit trafficking of nuclear and radiological material across international borders. This is accomplished through the detection, location and identification of nuclear and nuclear related materials, the development of response procedures and capabilities, and the establishment of required infrastructure elements to support the control of these materials HEU Transparency Implementation Monitors Russia to ensure that low enriched uranium (LEU) sold to the project U.S. for civilian nuclear power plants is derived from weapons-usable HEU removed from dismantled Russian nuclear weapons. Surplus U.S. HEU Disposition project Disposes of surplus domestic HEU by down-blending it. Surplus U.S. Plutonium Disposition project Surplus Russian Plutonium Disposition project Personnel Reliability and Safety Site Security Enhancements
Nuclear Weapons Transportation
Disposes of surplus domestic plutonium by fabricating it into mixed oxide (MOX) fuel for irradiation in existing, commercial nuclear reactors. Supports Russia’s efforts to dispose of its weapons-grade plutonium by working with the international community to help pay for Russia’s program. Provides training and equipment to assist Russia in determining the reliability of its guard forces. Enhances the safety and security of Russian nuclear weapons storage sites through the use of vulnerability assessments to determine specific requirements for upgrades. DOD will develop security designs to address those vulnerabilities and install equipment necessary to bring security standards consistent with those at U.S. nuclear weapons storage facilities. Assists Russia in shipping nuclear warheads to more secure sites or dismantlement locations.
Railcar Maintenance and Procurement Assists Russia in maintaining nuclear weapons cargo railcars. Funds maintenance of railcars until no longer feasible, then purchases replacement railcars to maintain 100 cars in service. DOD will procure 15 guard railcars to replace those retired from service. Guard railcars will be capable of monitoring security systems in the cargo railcars and transporting security force personnel. Weapons Transportation Provides emergency response vehicles containing hydraulic cutting tools, Safety Enhancements pneumatic jacks, and safety gear to enhance Russia’s ability to respond to possible accidents in transporting nuclear weapons. Meteorological, radiation detection and monitoring, and communications equipment is also included.
Source: GAO analysis.
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Gene Aloise
ENDNOTES 1
Under the NPT, nuclear weapons states pledged to facilitate the transfer of peaceful nuclear technology to non-nuclear weapons states, but not to assist them in acquiring nuclear weapons. 2 GAO, Nuclear Nonproliferation: IAEA Has Strengthened Its Safeguards and Nuclear Security Programs, but Weaknesses Need to Be Addressed, GAO-06-93 (Washington, D.C.: Oct. 7, 2005). 3 GAO, Nonproliferation: Strategy Needed to Strengthen Multilateral Export Control Regimes, GAO-03-43 (Washington, D.C.: Oct. 25, 2002). 4 Weapons-usable nuclear material is uranium enriched to 20 percent or greater in uranium235 or uranium-233 and any plutonium containing less than 80 percent of the isotope plutonium-238 and less than 10 percent of the isotopes plutonium-241 and plutonium242. These types of material are of the quality used to make nuclear weapons. 5 A listing of relevant U.S. nuclear nonproliferation programs can be found in appendix III. 6 Regional treaties, including the Treaty for the Prohibition of Nuclear Weapons in Latin America (the 1967 Treaty of Tlatelolco), the South Pacific Nuclear Free Zone Treaty (the 1985 Treaty of Rarotonga), the African Nuclear-Weapon-Free Zone Treaty (the 1995 Treaty of Pelindaba), and the Southeast Asia Nuclear-Weapon-Free Treaty (the 1995 Bangkok Treaty) require each participating country to conclude a comprehensive safeguards agreement with IAEA. Additionally, in February 2005, five Central Asian states announced that they had reached agreement on the text of a treaty to establish a nuclear-weapon-free zone. 7 Nuclear materials include source materials, such as natural uranium, depleted uranium, and thorium, and special fissionable materials, such as enriched uranium and plutonium. 8 Model Protocol Additional to the Agreement(s) Between State(s) and the International Atomic Energy Agency for the Application of Safeguards. 9 IAEA defines a country with significant nuclear activities as one that has declared nuclear material in a facility or a location outside facilities. 10 In 2004, the Department of Safeguards had 552 staff members. Of these, 251 were safeguards inspectors. 11 GAO, Nonproliferation: Strategy Needed to Strengthen Multilateral Export Control Regimes, GAO-03-43 (Washington, D.C.: Oct. 25, 2002). 12 Previously, the Nuclear Suppliers Group control list included nuclear equipment and material, the export of which would trigger a requirement that IAEA safeguards apply to the recipient facility. 13 This includes funding for nuclear security programs, but does not include funding for parts of DOD’s Cooperative Threat Reduction program that work on demilitarization, chemical or biological weapons issues, or the destruction and dismantlement of weapons delivery systems. 14 GAO, Weapons of Mass Destruction: Additional Russian Cooperation Needed to Facilitate U.S. Efforts to Improve Security at Russian Sites, GAO-03-482 (Washington, D.C.: Mar. 24, 2003).
Nuclear Nonproliferation: IAEA Safeguards and Other Measures… 15
16
937
Formally known as “The Agreement Between the Government of the United States of America and the Government of the Russian Federation Concerning the Disposition of Highly Enriched Uranium Extracted from Nuclear Weapons” (Feb. 18, 1993). GAO, Nuclear Nonproliferation: DOE’s Effort to Close Russia’s Plutonium Production Reactors Faces Challenges, and Final Shutdown Is Uncertain, GAO-04-662 (Washington, D.C.: June 4, 2004).
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 939-1059
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 32
RADIAL-BIAS-COMBUSTION AND CENTRAL-FUELRICH SWIRL PULVERIZED COAL BURNERS FOR WALL-FIRED BOILERS* Zhengqi Li† School of Energy Science and Engineering, Harbin Institute of Technology, 92, West Dazhi Street, Harbin 150001, P. R. China
ABSTRACT The kind of swirl coal burners is given. Radial-biased-combustion and centrally-fuelrich swirl coal combustion technology was developed. In the air and the air-particle test facilities, the single sensor hot-film and the anemometers were used to measure air and air-particle flows in the near-burner region of different swirl burners. Both cold air flow and reacting flow experiments were performed in the industrial 50, 220, 410, 670 and 1025 ton per hour boilers. On an air-particle test facility, the characteristics of the pulverized-coal concentrator with cone vanes were investigated. The influence of structure parameters, such as run parameters such as swirling vane angle and burner cone angle and length, and run parameters, such as non-swirl secondary air, central air and air supply, and primary air flow type on divergent angles, diameter and length of the central recirculation zone, mixing characteristic of the primary air and the secondary air, in-situ gas temperature and NOx formation near the burner zone, carbon in ash and NOx emission of boilers was determined with the radial-biased-combustion burner. The difference characteristics of gas/particle flow and coal combustion of the centrally-fuelrich and dual register burners were obtained. The experimental results show that the two new burners simultaneously have the ability of high combustion efficiency, flame
*
A version of this chapter was also published in Leading-Edge Electric Power Research edited by C.M. O’Sullivan published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research. † Tel.: +86 451 86 41 8854; Fax: +86 451 86 41 25 28; E-mail:
[email protected] 940
Zhengqi Li stability, low NOx emission and resistance to slagging and high temperature corrosion. The air-surrounding-fuel combustion theory was put forward.
1. INTRODUCTION 1.1. Problems of Coal Combustion Technology In China, utility boilers consume about 27 % of the total coal production and generate about 70 % of the country’s electricity, and emit the majority of pollutants in cities. China’s coals are mostly low-grade with low calorific value. They either have small amounts of volatile matter or high moisture and/or ash content. Generally the flame from these coals is not stable. The ashes also have low ash fusion points, thus a tendency to slag in the furnace. The power industry requires coal combustion techniques, which have flame stability, no slagging propensities, high combustion efficiency and which meet pollution control standards. It is difficult to attain these requirements simultaneously because they are often in conflict with each other. For example, the quality of coal provided to power plants often fluctuates and is usually low-grade. It is very difficult to keep a stable flame with this type of coal, especially when the load is low. This also lowers combustion efficiency. To achieve a stable flame, supporting fuel is often used which increases the operating cost [1]. Another example of these conflicting requirements is the attempt to decrease the emission of the pollutant NOx. An effective method is to raise the pulverized coal (PF) concentration and delay the mixing of air with the coal stream. However, this method has a propensity to form slag in the furnace and also decreases combustion efficiency [2-5]. Clearly there is a challenge in meeting these conflicting requirements of the industry.
1.2. Characteristics of Swirl Coal Combustion Technology Swirl coal burners are applied widely on boilers with different capacities. Compared with the tangential firing boilers, boilers with swirl burners have the following main characteristics: (1) They can avoid imbalance of temperature of super heater in tangential firing boilers. (2) Swirl burners form their own coal flame independently and don’t influence each other. (3) There is no strict demand for furnace shape and the furnace shape with swirl burners does not need to approach to square. It is convenient to the arrangement of convection heating facilities. (4) Swirl burners are arranged evenly on front-wall and back-wall. The distribution of quantity of heat imported to furnace is relatively uniform. It reduces the slagging trend resulted from excessive high gas temperature in the central region of furnace. (5) There is no need to increase the thermal capacity of a single burner when the unit capacity increases. We just increase the width of furnace and increase the number and rows of burners. Swirl burners take high gas temperature central recirculation zone as thermal source to make air/coal mixing ignite.
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners…
941
1.3. Types of Swirl Coal Burners According to the types of the secondary air and the fuel concentration of primary air/coal mixing, swirl coal burners can be divided into three categories: general, air-staged combustion and fuel-bias-combustion types.
1. General Type of Swirl Burners This type of burners is the burner whose secondary air is introduced to furnace without being divided into two parts and whose primary air/coal mixing is not concentrated. The following burners have the characteristics: double-volute swirl coal burner, tangential-register vane burner, axial-register vane burner and the volute burner with axial-register vanes. 2. Air-Staged Combustion Type of Swirl Burners This type of burners is the burner whose secondary air is divided into two or more parts and whose primary air/coal mixing is not concentrated, the following burners have the characteristics: (1) The dual channel swirl burner [7]：Without swirling, the primary air is ejected to the furnace. The secondary air is separated to two parts. Most of the secondary air passes through axially bent vanes, and without swirling, the rest secondary air is ejected to the furnace at a large velocity via another air channel. This type of burner has good regulating property. It is the first generation low NOx burner of BW Company. (2) The SM burner：The primary air is non-swirling and the secondary air swirls via axial bent vanes. The primary and secondary airs account for 80-90% of the total air. The rest of air is introduced to furnace through four symmetrical-arrangement nozzles around the burner. This type of burner is suit to slag tapping and dry ash extraction boilers. (3) The RSFC burner: The primary air is non-swirling and the secondary air is introduced to furnace through three concentric nozzles. Each nozzle has a swirler. Any one or all of the nozzles can be used for the injection of externally recirculated flue gas through the burner. With the RSFC burners, radial stratified combustion is formed in the near burner region, the coal burnout decreases, the NOx emission is reduced, and high temperature corrosion is prevented. (4) Volute-vane swirl burner [7]: The primary air is introduced to furnace through volute. The secondary air is separated into two swirling streams. They are injected to furnace through axially bent vanes in the inner and outer channels respectively. (5) Primary Air Exchange(PAX) burner[9]: For coals with very low volatile matter, such as semi-anthracites and anthracites, further provisions are required to obtain satisfactory ignition performances. With such coals, volatile matter has diminished to such an extent that the heat it contributes to the burner ignition zone is insufficient to sustain ignition. Temperature in the ignition zone has to be increased by controlling heat loss, returning heat from char reactions to the ignition zone, and further preheating the air and fuel prior to its introduction to the burner. BandW developed the PAX burner for these applications. The PAX burner utilizes a device in the burner nozzle to vent off primary air and replace it with hot air to preheat the fuel immediately prior to ignition. The extracted primary air, accompanied by a small
942
Zhengqi Li percentage of the coal, is vented into the furnace and uses the main burner as its ignition source. The dual register design (derived from the Enhanced Ignition-Dual Register burner) is used.
3. Fuel-Bias-Combustion Swirl Burner This type of burners is the burner whose primary air/coal mixing is separated to increase the fuel concentration. As the fuel concentration increases, the flame stability improves. It has two categories. The primary air/coal mixing is separated into two streams: the fuel-rich and the fuel-lean streams. The fuel-rich stream is introduced to furnace through burner, and the fuel-lean one is introduced to furnace solely at a certain furnace position. This is a high fuel concentration swirl burner. The fuel-rich and fuel-lean streams are introduced to furnace through different channels of burner. This is the fuel-rich and fuel-lean combustion swirl burner.
Figure 1. a) NSZ burner with external fuel enrichment and b) NSW burner with internal fuel enrichment.
(1) High Fuel Concentration Swirl Burner (1) Former Soviet Russia’s high fuel concentration swirl burner: Coal concentration combustion experiments were done on a 30×105kw T∏∏-210A type boiler. The air/coal mixing was conveyed in a new tubule by compressed air and the fuel concentration of the mixing was as large as 40-50kg (coal)/kg (air). The primary air
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners…
943
duct only conveyed air. Before arriving at the burner outlet, pulverized coal was injected to the primary air at a suitable position and a fuel concentration of 0.9 kg (coal)/kg (air) was gotten. The results showed that air/coal mixing ignited earlier and NOx emission sharply decreased. (2) Low-NOx burner with external coal concentrator(NSZ burner, see Figure 1a)[10]: Swirl type concentrator is inserted between coal mill and burner. Enriched coal-air mixing flows through the burner fuel nozzle. In order to intensify mixing of fuel with hot internal recirculation gas, this enriched mixing is supplied via four separate ducts, parallel to the burner axis. Air and transporting gas from concentrators are released into the combustion chamber above the burners.
(2) The Fuel-Rich and Fuel-Lean Combustion Swirl Burner (1) Dual Register(DR) burner and Enhanced Ignition-Dual Register(EI-DR) burner(see Figure 2) [9]: The EI-DR burner has axial vanes in the inner secondary air duct and tangential or axial vanes in the outer secondary air duct and the swirling direction of the inner and the outer secondary airs is identical. Pulverized coal is separated and concentrated into the wall zone of the primary air duct by the conical diffuser. Then, the coal rich zone is near the wall zone of the primary air duct and the coal lean zone is in the central zone of the primary air duct. The structures of DR and EI-DR burners are the same. The designed primary air velocity of EI-DR burner is less than that of DR burner, and The designed secondary air velocity of EI-DR burner is larger than that of DR burner. (2) Low-NOx burner with an internal coal concentrator (NSW burner, see Figure 1b) [10]: Such complex system of NSZ burners is a source of many problems, especially in boiler reconstruction. Usually there is no room available for fitting release ducts from concentrators, while many pipelines make access to the boiler difficult and complicate maintenance and repairs. It then proved necessary to design a new burner with an internal coal concentrator. Enriched coal-air mixing is directed towards the axis of flow in the form of several slightly swirled streams, while lean mixing is directed to the secondary air stream. When burner operates properly, ignition takes place in the zone of the finest released particles and thus a shield is formed, protecting the main combustion zone from the secondary air inflow. Secondary air is supplied via two coaxial ducts outside the main fuel nozzle, and fuel is mixed with the secondary air outside the “rich” combustion zone. Secondary air flow in both these ducts is controlled. (3) Dense dilute dual-channel burner (see Figure 3) [11]: Along the radial direction, from outside to inside, they are outer secondary air, inner secondary air, primary air in sequence. The inner and outer secondary airs become swirling after they pass through axial-register vanes. The swirling intensity of the two air streams can be regulated by pulling or pushing the axial-register vanes. The primary air/coal mixing becomes swirling through bent vanes in primary air duct. After the swirling coal-air mixing entering the four axial arrangement channels, the swirling of air is restrained and swirls weekly. Because of coal inertia, the pulverized coal gathered in near pulverized coal collector region and four fuel-rich and fuel-lean air/coal mixings are formed. Then fuel-bias combustion along the circle direction is gotten.
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Zhengqi Li
Figure 2. EI-DR burner and the position of the monitor pipe (the dimensions are in mm): (1) particle deflector, (2) primary air duct, (3) inner secondary air duct, (4) outer secondary air duct, (5) watercooled wall, (6) axial vanes (the angle is 60º), (7) tangential vanes (the angle is 25º), (8) conical diffuser, (9) monitor pipe.
Figure 3. Dense dilute dual-channel burner: (1) cone, (2) axial vanes, (3) flame stabilization ring, (4) axial vanes, (5) pulverized fuel feeder, (6) throttle valve, (7) bent vanes, (8) central pipe, (9) primary air duct, (10) pulverized coal distributor, (11) pulverized coal collector, (12) inner secondary air duct, (13) outer secondary air duct.
1.4. The Prospect of Swirl Coal Combustion Technology In early stage, it was thought that we should use large swirl number and central recirculation zone to have the coal flame stable. We ignored the factor of coal concentration. So, the general and air-staged combustion burners adopt various measures to increase the
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners…
945
swirl number and central recirculation zone. Because the fuel concentration of primary air/coal mixing is little, especially with swirling primary air, most of the pulverized coal is threw off to the low gas temperature region near the secondary air under the effect of centrifugal force. There is a little coal near the high gas temperature central recirculation zone. There is no zone where both the fuel concentration and the gas temperature are high. The quality of coal provided to power plants often fluctuates and is usually low-grade. It is very difficult to have flame stable, especially when the load is low. Xu et al. [12] has experimentally studied the gas flow fields, temperature distribution and gas composition distribution in pulverized coal precombustion chamber, numerically calculated particle trajectories in combustion processes for different particle diameters and presented a new flame stabilization theory - “three high zone” principle. This principle says that if flow carrying over pulverized coal particles forms a high concentrated coal particle zone that is also a high-temperature and appropriate oxygen zone (called “three-high zone ”) at a local region near the burner mouth, this zone can stabilize pulverized coal flame. Three-high zone theory makes us have a good understand of the effect of high fuel concentration. It can give us the reason why the flame stability is bad when both the swirl number and central recirculation zone are large. Air-staged combustion burner can decrease the formation of NOx effectively. The outer secondary air segregates the water-cooled wall from reducing atmosphere in the burner center zone. It can prevent furnace wall and water-cooled wall from high temperature corrosion and slagging propensities, but the carbon-in-ash increases to some extent. High fuel concentration has good flame stability, especially at low load. Since the fuel-lean air/coal mixing carries off some air, the carbon-in-ash increases to some extent. Fuel-rich and fuel-lean combustion technology combines high fuel concentration technology and air staged combustion technology together. Meanwhile, with the fuel-rich and fuel-lean mixings introduced to furnace stratified, the burner intensifies further staged combustion. Some fuel-rich and fuellean combustion technologies have high combustion efficiency, flame stability, no slagging propensities and high temperature corrosion and low NOx emission. It is the prospect of the swirl combustion technology.
2. RADIAL BIASED COMBUSTION SWIRL COAL BURNER 2.1. Concept of Radial Biased Combustion Swirl Coal Burner Qin proposed the radial biased combustion swirl coal burner in 1993 [13]. A fuel concentrator is installed inside the fuel-conveying duct which radially separates the primary air/coal mixing into two jets of different fuel concentrations (Figure 4). The fuel-rich primary air/coal mixing is in the inner annulus and the fuel-lean one is in the outer annulus. Surrounding them is a secondary air jet, which is also divided into two annular parts – the inner swirling secondary air jet and the outer non-swirling secondary air jet. The swirler is made of axial vanes.
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Zhengqi Li
Figure 4. The RBC burner: (1) wall, (2) non-swirl, (outer) secondary air duct, (3) Swirler, (4) swirl (inner) secondary air duct, (5) primary air duct, (6) central pipe, (7) flame igniter, (8) damper, (9) enricher, (10) fuel-lean primary air-coal mixture duct, (11) fuel-rich primary air-coal mixture duct.
2.2. Experimental Research on Pulverized-Coal Concentrator with Cone Vanes 2.2.1. Structure And Parameters of Pulverized-Coal Concentrator with Cone Vanes Figure 5 shows the structure of pulverized-coal concentrator with cone vanes[14]. Under the impact of cone vanes installed inside the primary air duct, the majority of the pulverized coal carried by the primary air is concentrated in the central zone of the primary air duct, with a fraction of coal in the peripheral zone of the primary air. Passing the cone vane, the fuelrich primary air/coal mixing is formed behind the concentrator and the peripheral primary air with a fraction of pulverized coal flows over the cone vanes. The fuel-lean primary air/coal mixing is formed outside the fuel-rich primary air/coal mixing. In Figure 5, R2 is the radius of the primary duct; R1 is the radius of the central pipe; and R is the radius of the outlet of the end vane. The principal parameters of the concentrator include a few of vanes n, the angle of vane β, the setting angle of vane α, the vane length L, the axial projection length of vane L1, the space between vanes L2, the coverage ratio of vanes ε, the blockage radio ψ and the area ratio of the fuel-rich primary air, etc. The coverage ratio of vanes was calculated from the following equation:
ε = H1 H2
(1)
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners…
947
where H1 is the radial projection length of overlap between two vanes, H2 is the radial projection length of vanes (see Figure 5), with m per unit. The blockage radio was calculated using the following equation:
ψ = 1 − f0 f
(2)
where f0 is the area of the end vane outlet (see Figure 5), f is the area of the primary air duct, with m2 per unit. The area fraction of the fuel-rich primary air/coal mixing was calculated from the equation of
fr , where fr (m2 per unit) is the area of outlet of the fuel-rich primary air. f
The performance parameters of concentrator include：the air ratio Ra , the coal concentration ratio Rrl, the enriching ratio Rr, the resistance coefficient ξ. The air ratio Ra is the ratio of the air feed in the fuel-rich primary air/coal mixing to the air fed in the fuel-lean primary air/coal mixing. The coal concentration ratio Rrl is the ratio of the coal concentration of the fuel-rich primary air/coal mixing to that of the fuel-lean primary air/coal mixing. The enriching ratio Rr is the ratio of the coal concentration of the fuel-rich primary air/coal mixing to that of the primary air/coal mixing.
Figure 5. The enricher with cone vanes.
The resistance coefficient was calculated using the following equation:
ζ = ΔP ρuin 2 2g
(3)
948
Zhengqi Li
where ΔP (Pa per unit) is the static pressure difference between the inlet and outlet of concentrator, ρ (kg/m3 per unit) is the density of the primary air, and uin (m/s) is the inlet velocity of the primary air.
2.2.2. Impact and Rebound Phenomena of Particles on Wall of the Cone Vane Figure 6 shows the impact and rebound phenomenon of particles on wall of the cone vane. The velocity of a rebounding particle is determined using the restitution coefficients,
et ( ≡
V2t V ) and en ( ≡ 2 n ), that is measured by experiments. The rebound particle velocity V1t V1n
components, V2 t and V2 n are then calculated by the following manner:
V2t = etV1t
(5)
V2 n = etV1n
(6)
Figure 6. Impact and rebound phenomena of particles on wall.
It should be noted here that the restitution ratios, which are determined experimentally, vary according to the flow velocity, and the combination of particles and target materials. The vane material generally is wear-resistant cast steel or ceramic so that the service life of concentrator is more than an overhaul period (always be four years). The performances of pulverized-coal impacting on wear-resistant cast steel or ceramic are being investigated by us. Results obtained by other researchers can be taken as reference. The expressions for the restitution ratios for sand particles impacting on the 410 stainless steel from Grant and Tabakoff [15] are as following:
et =
V2t = 1.0 − 2.12 β1 + 3.0775β12 − 1.1β13 V1t
(7)
en =
V2 n = 1.0 − 0.4159β1 + 0.4994β12 − 0.292β13 V1n
(8)
The expressions for the restitution ratios for 157-177 μ m silica sand particles impacting on the target materials: 2024 AL, Ti 6-4 and INCO718 from Wakeman and tabakoff [16] are as following:
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners…
et =
V2t = 0.953 − 0.000446β1 + 0.00000648β13 V1t
en =
V2 n = 1.0 − 0.0211β1 + 0.00228β12 − 0.000000876β13 V1n
949
(9) (10)
2.2.3. Structure Optimization for Cone Vane of Pulverized-Coal Concentrator Experiments were carried out on a gas-particle two phase test facility to optimize the structure of pulverized-coal concentrator. The full industrial-scale concentrator studied in the experiments was designed for a 670-tph coal-fired boiler. A scale ratio of 1:3 was employed. Coal ashes from a power plant were used to be the particles. The ratio of the model size to the actual burner size is 1: 3. For the concentrator model, the value of 2 time of R2 is 165 mm, the value of 2 time of R is 65mm, n is 3. The particle concentration is from 0.26 to 0.64kg (coal)/kg(air). Table 1 shows the experiment results. The results indicate that with three vanes, the air ratio is up to 1; the coal concentration ratio is up to 2; the enriching ratio is up to 1.4; and the resistance coefficient is less. The industrial experiments of the concentrator show that with this coal concentration ratio the burner can keep a stable flame. Table 1. Concentrator model structure parameters and experimental results [14] case L1(mm) L2(mm) α(°)
1 20 50 15
2 20 55 13.6
3 20 45 16.7
4 20 40 10
5 20 45 20
6 20 45 25
β(°)
15
15
15
10
25
10
R(mm) Ra Rrl Rr ξ
53.8 1.064 2.56 1.42 2.31
54 1.112 2.49 1.40 2.36
53.7 0.992 2.29 1.39 1.97
66.7 1.08 1.74 1.26 2.34
45.6 0.871 1.70 1.28 2.35
42 0.96 1.77 1.29 2.01
2.2.4. Improved Pulverized-Coal Concentrator with Cone Vanes In order to reduce NOx emissions greatly, the coal concentration ratio should be large, which need to be installed more vanes. With increasing of the number of vanes, resistance of concentrator increases, which lead to pulverized coal plugging in the concentrator and difficulty to set vanes. Structural improvement has been made to separate the end vane and isolation ring between the fuel-rich primary air/coal mixing and fuel-lean primary air/coal mixing. When the fuel-rich primary air/coal mixing passes through the zone between the end vane and isolation ring, the air in it can diffuse into the fuel-lean primary air/coal mixing along radial direction and the pulverized coal still gathers in the fuel-rich primary air/coal mixing under inertia effect. Thus, the improved concentrator achieves a larger concentration ratio with less resistance. Figure 7 shows the improved pulverized-coal concentrator with cone vanes, where x is the distance from the end vane to the isolation ring, H is the length difference between R2 and R1, and Rr is the radius of the inlet of isolation ring.
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Figure 7. The improved enricher with cone vanes.
2.2.5. Structure Optimization and Performance of the Improved Pulverized-Coal Concentrator Table 2 shows the experimental parameters. Table 2. Structure parameters of the improved coal concentrator model [14]
case L1 ( mm )
1
2
3
4
5
6
7
8
9
10
11
50
50
50
50
50
55
60
65
50
50
50
β (°)
20
25
35
40
30
30
30
30
30
30
30
L2
3.0
3.0
3.0
3.0
3.0
3.0
3.0
3.0
2.0
2.5
3.5
0.39
0.48
0.65
0.73
0.56
0.62
0.68
0.73
0.56
0.56
0.56
Ψ
L1
1. Resistance Characteristics (1) Influence of Dip Angle of Vane on Resistance The influence of dip angle of vane β on resistance was determined by experiments in cases 1-4. The expression for resistance coefficient ξ was as following:
ξ = 0.53 + 0.57
β 20
(11)
The expression indicates that with the increasing of dip angle of vane the resistance of concentrator and the angle of air flowing over vanes to the fuel-lean primary air/coal mixing increases and the value of
f0 f decreases. With the value of 0 decreasing, the air velocity f f
increases. It is the main reason of resistance increasing.
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(2) Influence of Vane Length on Resistance The influence of vane length L on resistance was investigated by experiment in cases 5-8. The expression for resistance coefficient ξ was as following:
⎛ l ⎞ ⎟ ⎝ 50 ⎠
ξ = −0.70 + 1.74 ⎜
(12)
The expression indicates that with the vane length increasing the resistance of concentrator increases. With length of vane increasing, the radial projection length of the vanes increases and the flow area of the fuel-rich primary air/coal mixing decreases.
(3) Influence of the Distance between Vanes on Resistance The influence of the distance between vanes L2 on resistance was determined by experiment in cases 9-11. Figure 8a shows the relation between resistance coefficient ξ and normalized distance
L2 . Resistance coefficient decreases and then increases with the L1
normalized distance increasing. With the normalized distance increasing, the air/coal flow area of the fuel-lean primary air/coal mixing increases and the angle of air flowing to the fuellean primary air/coal mixing. It results in the resistance coefficient decreases. With the normalized distance increasing further, eddies behind the vanes becomes large. It results in the resistance increases. The experiment indicated the minimum resistance coefficient ξ is obtained when normalized distance
a
L2 is 2.5. L1
b
Figure 8. Influence of normalized distance between vanes (a) and blockage ratio (b) on resistance coefficient [11].
(4) Influence of Blockage Radio on Resistance The blockage radio is a parameter which synthetically shows the influence of the angle of vane, the vane length, the number of vanes and air flow areas of the fuel-rich and fuel-lean primary air/coal mixings. Figure 8b shows the relation between resistance coefficient ξ and
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blockage radio ψ. The experimental result indicates that the blockage radio could express the variation of resistance well. In the cases that the blockage radio ψ is less than 0.6, the resistance coefficient increases slowly while the blockage radio increases. In the cases that the blockage radio ψ is more than 0.6, the resistance coefficient increases remarkably while the blockage radio increases. Thus, considering the reduction of resistance of the concentrator, it is recommended that the blockage radio for concentrator design should be less than 0.6. The experiment results indicate that the resistance of the improved coal concentrator reduces by 50% compared with the former concentrator. The influence of distance between the end vane and the isolation ring on distribution of air flow. In case 6, the distribution of air axial velocities at the inlet of the isolation ring with different x (see Figure 7) were measured. Figure 9 shows the results of measurement, where
U m is the axial velocity of air flow in the primary air duct.
Figure 9. Influence of distance from the end blade to the isolation ring on distribution of air axial velocities at the inlet of the isolation ring [11].
In the radial direction, the air axial velocities of the fuel-rich primary air/coal mixing is larger than that of the fuel-lean primary air/coal mixing. The distribution of air axial velocities becomes flat while x increases. At x=0.23H, partial region is in the eddy current zone.
fr X Figure 10 shows the influence of normalized area f and normalized distance H on the air ratio Ra. For radial biased combustion burner, it is recommended that the air ratio Ra should be in the range from 0.75 to 1. The influence of distance between the end vane and the isolation ring on radial separation performance.
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Figure 10. Influence of fr/f and X/H on the air ratio [11].
Figure 11. Influence of fr/f and X/H on the coal concentration ratio [11].
fr X f Figure 11 shows the influence of normalized area and normalized distance H on the X coal concentration ratio. With H from 0 to 0.5, the minimum coal concentration ratio is X H increasing. The obtained. The coal concentration ratio increases and then decreases with X maximum coal concentration ratio is achieved while H is 1. The phenomenon is caused by
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the inertia effect of the pulverized coal. In the region near the outlet of the end vane, the pulverized coal still move into the zone of the fuel-rich primary air/coal mixing under the X inertia effect. As H is larger than 1, the coal concentration in the zone of the fuel-rich primary air/coal mixing reduces because the pulverized particles diffuses into fuel-lean primary air zone in the radial direction.
fr X We should choose appropriate values of H and f to achieve the appropriate air ratio fr X and coal concentration ratio. When H is 1 and f is in the range from 0.3 to 0.4, the air ratio is in the range from 0.7 to 1 and the coal concentration ratio is in the range from 5 to 8.
2.3. Effect of Structure Parameters on Gas/Particle Flow Near the Burner Region 2.3.1. Effect of Angle of Secondary Air Swirling Vane on Characteristics of Isothermal Flow Issuing from the Radial Biased Combustion Burner A number of axial fixed swirling vanes are installed in the secondary air duct of radial biased combustion burner. The vanes were curved according to a special profile line and had an angle of β with burner axis. After passing through the vanes, the secondary air rotates and develops into a swirling jet at a certain swirling momentum at the secondary air outlet. For adjusting the swirl number of the secondary air near the burner outlet, the secondary air is divided into two flows, a non-swirling outer secondary air flow and an inner swirling secondary air flow. The swirl number can be adjusted by controlling the ratio of inner secondary air to outer secondary air. Some relations between vane profile and design parameters have been presented in document [17]. Some studies have shown that to keep the length of the straight section at the vane outlet and the bending radius of the vanes at appropriate values, the non-dimensional height of the vanes should range from 1.5 to 1.9. On the condition that the number, angle and cover ratio of vanes remain constant, an optimized vane profile can be obtained by choosing an appropriate non-dimensional vane height. And a reasonable design of the shape of the vane can make the secondary air flow out into the furnace at the angle that is the same as the angles of the vanes. The angle β of vanes influences deeply on the characteristics of swirling jet in the near burner region. A cold flow experiments in a small-scale burner were carried out to investigate the effect of the angle of the vane (the experimental angles are 55°, 58°, 60° and 65°) on the characteristics of the flow issuing from the burner [18]. The original burner is used on a coal-fired 670-tph utility boiler. The ratio of the small model to the original burner is 1: 3. An IFA300 constant-temperature anemometer system with a single-sensor hot-film probe was used to measure the mean velocities and turbulent parameters of swirling jet issuing from the burner by method of rotating the probe. Ribbons tied to a coordinate-frame were used to measure the airflow direction in the flow field. Table 3 shows the experimental parameters.
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Table 3. Experimental parameters for different swirling vane angles Primary air ratio, %
Secondary air ratio, %
Inner Swirl secondary air ratio, %
Velocity of the primary air, m/s
Axial velocity of the secondary air, m/s
Reynolds number at the burner outlet
19.5
80.5
85
8.5
12.0
1.6×105
1. Swirl Numbers of Airflow Issuing from the Burner at Different Swirling Vane Angles Assuming that the airflow passing through the vanes is idealized and non-viscous, the angle between the airflow direction and the burner axis is β . Thus the related expression for the tangential velocity w and the axial velocity u was w = u tan β . Ignoring the influence of the static pressure on the axial momentum, the swirl number of secondary air S can be calculated as follow: R
S=
∫u
2
R
tan β r dr 2
2 2
= tan β
0
R
∫ u r dr
∫ u rd dr 2
0
0
0 R
∫ u rd dr
= tan β f ( u, R, d 0 )
2
(13)
0
0
where R is the divergent radius of airflow at the burner outlet and r is the radius of the measurement point. In the swirling jet, the secondary air takes most of the part, thus the swirl number of swirling jet issuing from burner is determined by the tangent of swirling vane angle. As shown in Equation (12), the swirl number rises with the increase of β . Comparison between the experimental data of the swirl number and tangent of swirling vane angle is shown in Figure 12, and the value of f ( u, R, d 0 ) is approximately set to 1.
2. Influence of the Swirling Vane Angle on the Flow Resistance to the Secondary Air Because the ratio of the non-swirling outer secondary air is relatively small (no more than 25%), the main resistance to the secondary air occurs when the swirling secondary air passes through the swirling vanes. The resistance to the inner secondary air passing through swirling vanes includes frictional resistance and local pressure loss. The frictional resistance h f 1 was calculated from the following equation:
h f 1 = k1
ρu 2
(14)
2g
where k1 is the frictional resistance coefficient which is determined by surface roughness, length and air humidity of the vanes,
ρ ( kg / m3 ) is air density.
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Figure 12. Effect of
β
on swirl number and resistance.
When the airflow passes through the swirling vanes whose angle is increases from u to
ρ , the velocity
u , which leads to a local pressure loss. The local pressure loss h f 2 cos β
can be calculated as follow:
hf 2
ρ ⎛ u2
(15)
⎞ ρ u 2 tan 2 β = k2 − u ⎟ = k2 ⎜ 2 g ⎝ cos 2 β 2g ⎠ 2
where k2 is the coefficient. It stays constant in a certain vane structure. Then, the resistance to the inner secondary air passing through swirling vanes can be calculated as follows:
hf = hf 1 + hf 2 = where
ρu 2 2g
( k1 + k2 tan 2 β ) = ξ
ρu 2
(16)
2g
ξ is the resistance coefficient which can be calculated from the expression
ξ = k1 + k2 tan 2 β . When the swirling vane angle β is ＞45°, k1 is relatively small and can be ignored, then ξ is positively proportional to the square of the tangent of β . Assuming that the value of k 2 is 1, the relation between ξ and β should follow the curve shown in Figure 12. The resistance coefficient is small when
β is ＜50°. When β ranges
β is above 70°, the resistance coefficient rises sharply with increase of β . So, the increase of β not only enlarges the length of central from 50° to 65°; it begins to increase. When
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recirculation zone, but also increases the resistance to the secondary air simultaneously. It is suggested that β should not be over 70° in the design of swirling vanes.
3. Influences of Swirling Vane Angle on the Flow Field Structure and the Mean Velocity Distribution of the Swirling Jet Issuing from the Burner Table 4 shows the length LCR 2 and maximum diameter dCR 2 of the central recirculation zone of the swirling jet issuing from the burner. d is the diameter of the none-swirling secondary air cone. When
β increases from 55° to 65°, dCR 2 increases by 20% and LCR 2
increases by 30%. The ratio of the maximum mass flux of the recirculation air in the central recirculation zone to the mass flux of primary air (defined as the maximum normalized recirculation ratio) is shown in Table 4. The maximum normalized recirculation ratio can basically shows the mass flux of the recirculation flow in the central recirculation zone because the mass flux of primary air has no remain constant. While β is ≥60°, the maximum normalized recirculation ratio is up to 2, which shows that the recirculation gas can supply enough heat for the ignition of fuel-rich primary air/coal flow and satisfy the flame stable combustion for low-grade coal. Table 4. Influence of swirling vane angle on the length of central recirculation zone and maximum normalized recirculation ratio
β
55 °
58 °
60 °
65 °
LCR 2 / d
1.49
2.0
2.0
2.0
dCR 2 / d
0.8
0.86
1.0
1.0
Maximum normalized recirculation ratio
1.160
1.261
1.909
1.931
The distribution of the mean axial and the tangential velocities at different
β (55° or
60°) of the swirling jet are shown in Figure 13, where x is the distance from the burner outlet to the velocity point, U0 is the mean velocity of the airflow at the outlet of the burner. As shown in Figure 13a, near the burner outlet ( x / d = 0.0 ), the axial velocities have two peak values along the radial direction. The higher one is the velocity peak of the secondary air; the lower one is the velocity peak of the primary air. In the central pipe of the burner, there’s no air fed into the furnace, so the axial velocity is low near the outlet of the central core, which helps to form the front stationary point of central recirculation zone. The central core and the cone between the primary air and swirling secondary air (see Figure 4) have guide effect on the primary and secondary air. Also, large turbulent mass exchange occurs because of the great velocity gradient between primary air and secondary air. Thus, the primary air and the secondary air mix rapidly and the velocity peak of primary air disappears at the crosssection x / d = 0.25 , which shows that the primary air has well mixed with the secondary air. At a large swirling vane angle, the velocity peak of the jet decays rapidly.
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Figure13. Profiles of axial mean velocities (a) and tangential mean velocities (b) in the jet with different swirling vane angles.
When
β is set to 55 ° , the swirl effect of the jet and the centrifugal force of fluid
micelles are weakened. Most of the air is concentrated in the central zone of the jet and the flare angle of the jet reduces. Therefore, the length of central recirculation zone became short. As shown in Figure13b, at different angles of β (55° or 60°), only one tangential velocity peak appears. The tangential velocity is low in the central recirculation zone and in the flow field near the primary air outlet because the primary air is non-swirling and the airflow in the central recirculation zone is mostly the axial backflow. Influenced by the swirling vanes, the maximum tangential velocity appears in the airflow field near the secondary air outlet. As the swirling vane angle increases, the maximum tangential velocity and the swirl number rise, and the tangential velocity decays rapidly. It shows that the primary and secondary air is mixed intensely. Furthermore, the tangential velocity decays more rapidly than the axial velocity and in highly swirling flow the tangential rotation disappears soon because of the large turbulent mixing. At the cross-sections x / d ≥ 1.0 , the tangential velocity of the jet falls down to zero, and the flow becomes wholly axial. The differences between the two radial velocities with different β s are very few.
4. Turbulent Stress Distribution in Swirling Flow Field at Different Vane Angles Figure 14 shows the spatial distributions of normalized turbulence fluctuating root-meansquare (RMS) velocities and turbulence normal stresses at different vane angles. Figure 14a shows that the turbulent fluctuating RMS velocities are low in the region of central
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners…
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recirculation zone and jet boundary. It reaches a peak value in the interface of recirculation zone and the mainstream zone.
Figure 14. Profiles of normalized root - mean - square velocities and normalized turbulent stresses with different swirling vane angles.
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As the vane angle increases, the peak value of the turbulent fluctuating velocity moves outward along radial direction and the turbulent fluctuating velocitoes at the outlet increas but decay rapidly. At x / d ≥ 0.5 , the turbulent fluctuating velocities at a larger vane angle are already less than that at a smaller vane angle. Distribution of turbulence normal stress is nonhomogeneous. It is low in the region of central recirculation zone and the jet boundary and reaches a radial maximum value in the region near the boundary of recirculation zone and the region of the mainstream zone of secondary air.. However, , the turbulent normal stress in the region of swirl burner outlet is not the maximum in the whole flow field. As the flow expands downstream, the turbulent energy produces continually. At x / d = 0.25 − 0.5 , the turbulent normal stress reaches a maximum value and gradually declines afterwards. Thus, this region with intense turbulent fluctuation is advantageous for pulverized-coal combustion. In practical operation, the radial biased combustion swirl burner increases the pulverized-coal concentration in this region, which improves the ignition of air/coal mixing. It also improves the flame stability and combustion intensity. Turbulent normal stress is obviously anisotropic. '2
'2
The maximum values of axial normal stress u and tangential normal stress w are high, which indicates that the turbulent flow fluctuates more intensely in the two directions. '2
Meanwhile, the normal stress v in the radial direction is smaller than stresses those in the other two directions near the burner outlet, and gradually increases downstream. As the swirling vane angle increases, the turbulent fluctuation intensity of airflow obviously rises at the outlet and the turbulent mixing is enhanced. The maximum turbulent normal stresses in the three directions are raised more than two times. The higher turbulent fluctuation intensity is advantageous for the burning of the air/coal flow. The intense mixing in the early stage of the jet quickens the dissipation of turbulent energy; so the turbulent energy becomes lower in the later stage of the jet. At x / d = 1.0 , u and w at the smaller. '2
'2
at larger vane angle are less than those
5. Influence of Swirling Vane Angle on the Mixing Characteristics of Swirling Jet Figure 15 shows the ratio distribution of the fuel-rich primary air flow (Rrp) and the whole primary air flow (Rp) at different vane angles by the temperature tracing method. The fuel-rich primary air ratio at a certain point is the ratio of the fuel-rich primary air mass flux to the total mass flux at the same point in the flow field. The Primary air ratio can be obtained in the same way. The results show that the peak of the fuel-rich flow ratio reaches 40% near the outlet of burner. The peak locates at the cross-section r / d = 0.25 which is close to the central recirculation zone near the boundary of central recirculation zone, the ratio of the fuelrich primary air flow remains high, which is advantageous for the heat and mass transfer between the fuel-rich primary air /coal mixing and the high temperature gas in the recirculation zone. The peak ratio of the fuel-rich primary air flow does not fall until the flow reaches the cross-section x / d = 0.5 . The high ratio in the early combustion of the fuel-rich primary air flow can improve the flame stability, and lower the emission of fuel-NO by forming a reducing atmosphere. As the vane angle increases, the peak ratio of the fuel-rich primary air flow moves outwards in the radial direction and the mixing of the fuel-rich primary air flow and the gas in central recirculation zone is weakened. This is because as the swirl number of secondary air
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increases, the divergent angle of jet rises and the primary air expands outward under the driving of secondary air.
Figure 15. The ratio distribution of fuel-rich primary air Rrp （a） and primary air R p （b） at different vane angles.
Figure 15b shows the ratio distribution of the fuel-rich primary air flow which shows the mixing of the primary and secondary air. In the region near the outlet ( x / d = 0.25 ), the influence of the vane angle on the fuel-rich primary air ratio is not significant, and the maximum ratio can reach about 80%. The increase of vane angle will enhance the mixing of primary air and secondary air in the downstream and uniform the distributions of primary air ratio uniform in the whole flow field. Figure 16 shows the axial decay of the maximum ratios of the fuel-rich primary air flow, Rmrp, at different vane angles. In the region ranging from x / d = 0.25 to 1, when the vane angle becomes larger, the mixing intensity of the primary and secondary air was enhanced and the maximum ratio of the fuel-rich primary air flow declines much more rapidly. Also the distance, at which the ratio of the fuel-rich primary air flow is kept high, is shortened. At the downstream of the cross-section x / d = 1.0 , the mixing of the primary and secondary airs is already uniform. The ratio of the mixing flow flux to the entrance flux is 1：4. It indicates that the mixing of the airflow at the outlet of the swirl burner is intense, and the distance for air-flow to be uniformly mixed is short. The increase of the swirl number can strengthen the mixing of primary and secondary air. The gas/particle two-phase experiment with PDA shows a remarkable phenomenon that the diffusion velocity of particle-phase is slower than that of the gas phase [19]. In the region near the recirculation zone, the diffusion
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velocity of pulverized-coal particle obtained from the two-phase experiment is slower than that of fuel-rich primary air ratio obtained from the single phase experiment.
Figure 16. The axial decay of the maximum ratio of the primary air Rmrp at different vane angles.
As mentioned above, as the vane angle increases, the length of central recirculation zone and the divergent angle of jet increases as well. The normalized backflow ratio and turbulent fluctuation of airflow increase as well. It is advantageous for the coal flame stability. But when the vane angle increases to a certain extent, the resistance to the secondary air become greater, and the primary air and secondary air mixed much earlier. The peak value of the fuelrich primary air ratio moves outwards in the radial direction. The particle load of the fuel-rich primary air declines near the recirculation zone. It is disadvantageous for the ignition of air/coal flow. So, the vane angle should be chosen in the range between 60 ° and 65 ° .
6. Conclusion Swirl number S is proportional to the tangent of vane angle β . As the vane angle β increases, the swirl number becomes higher. Resistance coefficient of the secondary air is proportional to the squared value of vane angle β . When the vane angle is over 70 ° , the quick increase of local resistance coefficient of the vane will make the resistance to the secondary air too large. When the vane angle increases, the tangential velocity of the flow at the outlet rises. The axial velocity peak moves outward in the radial direction. The divergent angle of jet and the length of central recirculation zone increase. The recirculation rate also increases to supply enough heat for the ignition of the fuel-rich primary air/coal mixing. When the vane angle β increases, the turbulent fluctuation velocities increase also, and its maximum value moves outwards in the radial direction. Distribution of turbulent normal stress is non-homogeneous and anisotropic in the airflow near the outlet. At the interface of the mainstream and the recirculation zone which ranges from x / d = 0.25 to 0.5, the
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turbulent normal stress has a maximum value. The intense turbulent fluctuation in this region is advantageous for the combustion of pulverized-coal. When the vane angle increases, the turbulent normal stresses in the three directions obviously rises. The maximum value can be 2 times as large as before. It shows that the turbulent fluctuation and mixing are strengthened. And the mixing of jet also is also strengthened with the increase of vane angle.
2.3.2. Effect of Division Cone Angles between the Fuel-Lean Primary Air/Coal Mixing and the Swirling Secondary Air on Particle-Laden Flows Near the Burners Figure 17 shows burner cones. The cone between the fuel-lean primary air/coal mixing and the swirling secondary air has the influence on the secondary air flow direction, the secondary air velocity and the mixing of primary and secondary airs. A two-dimensional particle dynamics anemometer was used to measure gas/particle flow characteristics with division cone angles of 10°, 22.5°, and 30° [20]. The size ratio of the burner model to the utility burner in a 670-tph coal-fired boiler was 1: 6. The particles, up to 8μm, were used to measure the airflow velocity and turbulence, whilst particles of diameter in the range from 10 to 100μm were to represent the particle (solid) phase flow.
Figure 17. Burner cones: 1. Core, 2. the cone between the fuel-rich and the fuel-lean primary air/coal mixtures, 3. the cone between the fuel-lean primary air/coal mixture and the swirling secondary air, 4. the cone between the swirling and non-swirling secondary air, 5. non-swirling secondary air cone.
1. Effect of Cone Angles of Air and Particle Velocities Figures 18, 19 and 20 show profiles of mean axial velocities. With the increase of the cone angle, the positions of peak values of air and particle mean axial velocities move outward along the radial direction, the peak values reduce and the jet decay is faster. It shows that the increase of the cone angle strengthens the secondary air radial diffusion. Otherwise, with the increase of the cone angle, the divergent angle of the jet increases, and then the cross-section of the jet enlarges. It results in the decrease of air and particle mean axial velocities.
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Figure 18. Profiles of air and particle mean axial velocities with the cone angle of 10°.
Figure 19. Profiles of air and particle mean axial velocities with the cone angle of 22.5°.
Figure 20. Profiles of air and particle mean axial velocities with the cone angle of 30°.
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Figures 21 and 22 show the effect of cone angles ( α1 ) on the maximum diameter of central recirculation zone ( d CR 2 ) and the air divergent angle, where r is the distance between the burner center line and the boundary of the jet. The air divergent angle of jet is the air semi-velocity divergent angle which is the angle formed by two air semi-velocity boundaries. The air semi-velocity boundary is the line where the mean axial velocity is half of the maximum mean axial velocity at a cross-section. With the increase of cone angle, d CR 2 and semi-velocity divergent angle increases. The reason is as follows: the larger the cone angle is, the more swirling secondary air diffuses outward and the larger the swirling secondary air radial momentum are. Furthermore, the larger the cone angles are, the larger the area of the fuel-lean primary air is, and the less the primary air velocity is. The increase of the central recirculation zone size increases the recirculation flux of the high-temperature gas. It is advantageous to coal combustion.
Figure 21. Effect of cone angles on the maximum diameter of central recirculation zone.
Figure 22. Effect of cone angles on air semi-velocity boundary.
Figures 23, 24 and 25 show profiles of mean tangential velocities. Profiles of air and particle mean tangential velocities with different cone angles are similar. With the increase of cone angle, the positions of air and particle mean tangential velocities move outward along
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the radial direction. The mean tangential velocities increase slightly because the increase of area of swirling secondary air outlet.
Figure 23. Profiles of air and particle mean tangential velocities with the cone angle of 10°.
Figure 24. Profiles of air and particle mean tangential velocities with the cone angle of 22.5°.
Figure 25. Profiles of air and particle mean tangential velocities with the cone angle of 30°.
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Figures 26, 27 and 28 show profiles of air and particle axial Root Mean Square (RMS) velocities. Figure 29, 30 and 31 show profiles of air and particle axial RSM velocities. Air and particle axial RSM velocities are similar to air and particle tangential RSM velocities. The RSM velocities are less in the central recirculation zone. They are larger near the boundary of central recirculation zone and in the region of swirling secondary air where there are larger shear layers. With the effect of airflow diffusion and turbulent transport, the air and particle axial and tangential fluctuation velocities decrease. At x / d = 0.11~0.51, the air and particle axial and tangential fluctuation velocities with
α1 =30° are larger than that with
α1 =10°. It shows that with the cone angle increasing, the air and particle velocity gradient between primary air and secondary air becomes larger. The increase of air and particle turbulent transport ability strengthens the air and particle momentums and mass transport between air/particle flows. It can increase coal combustion and flame propagation velocities. So, it is advantageous to the ignition and combustion of pulverized coal.
Figure 26. Profiles of air and particle axial RMS velocities with the cone angle of 10°.
Figure 27. Profiles of air and particle axial RMS velocities with the cone angle of 22.5°.
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Figure 28. Profiles of air and particle axial RMS velocities with the cone angle of 30°.
Figure 29. Profiles of air and particle tangential RMS velocities with the cone angle of 10°.
Figure 30. Profiles of air and particle tangential RMS velocities with the cone angle of 22.5°.
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Figure 31. Profiles of air and particle tangential RMS velocities with the cone angle of 30°.
2. Effect of Division Cone Angles on Particle Size Distribution The particle mean diameter (d10) is the average of diameters of particles. Figure 32 shows profiles of particle mean diameter. The distributions of particle size with different cone angles are similar. Because the primary air is non-swirling, the large particles go downstream under the inertia effect, and the little particles are easy to diffuse into the secondary air and the central recirculation zone by the driving of airflow. Therefore, in the region x / d =0.11~0.51, the particle mean diameter is little in the central recirculation zone and near the wall, but is larger outside the central recirculation zone. With the jet developing, particles gradually mix each other. The distribution of particle mean diameter is to be uniform.
Figure 32. Profiles of particle mean diameter with different division cone angles.
3. Effect of Division Cone Angles on Distribution of Particle Concentration Figures 33 and 34 show profiles of number concentrations for particle size in the range from 0.5 to 100μm, where Cn is the number concentration at a given point and Cmax is the largest number concentration in the same cross section.
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Figure 33. Profiles of particle number concentration with different division cone angles.
Figure 34. Profiles of particle number concentration with the cone angle of 22.5°.
There is a peak value of the particle number concentration at every cross-section at different cone angles. The peak value of particle number concentration with the cone angle of 10° is closer to the central recirculation zone than that with the cone angle of 30°. The particle number concentration with the cone angle of 10° is less than that with the cone angle of 30° near the wall at x / d = 0.11~0.51. This is because that the cone at the angle of 10° delays the radial diffusion of primary air and makes more particles stay at the central zone. The particle number concentration is large in the central zone. With the jet developing, the particle number concentration becomes uniform radially behind x / d = 1.
4. Effect of Division Cone Angles on the Mixing Characteristics of Primary Air and Secondary Air Measurements were performed on a single-phase test facility to investigate the mixing characteristics of primary air and secondary air [21]. Figure 35 shows profiles of the maximum ratio of fuel-rich primary air with different cone angles. When the cone angle is
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners… less, for example
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α1 =31.0°, the mixing of fuel-rich primary air and other airflows is delayed
and the maximum ratio of fuel-rich primary air is larger in the flow-field because the secondary air is driven outward. When the cone angle increases more, for instance α1 =37.1°, the mixing of primary air and secondary air is weakened in the early stage but strengthened in the latter stage. Compared with other two cone angles, the maximum ratio of the fuel-rich primary air with the cone angle of 37.1° declines more quickly. It shows that the mixing of primary air and secondary air in the latter stage is larger. Behind x / d=1, the mixing of fuelrich primary air is over.
Figure 35. The axial profiles of the maximum ratio of fuel-rich primary air with different cone angles.
5. Conclusion (1) With the increase of division cone angle, the secondary air is driven outward along radial direction; and the central recirculation zone becomes larger. Meanwhile, the positions of the peak value of fuel concentration move outward along radial direction, and the particle concentration reduces near the central recirculation zone. (2) With the increase of the division cone angle, air and particle axial and tangential fluctuation velocities become larger near the burner outlet. (3) With the increase of the division cone angle, the mixing of primary air and secondary air is delayed in the early stage.
2.3.3. Effect of The Length of the Division Cone between the Swirling Secondary Air and the Fuel-Lean Primary Air/Coal Mixing on Characteristics of Isothermal Airflows Near the Burner Region Experiments were carried out on a single-phase test facility to investigate the effect of the increase the length of the division cone between the swirling secondary air and the fuel-lean primary air/coal mixing on isothermal airflow issuing from the burner model [14]. The size ratio of the burner model to the utility burner in a 670-tph coal-fired boiler was 1: 3. While
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the other structural parameters of the burner modal is invariable, the ΔL for experiments are 6.8mm, 13.5mm, 20.3mm and 27mm, namely the ΔL / d are 0.018, 0.036, 0.055 and 0.073. The boundary of the air (particle) jet is defined as the edge at which the air (particle) axial mean velocity is 10% of the air (particle) maximum mean axial velocity .Up to a downstream jet distance of x / d =0.52, jet borders of the air and particle are almost a straight line [22]. In order to show the jet development, the divergent angle of the air (particle) jet is defined as the angle between the air (particle) jet borders at the section from x / d =0.1 to 0.52. Figure 36 shows the effect of the increase of the cone length on the size of central recirculation zone and the divergent angle of jet. The increase of the cone length enhances the outward diffusion of secondary air, and enlarges the size of central recirculation zone and the divergent angle of jet. While ΔL is 27mm, namely ΔL / d is 0.072, the jet issuing from the burner model shows instability: the close jet, which has a stable central recirculation zone, becomes an open jet, which has no central recirculation zone, with a little disturbance. Figures 37 and 38 show the effect of the increase of the cone length on the ratio and the maximum ratio of primary air. With the increase of the cone length, the maximum ratio increases at x / d =0.25-1. It shows that the mixing of primary air and secondary air weakens. At x / d >1.0, the increase of the cone length has a little influence on the mixing of primary air and secondary air. In the region of burner outlet, the large ratio of primary air can make the coal concentration of the primary air/coal mixing large. It is advantageous to the ignition of pulverized coal. And the delay of mixing of primary air and secondary air is advantageous to reducing the fuel NOx formation in the beginning of coal combustion. By consideration of the above results, ΔL should be in the range from 0.018d to 0.055d.
Figure 36. Effect of the increase of the cone length on the size of central recirculation zone and the divergent angle of jet ( α ).
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Figure 37. Effect of the increase of the cone length on the characteristics of mixing of primary air and secondary air.
Figure 38. Effect of the increase of the cone length on the maximum ratio of primary air.
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2.3.4. Effect of the Angle of Non-Swirling Secondary Air Cone on Characteristics of Isothermal Airflows Near the Burner Region The non-swirling secondary air cone is the outmost cone of the burner (see Figure 17). With angles of non-swirling secondary air cone ( α nons ) of 0°, 10° and 30°, experiments were carried out on a single-phase test facility [21]. Figure 39 shows the maximum diameter and maximum normalized air recirculation rate of the central recirculation zone. The maximum diameter increases linearly with the increase of α nons . While α nons changes from 0° to 30°,
dCR 2 / d changes from 0.73 to 0.84, increasing by 15.6%. The maximum normalized air recirculation rate ( qrp ) also increases with the increase of
α nons . While α nons changes from
0° to 30°, qrp changes from 0.36 to 0.54, increasing by 47%. Figure 40 shows the air semivelocity lines of jet with different increases linearly with increase of
α nons . The air semi-velocity divergent angle ( α1 2 )
α nons . While α nons increases from 0° to 30°, the α1 2
increases by 30%. The linear expression was as following: α1 2 = 0.42α nons + 35.69
(17)
The increase of the cone angle enhances the radial guidance to the non-swirling secondary air and reduces the restriction of non-swirling secondary air against the swirling secondary air. It makes the swirling secondary air diffuse more rapidly along the radial direction under its centrifugal effect. The experiments for mixing characteristic of primary air and secondary air show the change of angles of non-swirling secondary air cone just has a large influence on the flow characteristic of secondary air, but has a little influence on the mixing of primary air and secondary air. It is suggested to increase the angle of non-swirling secondary air cone. It is advantageous to the low grade coal combustion with large central recirculation zone.
Figure 39. Effect of the angle of non-swirling secondary air cone on the maximum diameter and maximum normalized recirculation rate.
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2.3.5. Influence of Two Burner Core Geometries on Particle-Laden Flows Near Swirl Burners A three–dimensional particle-dynamics anemometer (PDA) made by Dantec was used in this study. We get the total number concentration (number of particles per unit measurement volume) and particle volume fraction (the percent volume of dispersed phase to carrier phase). The overall uncertainties in measured values of the particle diameter and the particle concentration are typically 4 % and 30 %, depending on optical configuration; the mean velocity, typically 1 %. The measurable range for velocities is –500 m/s to 500 m/s, depending on optical configuration; for particle diameters, 0.5 to 1000 μm, respectively. The experiments were done on a test facility [19]. Titanium dioxide powders were fed via the electromagnetic oscillating feeder into the main air duct which sent the central air, the primary air and the secondary air between the wind box and the blower, to trace the air flow. The particle mass flow rate was 0.12 kg/hr, and particle diameters were smaller than 10 μm. Glass beads were fed via another feeder into the fuel-rich primary air/coal mixing duct. The particle density of the glass beads was 2500 kg/m3. The particle-size distribution obtained by the PDA is shown in Figure 41. The particles between the diameters from 0 to 140 μm amounted to 98.4 %. Therefore, the particle size distribution was almost the same as that of pulverized coal. Particle density varies greatly with respect to coal types, and generally speaking is about 2200 kg/m3 for bituminous coal. The characteristics of glass beads are similar to those of pulverized bituminous coal. The principal idea in the present study is to use the phase information to distinguish between signals from seeding particles and dispersed-phase particles. A necessary condition for allowing seed measurements by the phase-Doppler method are that the seeding particles are spherical and the refractive index must be identical.
Figure 40. Air semi-velocity lines of jet with different angles of non-swirling secondary air cone.
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Otherwise, the PDA may catch the particles passing through the measurement volume with low efficiency. Glass beads can meet these requirements. The spherical characteristic of the titanium dioxide particles is not the same as that of the glass beads, and the refractive index of the titanium dioxide particles is different from that of the glass beads. Because the smaller particles are lost during the experiment, it is difficult for the PDA to detect more particles, whose diameters are smaller than 10 μm, to obtain the information of the gas-phase. We tried to use the titanium dioxide particles. Compared with the case without the titanium dioxide particles, the PDA caught smaller particles in the case with the titanium dioxide particles. So the titanium dioxide particles were used although they are not quite adequate for phase-Doppler measurements.
particle number %
15
10
5
0 0
83.79
167.58
251.37
335.16
418.95
Particle mean diameter (μm)
Figure 41. Particle size distribution.
Figure 42 shows the burner model with the common core of which diameter is 63 mm. Figure 43 shows the sawtooth shaped core of which diameter is 57 mm and the height of the tooth is 10 mm. The following definition of the particle swirl number Sp and the air swirl number S are used:
Sp = ∫
do / 2
0
S=∫
do / 2
0
⎛1 ⎝2
do / 2
ρ p ω p Qr 2 dr ⎜ d ∫ 0 ⎛1 ⎝2
do / 2
ρωur 2 dr ⎜ d ∫ 0
⎞ ⎠
ρ p u p Qrdr ⎟ ⎞ ⎠
ρu 2 rdr ⎟
(18) (19)
where: do is test section furnace diameter, m; ρp is the glass bead material density, kg/m3; ωp, up are the mean tangential, axial velocities of the particles with the size distribution in the range from 0.5 to 100 μm, m/s; Q is the dispersed particle volume flux with the size distribution in the rang from 0 to 100μm in the measured location, m3/（m2 · s）; and ω, u are the air tangential, axial velocities, m/s. Table 3 shows experimental parameters. During
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the experiment, the total secondary air mass flow rate and primay air parameters were kept constant. The air mass flow rate was controlled within an accuracy of 5 %. Burners with the sawtooth shaped and common cores have the same primary air exit area.
Figure 42. The burner model (the dimensions are in mm). 1. central air 2. primay air and glass beads 3. swirling secondary air 4. non-swirling secondary air.
Figure 43. The structure of the sawtooth shaped core.
The particles (titanium dioxide and glass beads), up to 8 μm, were used to measure the airflow velocity and turbulence whilst particles (glass beads) of the diameter in the range 10 to 100 μm were to represent the particle (solid) phase flow. From the view point of modeling, particles whose diameters were between 0.5 and 100 μm were used for particle volume flux and number concentration and volume fraction analysis. Particle volume flux was defined as particle volume crossing a unit area of the measurement volume per unit of time.
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Air/particle flow characteristics were measured in sections of x/d = 0.1, 0.22, 0.52, 1.02, 2.02, 3.32.
1. Velocity Figure 44 shows profiles of the gas/particle mean axial velocities. With the sawtooth shaped and common cores in the cross sections from the burner jet to x/d = 1.02, there are two peak values in profiles of air/particle mean axial velocities. The peak zone near the burner center is the primay air and particle mixing flow zone, and another peak zone near the wall is the secondary air flow zone. In the x/d = 0.1 cross section, the peak value near the burner center is larger than that near the wall. With the primay air and particle mixing diffusing into the secondary air, the peak value near the burner center gradually reduces. On the other hand, the peak value near the wall gradually increases. As the jet stream developed, the secondary air diffuses into the wall zone, and the velocity peak value also gradually reduces. And its radial position also gradually moves toward the wall. The profiles of gas/particle mean axial velocities are almost independent of the cone structures. The central recirculation zone and near wall recirculation zone of the burner with the sawtooth shaped core are the about same as those of the burner with the common cone. The profiles of the gas/particle axial fluctuation velocities, the gas/particle mean tangential and fluctuation velocities are almost independent of the cone structures. Velocity (m/s) a
400
-5 0
5 10 15
0
5 10 15
0
5
10
0
5
10
0
5
0
5
350 300 250 200 150
Radius (mm)
100 50 0 -50 -100 -150 -200 -250 -300
b
-350 -400
x=17.7 mm x=39.4 mm x=92.5 mm x/d=0.1 x/d=0.52 x/d=0.22 particle (the common core) − air
x=181 mm x=358 mm x=588 mm x/d=1.02 x/d=2.02 x/d=3.32 particle (the sawtooth shaped core)
Figure 44. Profiles of air (a) and particle (b) mean axial velocities with different cores.
Figures 45 and 46 show profiles of mean radial velocities and radial fluctuation velocities. Although the primary air/coal mixing was non-swirling, due to the angle of the cones, mean radial velocities were larger in the primay air and secondary air flow zone (the radius r > 28.2 mm) at the section of x/d = 0.1. They were smaller in the wall zone. There was one peak value in the profiles. With the jet development, the mean radial velocities gradually decreased. At the sections of x/d = 0.1 and 0.22, with the sawtooth shaped core the particle
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mean radial velocity is smaller than the air mean radial velocity in the primay air and secondary air main flow zone. That make lots of particle remain in the central zone of the burner. Velocity (m/s) -10 0 10 20 30 -10 0 10 20 30 400
a
0
5 10 15
0
5
10
0
5
0
5
350 300 250 200 150
Radius (mm)
100 50 0 -50 -100 -150 -200 -250 -300 -350
b
-400
x=17.7 mm x/d=0.1
x=39.4 mm x/d=0.22
x=92.5 mm x/d=0.52
particle (the common core) − air
x=181 mm x/d=1.02
x=358 mm x/d=2.02
x=588 mm x/d=3.32
particle (the sawtooth shaped core)
Figure 45. Profiles of air (a) and particle (b) mean radial velocities with different cores.
RMS velocity (m/s) 400
a
0 10 20 30 40 102030405060 10 20 30 40 5 10 15 20 25 5 10 15 20 25 5 10 15 20 25
350 300 250 200 150
Radius (mm)
100 50 0 -50 -100 -150 -200 -250 -300
b
-350 -400
x=17.7 mm x=39.4 mm x=92.5 mm x/d=0.1 x/d=0.52 x/d=0.22 particle (the common core) − air
x=181 mm x=358 mm x=588 mm x/d=1.02 x/d=2.02 x/d=3.32 particle (the sawtooth shaped core)
Figure 46. Profiles of air (a) and particle (b) radial fluctuation velocities with different cores.
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The air mean radial velocity appears positive and negative fluctuation near the zone that radius is about 100 mm. At the sections of x/d ≥ 0.52, the sawtooth shaped core has little influence on the mean radial velocities. With the sawtooth shaped core the air and particle radial fluctuation velocities are clearly larger than those with the common cone in the central recirculation zones and primay air and secondary air main flow zones at the sections of x/d = 0.1-0.52 and the zone that radius is less than 150 mm at the section of x/d = 1.02. In these zones, air/particle flow possesses larger radial turbulence transport capacity.
2. Particle Concentration Figures 47-49 show profiles of particle volume fluxes, normalized particle number concentration and normalized particle volume fraction for particle size in the range from 0.5 to 100 μm with different cores, Cn is the particle number concentration at a given point and Cnmax is the largest particle number concentration in the same cross section, Cv is the particle volume fraction at a given point and Cvmax is the largest particle volume fraction in the same cross fraction. As a lot of particles spray into the test section from gaps of the sawtooth shaped core (see Figure5), in radially measured fields of cross sections of x/d = 0.1-1.02, the peak of the particle volume flux with the sawtooth shaped core is closer to the burner center than that with the common core. From the profiles of normalized particle number concentration and normalized particle volume fraction, we can see that at the sections of x/d = 0.1-1.02, the sawtooth shaped core make the central recirculation zone possess more normalized particle number concentration and normalized particle volume fraction than those with the common core.
-4
3
2
Particle volume flux (10 m /(m s)) 150
-1 0 1 2 3 4 5 6 -2 0 2 4
0 1 2 3 4
-0.5 400
0.0
0.5
0.0
0.5
0.0
350 125 300
Radius (mm)
100
250 200
75 150 50
100 50
25 0 0
-50
x=17.7 mm x/d=0.1
x=39.4 mm x=92.5 mm x/d=0.52 x/d=0.22 the common core
x=181 mm x=358 mm x/d=1.02 x/d=2.02 the sawtooth shaped core
Figure 47. Profiles of particle volume fluxes with different cores.
x=588 mm x/d=3.32
0.5
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Cn/Cnmax 0.0 150
0.5
1.0
0.5
1.0
0.5
1.0
0.0 400
0.5
1.0
0.5
1.0
0.5
1.0
350 125 300
Radius (mm)
100
250 200
75 150 50
100 50
25 0 0
-50
x=17.7 mm x/d=0.1
x=39.4 mm x=92.5 mm x/d=0.52 x/d=0.22 the common core
x=181 mm x=358 mm x/d=1.02 x/d=2.02 the sawtooth shaped core
x=588 mm x/d=3.32
Figure 48. Profiles of number concentration with different cores.
Cv/Cvmax 0.0 150
0.5
1.0
0.5
1.0
0.5
1.0
0.0 400
0.5
1.0
0.5
1.0
350 125 300 250
Radius (mm)
100
200 75 150 100
50
50 25 0 0
-50
x=17.7 mm x/d=0.1
x=181 mm x=358 mm x=39.4 mm x=92.5 mm x/d=0.52 x/d=1.02 x/d=3.32 x/d=0.22 the common core the sawtooth shaped core
Figure 49. Profiles of normalized particle volume fraction with different cores.
The peak of the particle volume flux with the sawtooth shaped core is closer to the burner center than that with the common core. The more the position is close to the burner center, the higher the gas temperature becomes. The sawtooth shaped core makes the high pulverized coal concentration well match high temperature. At the same time, there are larger air radial fluctuation velocities and radial turbulence transport capacity near the border of the central
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recirculation zone. These factors make the pulverized coal easily heated, ignited and keep flame stable [12, 24, 25]. There is the larger pulverized coal concentration in the central recirculation zone with the sawtooth shaped cone. The central recirculation zone is a low oxygen concentration and reducing atmosphere zone. This zone can effectively control the NOx formation [50].
3. Particle Diameter Figure 50 shows profiles of particle mean diameters for particle size in the range from 0.5 to 100 μm. The particle mean diameter is the arithmetic mean diameter. The profiles are almost independent of the cone structures.
Particle mean diameter (μm) 20 400
30
40
50
30
40
50 30 40 50
40 50 60
20 30 40 50
30
40
50
350 300
Radius (mm)
250 200 150 100 50 0 -50
x=17.7 mm x/d=0.1
x=39.4 mm x=92.5 mm x/d=0.52 x/d=0.22 the common core
x=181 mm x=358 mm x/d=1.02 x/d=2.02 the sawtooth shaped core
x=588 mm x/d=3.32
Figure 50. Profiles of particle diameters with different cores.
4. Conclusion (1) Profiles of air/particle mean axial velocities, mean tangential velocities, axial fluctuation velocities and tangential fluctuation velocities and the central recirculation zone are almost independent of as the sawtooth shaped and the common cores. (2) The peak of the particle volume flux of the burner with the sawtooth shaped core is closer to the burner center than that with the common core. The sawtooth shaped core make the central recirculation zone of burner possess more normalized particle number concentration and normalized particle volume fraction than the common core. (3) With the sawtooth shaped core the particle mean radial velocities are smaller than the air mean radial velocities and the air mean radial velocities appear clear fluctuation in the primay air and secondary air main flow zone in the near the burner region. In
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the central recirculation zone, the air fluctuation velocities are clearly larger than those with the common cone. (4) Profiles of particle mean diameters are almost independent of as the sawtooth shaped and the common cores.
2.3.6. Influence of Division Cone Angles between the Fuel-Rich and the Fuel-Lean Ducts on Particle-Laden Flows and Combustion Near Swirl Burners In order to prevent the loss of the enriching effect caused by mixing fuel-rich and fuellean primary air/coal mixings before they are ejected into the furnace, we usually install a division cone between the primary air/coal mixings. A three-dimensional particle-dynamics anemometer (PDA) is used to study gas/particle flow characteristics with division cone angles of 43.2° and 0° [26]. The uncertainties and the particle material used in the experiment are introduced in 2.3.5 Part. No enricher was mounted in the RBC burner model (see Figure 51), and glass beads were fed only into the fuel-rich primary air/coal mixing duct. This simulates the extreme case in which particles in the primary air are all concentrated into the fuel-rich primary air/coal mixing. Except for the division cone structure, the two burner models were the same. In Model A, the division cone angle was 43.2° , the division cone diameter was φ83mm, and the distance from the division cone edge to the central cone edge was 13.9 mm. In Model B, the division cone was removed (equal to division cone angle of 0° ) and the diameter of the division annulus between the fuel-rich and the fuel-lean ducts wasφ71mm. The distance from the division cone edge to the central cone edge was 33mm. Operational parameters for the two models were the same. The primary air velocity was 15.5m/s, and the swirl secondary air axial velocity was 21.4m/s. The non-swirl secondary air velocity and central air velocity were both 0 m/s. The fuel-rich primary air/coal mixing particle mass concentration, which is defined as the ratio of particle mass flow rate to air mass flow rate, was 0.20kg (fuel)/kg (air), and that of the fuel-lean one was 0 kg (fuel)/kg (air).
1. Gas/Particle Flow Characteristics Gas/particle flow characteristics were measured in sections of x/d=0.22, 0.37, 0.52, 1.02, 2.02, 3.32. Figure 52 shows the profiles of air/particle axial mean velocities, and Figure 53 shows the profiles of 0 ~ 100 μ m particle volume fraction. In Figure 54, γ refers to the division cone angle. u=0 refers to the points between the central recirculation zone and the main flow zone at which the air axial mean velocity is 0m/s, and Qmax refers to the peak value of particle volume flux at the point near the burner center. Profiles of gas/particle tangential and radial velocities were similar at the two cone angles. Figure 52 shows that there were two peak values in the profiles of gas/particle axial mean velocities at both division cone angles. The peak zone near the burner center was the primary air/coal mixing flow zone, and another peak zone near the wall was the secondary air flow zone. As the jet stream developed, theprimary air entered the central recirculation zone from the cross section at x/d=0.37 with a division cone angle of 43.2° (see Figure 51a).
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Figure 51. Burner models (dimensions are in mm). a. with division cone angle of 43.2° b. with division cone angle of 0° . 1. central air 2. fuel-richprimary air and glass beads 3. fuel-leanprimary air 4. swirl secondary air 5. non-swirl secondary air.
Figure 52. Profiles of axial mean velocities for gas (a) and particles (b) at different division cone angles. ○ the division cone angle is 43.2° the division cone angle is 0° .
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Figure 53. Particle volume flux profiles at different division cone angles. ○ the division cone angle is 43.2° the division cone angle is 0° .
Figure 54. Axial zero air velocity (u=0) line and Qmax points.
At x/d=1.02, theprimary air was completely incorporated in the central recirculation zone. The diameter of the central recirculation zone increased, and it continued to enlarge with the jet development. In the central zone, between the cross section of x/d=0.52 and that of x/d=1.02, axial mean velocities of the air were negative while those of particles remained positive. Therefore, numerous particles penetrated the central recirculation zone. This pattern of air/particle flow was also found in previous works [27-33]. With a division cone angle of 0° , there was no barrier from the division cone and the axial flow momentum was much greater. Therefore, the fuel-rich primary air/coal mixing mixed earlier with the fuel-lean one and, as a result, theprimary air flow zone near the center maintained a higher positive velocity and the diameter and length of the central recirculation zone stayed small (Figure 52a and Figure 54). It should be noted that, at the position of x/d=1.02 (x=181mm), the central recirculation zone completely disappeared and no particles penetrated the central recirculation zone. Figure 53 shows that profiles of particle volume fluxes were also similar at both division cone angles. Profiles of particle volume flux in cross sections from x/d=0.22 to 1.02 have two peak zones, resulting from burner structures and particle inertia. With the RBC burner, the
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diameter of the outer tube of the fuel-rich primary air/coal mixing duct was φ71mm (see Figure 51). The central cone diameter was φ63mm. When particles ejected into the test chamber from the fuel-rich primary air/coal mixing duct, particles in the outer annulus of the fuel-rich primary air/coal mixing duct were generally not influenced by the central cone and ejected directly into the test chamber. It is these particles that formed the peak zone of the particle volume flux near the jet axis. While particles in the inner zone of the fuel-rich primary air/coal mixing duct ejected into the test chamber at a certain angle to the burner central axis, due either to collision with the central cone or to the guidance of the central cone, these particles formed the other peak of the particle volume flux outside of the peak zone near the burner central axis. With jet development, the peak values were noticeable. Figure 54 shows that with a division cone angle of 43.2° , the fuel-rich and the fuel-lean primary air/coal mixings did not mix with each other before entering the test chamber through their own ducts. The position of the particle volume flux peak near the central axis is closer to the axis than that of the cone angle of 0° , and downstream from the cross section x/d=0.37(x=66mm) the particle volume flux peak zone is inside the central recirculation zone. In contrast, with a division cone angle of 0° , the fuel-rich and the fuel-lean primary air/coal mixings mix before entering the test chamber through their own ducts. Since particles in the fuel-rich primary air/coal mixing are easy to diffuse into the fuel-lean primary air/coal mixing, the position of the particle volume flux peak near the central axis is farther away from the central axis than that of the cone angle of 43.2° , and it is always in the outer part of the central recirculation zone.
2. Influence of Division Cone Angles on Combustion In boilers with swirl burners installed on walls, each swirl burner forms its own flame independently and generally does not influence the others. Using the central recirculation zone as the heat source, coal particles ignite on time and form stable flames. The size of the central recirculation zone has an important effect on ignition and combustion. With a division cone angle of 43.2° , the central recirculation zone is bigger and is expected to provide enough heat for PF ignition. The position of the particle volume flux peak near the central axis is closer to the central axis. Because the gas temperature is higher in the central recirculation zone, a zone of high temperature and high fuel concentration is formed. With the increase of PF concentration near the high temperature central recirculation zone, emissivity of the PF stream increases. Then radiative heat, absorbed from the central recirculation zone and the flame in the furnace, increases [34]. As a result, the temperature of the PF and air increases faster than usual. An experiment done by Horton et al (1977) [35] showed that increasing the PF concentration in a certain range could also increase the flame velocity. Downstream from the cross section at x/d=0.37 (x=66mm), the recirculation zone appears around the primary air flow zone, and the particle volume flux peak zone near the central axis gradually becomes incorporated in the central recirculation zone (see Figures 52 and 54). Therefore, a proper angle of division cone is advantageous for heating and ignition of PF particles. Coal quality frequently changes in China’s power plants, and boilers are prone to flame extinction even with a rated load when burning low-grade coals. The appropriate division cone angle will curtail flame extinction and insure stable boiler operation. PF particles igniting at the proper position also provide good conditions for burnout. The early stage of coal combustion takes place in a dynamic combustion zone. When the temperature
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rises, combustion speed increases. These conditions are advantageous to the burnout of coal particles. With a division cone angle of 0° , the size of the central recirculation zone is too small to provide enough heat for PF ignition. The position of the particle volume flux peak near the axis is farther away from the central axis than that with the division cone angle of 43.2° . Furthermore, it is always in the outer region of the central recirculation zone where the temperature is lower. No zone of high temperature and high fuel concentration is formed. That is disadvantageous to flame stabilization and burnout, especially in the case of low-grade coals.
Figure 55. Zero velocity line ( ○ ) of the burner central recirculation zone and the stream border (●). a. with PA, without secondary air b. With bothprimary air and secondary air.
Many factors influence NOx formation, such as coal nitrogen, coal type, particle diameter, swirl number, stoichiometric ratio, primary air ratio, temperature and residence time. There are many measures to abate NOx emission. The low NOx burner is an inexpensive one. By ensuring the residence time of the coal particles in the fuel-rich zone or the reducing atmosphere zone, the burner decreases fuel NOx formation. When division cone angle is 43.2° , the central recirculation zone is large. Downstream from the cross section at x/d=0.37 (x=66mm), the particle volume flux peak zone near the axis is inside the central recirculation zone, which is a low oxygen zone where the atmosphere is reducing and can decrease the formation of the fuel NOx. When the division cone angle is 0° , the particle volume flux peak zone near the axis is farther away from the central recirculation zone. In this area, the atmosphere is oxidizing, the temperature is low, and ignition takes place further from the burner nozzles. The stronger the oxidizing atmosphere, the more advantageous it is to the formation of fuel NOx; the farther away from the burner nozzles that ignition takes place, the moresecondary air that mixes in [28-31, 33, 36-48].
3. In-Situ Industrial Experiments The 670t/h boiler of ΕП 670–13.8–545KT type was made in the former Soviet Union. It is fired with PF and synchronized to a 200MWe steam generator. It is a dry-ash type furnace with a division wall. The boiler burns lean coal (defined in China as a coal with 10-20% volatile, dry-ash free matter) with low volatility [Table 6].
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Central air
primary air
Swirling secondary air
Non-swirling secondary air
Exit area (×10-3 m2)
2.98
6.69
11.41
3.35
Mass flow rate of particle (kg/s)
0.0
0.0124
0.0
0.0
Mass flow rate of air (×10-2 kg/s)
0.0
12.08
36.91
0.0
Particle loading
0.0
0.1
0.0
0.0
Air temperature
16 ℃
Particle swirl number
0.92
Air swirl number
0.26
Table 6. Design and burned coal composition Proximate analysis, wt% (as received) Moisture
Ash
Volatility
Fixed carbon
Net heating value (kJ/kg)
Design coal
4.38
34.36
17.0
43.81
19661
Coal fired during test
5.60
27.46
13.20
53.74
22600
Ultimate analysis, wt% (as received) Carbon
Hydrogen
Nitrogen
Oxygen
Sulfur
Design coal
54.44
2.03
0.77
2.38
1.36
Coal fired during test
58.07
2.74
0.97
4.35
1.01
The boiler is of T type arrangement with dual furnaces, and uses a bin system with cold moisture–laden exhaust air from pulverizers to convey the PF. The furnace is 17.76m in width and 8.8m in depth. Sixteen swirl burners are located on two opposite walls of the furnace, with eight burners on each side arranged vertically in two rows. The coal is low- grade and the quality changes frequently. The primary air/coal mixing temperature is 75℃, and the primary air ratio is 26%. Compared with the system in which PF is conveyed by hot air, the primary air/coal mixing temperature is lower, and theprimary air ratio is higher. Therefore, it is required that burners excel in flame stabilization. According to the above experimental results, burners with division cone angle of 43.2° are adopted.
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To verify the effectiveness of the division cone, we made in-situ measurements of the near-burner flow in the cold state. The uncertainty value in central recirculation zone size was 50mm. Figure 55a shows the flow structure without secondary air and with primary air only. The fuel-rich primary air velocity was 10.1m/s, and the fuel-lean primary air velocity was 10.8m/s. Figure 55b shows the flow structure with both secondary air and PA. Test velocities were determined by modeling. The fuel-rich primary air velocity was 10.1m/s, the fuel-lean primary air velocity was 10.8m/s, the swirl secondary air velocity was 12.1m/s, and the nonswirl secondary air velocity was 4.7m/s. db represents the outer diameter of the non-swirl secondary air nozzle, which was φ1246mm. A central recirculation zone was formed with the guidance of the central cone and the division cone even though no swirl secondary air was ejected. The diameter and length of the central recirculation zone, and the divergence angle were 0.48db (φ600mm), 0.56 db(700mm) and 97° respectively [Figure 55a]. With secondary air given, the size of the central recirculation zone became much larger [Figure 55b]. The diameter of the central recirculation zone was between 1.61db (φ2000mm) and 1.77db(φ2200mm), and the length was 2.41db(3000mm). The divergence angle was 98° . Coal analysis is shown in Table 6. With a 200MWe load, the boiler operated stably, with parameters such as steam temperature, steam pressure, etc., within normal range. The PF ignited properly and combustion was successful. The carbon loss was 2.36%, and the boiler efficiency was 90.02%. NOx (O2=6%) was 762 mg/Nm3. The boiler operated stably at 100MWe during the low load test. Boiler steam parameters were in normal range. Furnace pressure fluctuation was ±50Pa, which implies that combustion was stable in the furnace. The flame scanners showed a steady signal rather than an intermittent signal, and the boiler ran well. The low load test lasted four hours. After RBC burners were adopted, flame stability was greatly improved and no flame extinction occurred even with a wide variation in coal quality and boiler load.
4. Conclusion The influence of division cone angles between the fuel-rich and the fuel-lean ducts on gas/particle flow is significant. With an angle of 43.2° , the central recirculation zone is larger. The particle volume flux peak near the central axis is closer to the central axis than with an angle of 0° . Even at a certain distance from the burner, the particle volume flux peak zone is still in the central recirculation zone, and large masses of particles penetrate the central recirculation zone. Evidently, it is easy to form a high temperature and high fuel concentration zone. With a division cone angle of 0° , the central recirculation zone is smaller. The particle volume flux peak near the central axis is farther away from the central axis, and it is always in the outer part of the central recirculation zone. Therefore, it is not easy to form a high temperature and high fuel concentration zone. In-situ experiments on a 200MWe unit show that with a division cone angle of 43.2° , boiler efficiency is 90.02% when fired with lean coal, and NOx emission is 762mg/Nm3(O2=6%). The boiler operates stably with a load of 100MWe without auxiliary fuel oil.
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2.4. Influence of Run Parameters on Gas/Particle Flow 2.4.1. Influence of the Non-Swirling Secondary Air on Gas/Particle Flow and Coal Combustion
1. Gas/Particle Flow Characteristics Burner operational parameters have great effects on flow characteristics and burner properties [48-51]. The objective of our work is to investigate the influence of the nonswirling secondary air on gas/particle flow and coal combustion of radial biased combustion burners. To this end, the pilot and full scale experiments have been carried out. The data has value because of the support it lends to theoretical and numerical calculations [22]. A three–dimensional particle-dynamics anemometer was used in this study. The uncertainties and the particle material used in the experiment are introduced in 2.3.5 Part. The non-swirling secondary air ratio is the ratio of the non-swirling secondary air mass flow rate to the total secondary airflow rate. The following definition of the total air swirl number St is used:
St
∫ =
d0 / 2
0
d∫
( ρωu + ρ pω p Q ) r 2 dr
d0 / 2
0
( ρu 2 + ρ p u p Q )rdr
(20)
Figure 51a shows the radial biased combustion burner model. No enricher was mounted in it, and glass beads were fed only into the fuel-rich primary air/coal mixing duct. This simulates the extreme case in which particles in the primary air are all concentrated into the fuel-rich primary air/coal mixing. Table 7 shows experimental parameters. During the experiment, the total secondary air mass flow rate and primary air parameters were kept constant. The air mass flow rate was controlled within an accuracy of 5 %. Different nonswirling secondary air ratios were obtained by changing the non-swirling and swirling secondary air flow rates. The gas/particle flow characteristics were measured at sections of x/d = 0.1, 0.22, 0.37, 0.52, 1.02, 2.02, 3.32.
(1) The Total Air Swirl Number The total air swirl number, shown in Table 7, was calculated with the measured velocities at the section of x/d = 0.1. The total air swirl number decreased with the increase of nonswirling secondary air ratios. (2) Velocity The definition of the boundary of the air (the particle) jet and the divergent angle of the air (the particle) jet is shown in the 2.3.3 Part. Figure 56 shows jet borders with different nonswirling secondary air ratios, where B refers to the value of the jet boundary and Rns is the non-swirling secondary air ratio. Figure 56 shows that jet boundaries of the air and the particle were almost a straight line in the zone of x/d ≤ 0.52. Table 8 shows divergent angles of the air and the particle with different non-swirling secondary air ratios.
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Table 7. Experimental parameters with different non-swirling secondary air ratio
Central air
Fuel-rich primary air
Fuel-lean primary air
Swirling secondary air
Nonswirling secondary air
2.98
3.19
3.16
11.41
3.35
Mass flow rate of particle (kg/s)
0.0
0.0124
0.0
0.0
0.0
Particle loading
0.0
0.2
0.0
0.0
0.0
Exit area (×
10−3 m2)
Air temperature
16 ℃
Non-swirling secondary air ratio (%)
Mass flow rate of air ( ×
0
0.0
6.04
6.04
29.81
0.0
Total air swirl number 0.3
11.1
0.0
6.27
6.27
27.17
3.39
0.2
22.4
0.0
6.00
6.00
22.43
6.46
0.2
10−2 kg/s)
Table 8. Air and particle divergent angles Non-swirling secondary air ratio Air divergent angle Particle divergent angle
Figure 56. Jet borders.
0.0 %
11.1 %
22.4 %
100.8° 109.0°
45.5° 88.6°
44.3° 68.8°
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Figures 57 and 58 show profiles of the decay of the gas/particle axial maximum velocities and the gas/particle mean axial velocities with non-swirling secondary air ratios. There were two peak values in the profiles of gas/particle mean axial velocities near the burner. The peak zone near the burner center was the primary air/coal mixing flow zone, and another peak zone near the wall was the secondary air flow zone. At the section of x/d = 0.1, the peak value near the burner center was larger than the peak value near the wall. However, with the primary air/coal mixing diffusing into the secondary air, the peak value near the burner center gradually reduced. On the other hand, the peak value near the wall gradually increased. With the jet development, the secondary air diffused into the wall zone, the peak value near the wall also gradually reduced and its radial position gradually moved toward the wall. The experimental results show that the gas/particle borders of the jet greatly moved to the burner centerline with the increase of non-swirling secondary air ratios. When the non-swirling secondary air ratios increase from 0 % to 22.4 %, the air divergent angles decreased from 108° to 44.3° and the particle divergent angles decreased from 109° to 68.8° . The central recirculation zone apparently decreased with increasing the non-swirling secondary air ratios. For non-swirling secondary air ratio equaled zero, the central recirculation zone diameters are 25.9~28.5 mm in the zone of x/d = 0.1~0.37, and they become larger with the development of the jet. As the jet developed, the primary air entered the central recirculation zone from the cross section at x/d = 0.37. At x/d = 1.02, the primary air was completely incorporated in the central recirculation zone. In the central zone between the cross section of x/d = 0.52 and that of x/d = 1.02, mean axial velocities of the air were negative, while those of particles remained positive. Therefore, numerous particles penetrated the central recirculation zone. The pattern of air-particle flow was also found in previous works [27-33]. In the case that the non-swirling secondary air ratio was 22.4 %, the central recirculation zone diameters were 14.2~20.0 mm at x/d = 0.1~0.37, and the central recirculation zone was closed at x/d = 0.52. In this case we observed the smallest central recirculation zone. In addition, the larger was the non-swirling secondary air ratio, the slower was the rate of air-particle diffusion towards the furnace wall.
Figure 57. Decays of air-particle maximum axial velocities.
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Figure 58. Profiles of (a) the air and (b) the particle axial mean velocities with different secondary air ratio.
Figure 59 shows profiles of axial fluctuation velocities. There were two peak values in the profiles of gas/particle root mean square (RMS) axial fluctuation velocities. The profiles became flat in the downstream region. Figure 60 shows profiles of mean radial velocities. Although the primary air/coal mixing was non-swirling, due to the angle of the cones, mean radial velocities were larger in the primary air and secondary air flow zone (the radius r > 28.2 mm) at the section of x/d = 0.1. They were smaller in the wall zone. There was one peak value in the profiles. With the jet development, the mean radial velocities gradually decreased. With the increase of the nonswirling secondary air ratio, the particle mean radial velocity and maximum mean radial velocity (Figure 60 (b)) decreased in the main flow field. In the same section, the position of particle maximum radial velocity in the case of the 0 % non-swirling secondary air ratio was closer to the wall than that in the case of 11.1 % and 22.4 % non-swirling secondary air ratios. Therefore, particles diffused faster into the wall zone when the non-swirling secondary air ratio was low. Figure 61 shows profiles of radial fluctuation velocities. At the sections of x/d = 0.1 to 1.02, the radial fluctuation velocities were larger in the central recirculation zone and the primary air and the secondary air main flow zones and smaller in the wall zone. At the sections of x/d = 2.02、3.32, the profiles of radial fluctuation velocities became flat as the profiles of the mean radial velocities became flat.
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Figure 59. Profiles of (a) the air and (b) the particle axial fluctuation velocities with different secondary air ratio.
Figure 60. Profiles of (a) the air and (b) the particle radial mean velocities with different secondary air ratio.
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Figure 61. Profiles of (a) the air and (b) the particle radial fluctuation velocities with different secondary air ratio.
Figure 62. Profiles of (a) the air and (b) the particle tangential mean velocities with different secondary air ratio.
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Figure 62 shows profiles of mean tangential velocities. Because there was no central air and the primary air was non-swirling, the mean tangential velocities were smaller in the burner central zone (r ≤ 55.5 mm) and larger in the secondary air at the section of x/d = 0.1. The profiles became flat in the down stream region. Without the non-swirling secondary air, the maximum mean tangential velocities were the largest among the three non-swirling secondary air ratios. The profiles were almost independent of the non-swirling secondary air ratios. Figure 63 shows profiles of tangential fluctuation velocities. At the sections of x/d = 0.1 to 0.52, there were two peak values in the central recirculation zone and the secondary air flow zone. At the section of x/d = 1.02 to 3.32, the profiles of the tangential fluctuation velocities became flat as the profiles of the mean tangential velocities became flat.
Figure 63. Profiles of (a) the air and (b) the particle tangential fluctuation velocities with different secondary air ratio.
(3) Particle Concentration Figure 64 shows profiles of particle volume fluxes for particle size in the range from 0.5 to 100 μ m at different non-swirling secondary air ratios. The profiles of particle volume fluxes show that they had two peaks in the sections of x/d = 0.1 to 1.02, resulting from burner structures and particle inertia. The diameter of the outer tube of the fuel-rich primary air/coal mixing duct was 71mm (see Figure 51a). The central cone diameter was 63mm. When particles ejected into the test chamber from the fuel-rich primary air/coal mixing duct, particles in the outer annulus of the fuel-rich primary air/coal mixing duct were generally not influenced by the central cone and ejected directly into the test chamber.
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Figure 64. Profiles of particle volume fluxes with different secondary air ratio.
It is these particles that formed the peak zone of the particle volume flux near the jet axis. While particles in the inner zone of the fuel-rich primary air/coal mixing duct ejected into the test chamber at a certain angle to the burner central axis, due either to collision with the central cone or to the guidance of the central cone, these particles formed the other peak of the particle volume flux outside of the peak zone near the burner central axis. At the sections of x/d = 2.02 and 3.32, the profiles became flat. The profiles of particle volume fluxes were almost independent of the non-swirling secondary air ratios. The maximum particle volume flux near the burner center, increased with increasing of the non-swirling secondary air ratio. Therefore, the concentration of particles in the burner central zone increased with the nonswirling secondary air ratio. Figure 65 shows profiles of number concentrations for particle size in the range from 0.5 to 100 μ m, where Cn is the number concentration at a given point and Cnmax is the largest number concentration in the same cross section. At the sections of x/d = 0.1 to 1.02, there were also two peak values in the profiles. However, at the sections of x/d = 2.02 and 3.32, the profiles became flat. The profiles of number concentrations were similar to that of particle volume fluxes. The profiles were almost independent of the non-swirling secondary air ratios.
(4) Particle Diameter Figure 16 shows profiles of particle mean diameters for particle size in the range from 0.5 to 100 μ m. The particle mean diameter is the arithmetic mean diameter. Profiles of the
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particle mean diameter had two peaks in the sections from x/d = 0.1 to 1.02, whose positions were same as the position of particle volume flux peaks.
Figure 65. Profiles of number concentrations with different secondary air ratio.
Particle in the fuel-rich primary air/coal mixing duct were separated into two particle jets, when ejected into the test chamber. The larger the particle was, the larger inertia it had. As the primary air/coal mixing was non-swirling, particles had the characteristic of keeping the nonswirling jet. The finer particles of two particle jets were liable to diffuse to the secondary air or the central recirculation zone. On the other side, the larger particles were liable to flow in their former flow direction due to their larger inertias. Then, two particle mean diameter peaks were formed. With the jet development, the larger particles were also transported into the wall zone or the central recirculation zone, and the profiles became flats. In the wall zone, particles near the burner jet came from the wall zone of the down stream through the outside recirculation. Particle diameters were larger in the wall zone of the down stream. As a result, the particle mean diameters were large in the wall zone. The profiles were almost independent of the non-swirling secondary air ratios.
2. Mixing Characteristics of Jet The mixing characteristics of jet from the burner were measured on a single-phase test facility [14]. Figures 67 and 68 show the ratio of primary air and the maximum ratio of primary air of every section with different non-swirling secondary air ratio. With the increase of non-swirling secondary air ratio, the ratio of primary air in the burner central zone of every section increase and the maximum ratio of primary air decreases more slowly.
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners…
Figure 66. Profiles of particle mean diameters with different secondary air ratio.
Figure 67. Ratio of primary air with different secondary ratio.
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It shows that the mixing of primary air, gas of central recirculation zone and secondary air is greatly delayed. It is disadvantageous to the heating of primary air/coal mixing, coal ignition and flame stability. But it is advantageous to the air-staged combustion and reducing the fuel NOx formation.
Figure 68. Maximum ratio of primary air with different secondary air ratio.
3. Industrial Experiment (1) Experimental Boiler Experiments were carried out on the 410-tph and 220-tph boilers of a power plant. Both boilers were retrofitted from oil to coal - firing. Eight burners are located on the front boiler wall, and they are grouped in two rows. A common big wind box is used for the eight burners. The wind box is divided into the top and the bottom wind boxes by the division plate located between the top and the bottom burners. There are dampers at wind box entrances to balance the flow entering the top and the bottom wind boxes. There are also dampers at the burner swirling and non-swirling secondary air entrances. Figure 69 shows the 410-tph boiler furnace, platen superheater and burner index. The membrane water-cooled wall, whose tube diameter and pitch were 60 mm and 80 mm, was used. The tube diameter of the platen superheater was 42 mm. The transverse pitch and the number of transverse rows were 720 mm and 16. The longitudinal pitch and the number of longitudinal rows were 48 mm and 42. The working substance temperature was 321 ℃ in the water-cooled wall. The working substance temperature in the platen superheater was 352 ℃ at the entrance and 437 ℃ at the exit. Figure 70 shows the full industrial-size burner. The axially vanes were set at angles of 65º with the airflow direction. Table 9 shows the design parameters of the burner.
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners… 1001
Figure 69. The furnace, burner index, and swirling secondary air direction on the 410-tph boiler (dimensions are in mm).
Figure 70. The full industrial-size burner on a 410-tph boiler (dimensions are in mm) (1)central air (2) fuel-rich primary air/coal mixture (3) fuel-lean primary air/coal mixture (4) swirling secondary air (5) non-swirling secondary air.
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Table 9. Design parameters of the burner on the 410-tph boiler Fuel-rich primary air
Fuel-lean primary air
Swirling secondary air
Nonswirling secondary air
83.4
83.4
412.7
98.8
Mass flow rate of coal (kg/s)
1.376
0.459
Coal loading
0.74
0.25
90
90
320
320
Central air Exit area (×
10−3 m2 )
Air temperature (℃)
102.3
320
Non-swirling secondary air ratio (%)
Swirl number
Mass flow rate of air (kg/s)
0
0.0
1.865
1.865
11.030
0.0
0.48
20.0
0.0
1.865
1.865
8.824
2.206
0.36
Table 10. Design parameters of the burner on the 220-tph boiler
Central air
Fuel-rich primary air
Fuel-lean primary air
Swirling secondary air
Nonswirling secondary air
86.0
45.2
45.2
203.3
69.2
Mass flow rate of coal (kg/s)
0.739
0.246
Coal loading
0.67
0.22
95
95
300
300
Exit area (×
10−3 m2 )
Air temperature (℃)
300
Non-swirling secondary air ratio (%)
Swirl number
Mass flow rate of air (kg/s)
0
0.0
1.106
1.106
6.074
0.0
0.39
20.0
0.0
1.106
1.106
4.859
1.215
0.31
Figure 71 shows the 220-tph boiler furnace, platen superheater and burner index. The membrane water-cooled wall, whose tube diameter and pitch were 60 mm and 80 mm, was used. The outside two tubes’ diameter of the platen superheater was 42 mm, and the other tubes’ diameter, 38 mm. The mean transverse pitch and the number of transverse rows were 766 mm and 12. The mean longitudinal pitch and the number of longitudinal rows were 49.3
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners… 1003 mm and 38. The working substance temperature was 317 ℃ in the water-cooled wall. The working substance temperature in the platen superheater was 375 ℃ at the entrance and 445 ℃ at the exit. Figure 72 shows the full industrial-size burner. The axially vanes were set at angles of 65º with the airflow direction. Table 10 shows the design parameters of the burner.
Figure 71. The furnace, burner index, and swirling secondary air direction on the 220-tph boiler (dimensions are in mm).
Figure 72. The full industrial-size burner on a 220-tph boiler (dimensions are in mm) (1)central air (2) fuel-rich primary air/coal mixture (3) fuel-lean primary air/coal mixture (4) swirling secondary air (5) non-swirling secondary air.
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(2) Cold Flow Experimental Results Cold flow experiments were carried out on the 410-tph boiler. The similarity criteria are as follows: (1) self-modeling flows; (2) momentum ratios of the primary air coal-mixing to the secondary air maintained constant. The mass fluxes of different burners in the same wind box were kept equal. Burner swirling secondary air dampers were open, the non-swirling secondary air damper positions of the bottom burners (No. 1~4) were set to 0 %, and the nonswirling secondary air damper positions of the top burners (No. 5~8) were set to 100 %. Table 11 shows the experimental parameters. Figure 73 shows the measured flow field, where d0 is the burner diameter. The distance between two measurement traverses was 100 mm. We estimate that the uncertainties in establishing the location of the central recirculation zone border were 100 mm (0.10 d0). With the increase of the non-swirling secondary air ratio, the divergent angles decreased from 101° to 76° , and the central recirculation zone diameters decreased from 1.53 d0 to 1.21 d0. Table 11. Cold flow experimental parameters on the 410-tph boiler Non-swirling Secondary air damper (% open)
Non– swirling secondary air ratio (%)
Burner number
0 100
3.7 20.3
1~4 5~8
Central air
Fuel - rich primary air
Fuellean primary air
Mass flow rate of air (kg/s) 0.095 1.850 1.850 0.095 1.723 1.723 Air temperature (℃) 30 50 50
Figure 73. The jet border and the CRZ boundary on the 410-tph boiler.
Swirling secondary air
Nonswirling secondary air
Swirl number
10.529 9.183
0.403 2.337
0.45 0.37
30
30
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(3) Reacting Flow Experimental Results In the reacting flow experiment, the boiler operational parameters such as the load, the furnace exit O2, the coal feed rate, the central air and the primary air flow rates were kept constant. Only damper positions of the swirling and the non-swirling secondary air jets were changed. Table 12 shows the properties of the coal-fired.
Table 12. Burned coal composition Proximate analysis, Wt % (as received) Moisture Ash 4.9 34.26 Ultimate analysis, Wt % (as received) Carbon Hydrogen 52.22 3.08 R200 PF fineness, % R90 46.09 3.0
Volatility
Fixed carbon
36.09
24.75
Net heating value (kJ/kg) 19720
Oxgen 4.14
Nitrogen 0.77
Sulfur 0.63
A thermocouple inside a water-cooled probe was used to measure the gas temperature in the burner zone. Gas temperatures of the No. 2 burner were measured along the burner axis in the 410-tph boiler. Figure 74 shows the results, where curves a and b corresponded to different positioning of the swirling and the non-swirling secondary air dampers respectively. In the 220-tph boiler, gas temperatures of the No. 4 burner were measured radially at x/d1 = 2.4 (x = 1920mm), where d1 = 798 mm was the burner diameter. Figure 75 gives the results. Figures 74 and 75 shows that in both boilers gas temperatures in the burner zone decreased with increasing the non-swirling secondary air ratio.
Figure 74. Temperature profiles on the burner axis.
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Figure 75. Radial temperature profiles in the section that is 2.4d (1920mm) away from the exit of burner.
In the 220-tph boiler, the swirling secondary air dampers of all the burners were set to 100 %, and the non-swirling secondary air dampers of all the burners were set in sequence to at 0 %, 50 % and 100 %. Along the axis of No. 2 burner axis, gas sample were taken using a water-cooled probe and subsequently analyzed. Measurement ranges for NO, NO2, CO and O2 of the instrument are 0-2000 ppm, 0-200 ppm, 0-4000 ppm and 0-21 %. The volume concentration of NOx is the sum of volume concentrations of NO and NO2. Resolutions of NO, NO2, CO and O2 are 1 ppm, 1 ppm, 1 ppm and 0.1 %. Figure 76 shows the measured O2, NOx and CO concentrations when the non-swirling secondary air was set to 0. The measures were taken inside the central recirculation zone. The O2 concentration was almost 21 % at the burner exit, since the flame had not been ignited and the cold air jet was given from the burner central tube. Further down zone the coal jet was heated and volatiles were given off. In the zone of x/d1 = 0.2~0.5, a large quantity of volatiles were given off and they burned rapidly. Consequently, oxygen was rapidly consumed. The volatile-N, given off during devolatilization, was oxidized to a greater, extended to NOx. The NOx formation rate rapidly increased, and it stayed relatively constant when x/d1 ≥ 0.4 . When the swirling jet mixed rapidly with the coal jet, the volatiles had enough oxygen for rapid combustion. Therefore, the CO concentration was at a low level. Down jet, at the central recirculation zone closure, the O2 concentration graduately increased due to the diffusion of O2 from the secondary air jet. It assured a good char burnout. Figures 77, 78 and 79 show O2, CO and NOx profiles at the burner axis for different positions of the non-swirling secondary air damper. Pickett et al. (1999) found that the velocity profiles for reacting flow showed similar trends and patterns as were observed in cold flow experiments [48]. Our cold flow experiments show that when the non-swirling secondary air ratio was increased the mixing of the fuel jet and the primary air jet was decayed.. Thus, as the non-swirling secondary air dampers were graduately opened, the
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners… 1007 oxygen flowing into the jet center decreased, and the O2 concentration on the burner axis decreased (see Figure 77).
Figure 76. Profiles of in situ NOx, CO, and O2 concentrations on the burner axis.
Figure 77. Profiles of in situ O2 concentration on the burner axis.
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Figure 78. Profiles of in situ CO concentration on the burner axis.
Figure 79. Profiles of in situ NOx concentration on the burner axis.
Our gas/particle flow experiments show that fuel fluxes in burner central zone increased with the non-swirling secondary air ratio. In this way, the fuel-rich combustion was promoted, and the NOx reducing environment was created. The specific air-particle flow pattern inhibited the formation of the fuel-NOx. Our observations are in agreement with the previous experiments [2, 4, 31, 36-47, 52]. The NOx formation in the burner zone apparently decreased when the non-swirling secondary air ratios increased (see Figure 79). Table 13 shows the influence of the position of non-swirling secondary air dampers on NOx emission and char burnout of the 220-tph boiler. The economizer exit oxygen shows that
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners… 1009 the increase of non-swirling secondary air had a little effect on the boiler exit oxygen, because opening of these dampers had little effect on the total amount of air supplied to the boiler. NOx emissions (O2 = 6 %) decreased from 359 ppm to 331 ppm, with the average exit CO concentration at 18.7 ppm. Thus, the gaseous incomplete combustion loss is negligible. The carbon-in-ash decreased substantially from 2.98 % to 2.03 %. The swirl number influences the amount of oxygen and particles and the particles residence time in the burner central zone, which have effect on the particle burnout in the burner region. Experiments with a single annular orifice (SAO) burner and a single central orifice (SCO) burner in a large scale laboratory combustor [33, 53] emerges that the quality of the burnout in the burner region, are primarily influenced by the particles residence time in the burner inner recirculation zone. The maximum particle burnout for both burners occur at a certain swirl number.
Table 13. The boiler NOx emission and the carbon in ash content on the 220-tph boiler Non-swirling secondary air damper, % open Economizer exit oxygen, % NOx (O2 = 6 %), ppm Carbon in ash content, %
0 3.5 359 2.98
50 3.5 337 1.96
100 4.0 331 2.03
Above and below this swirl number, the particle burnout starts to decrease, respectively. Increasing the swirl number creates a more compact and intense central recirculation zone within which combustion rates, excepting very high swirl values, are generally intensified. At very high swirl values, the particles will be “centrifuged out” of the central recirculation zone resulting in shorter residence times and a fall-out in burnout. With increase of the nonswirling secondary air ratios, the fuel fluxes increased in the burner central zone, where the gas temperature is higher than the gas temperature in the outside, resulting in a fall-out of carbon-in-ash.
4. Conclusion The radial bias swirl-stabilized burner for combustion of pulverized coal has been investigated by conducting both extensive measurement of gas and solid phase velocities, particle concentrations, particle diameters, and subsequent trials in industrial boiler. The following conclusions are drawn: (1) Up to a down jet distance of x/d = 0.52 (d - burner diameter), the gas-phase flow pattern coincides with the solid-phase flow. Jet borders of the air and particle are almost a straight line. Further down jet, the gas jet and the solid phase jet diverge. (2) Low NOx combustion is achieved by injecting coal particles into the swirl-induced central recirculation zone that is a well-known method. However, a substantial improvement to char burnout is achieved by dividing the secondary combustion air jet into a non-swirling and a swirling part and the primary air-coal mixing into a fuelrich and a fuel-lean primary air-coal mixings. The non-swirling jet directed the particles towards the down jet part of the central recirculation zone. When 20 % of the secondary air jet was provided through the non-swirling jet, the carbon in ash content decreased from 2.98 % to 2.03 %.
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(3) The ratio of mass flow rate of the non-swirling part to the flow rate of the total (swirling and non-swirling) secondary combustion air jet is an important burner design parameter. The dependence of the central recirculation zone properties and primary air diffusion and subsequent NOx and CO emissions on this parameter has been given in the paper.
2.4.2. Influence of the Central Air on Coal Combustion
1. Experimental Boiler The 670t/h boiler of ЕП 670-13.8-545KT type in a power plant was made in former soviet Union. It is fired with pulverized coal and synchronized to a 200 MWe steam generator. It is of dry-ash type furnace with a division wall. The boiler is of T type arrangement with dual furnaces, and it adopts bin systems with cold moisture-laden exhaust air from pulverizers conveying PF. The furnace is 17.76m in width and 8.8m in depth. Sixteen swirl burners are located on two opposed sidewalls of the furnace, with eight burners on each sidewall vertically in two rows. Volute burners were originally used. Eight burners of the bottom row were retrofitted with RBC burners before the industrial test [19]. 2. Cold Flow Experiment In cold flow experiment, co-axial airflow pattern was maintained to be in the second selfmodeling zone. Compared with reacting flow, momentum ratios were maintained same. In addition, the SA and the PA flowrates of each burner were kept to be equal, and dampers of the non-swirl SA were 100% open. Little tufts were used to trace flow near the burner. The uncertainty is 100mm (0.01db). Here, db represents outer diameter of the non-swirl SA nozzle of the burner, which is φ1080mm. Figure 80 shows the flow pattern, where Rc is the central air ratio.
Figure 80. Reverse-flow and jet boundaries of a full-scale burner.
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners… 1011 As ratio of the central air is 1.2%, the velocity of the central air is so little that the boundary of the reverse flow maintained unchanged. As ratio of the central air is 6.2%, the part of the reverse flow zone at the burner exit in the central zone of the burner is blown away. Instead, a zone, where the axial velocity is positive, is formed like a taper cone. Little tufts also measured the jet boundary, where axial velocity is zero, and the divergent angle of the jet was got. As ratios of the central air are 1.2% and 6.2%, divergent angles of the jet are 90° and 89° . It has a little change.
3. Reacting Flow Experiment At rated load, in-situ species and temperature were measured on axis. They are shown in Figures 81 and 82. A naked thermoelectric couple protected by a water-cooled gun was used to measure the gas temperature. In-situ species were sucked out by the water-cooled gun and continuously measured by an analyzer. Resolutions of O2 and CO are 0.1% and 1ppm. CO2 is calculated continuously according to the measured O2 concentration. The coal fired is shown in Table 14. As ratios of the central air increase from 0.8% to 4.9%, velocities of the central air increase from 4.0m/s to 24.5m/s, and gas temperature on axis decreases about 263℃. Especially as ratio of the central air is 4.9%, the gas temperature was only 927℃ at x/db=0.46(x=500mm). As ratio of the central air is0.8%, with increase of distance, O2 decreases quickly, and becomes to be about 4.5%. Meanwhile, CO2 and O2 increase instantly, and CO2 becomes to be about 14.5%. This makes the zone of the reverse flow become the zone of reducing atmosphere. On the contrast, as ratio of the central air is 4.9%, O2 increases quickly, and CO and CO2 maintain relatively small. At x=800mm(x/db=0.74), O2 decreases to be 18.9%. This makes the zone of the central air become the zone of oxidizing atmosphere.
Figure 81. In-situ gas temperature along axis of burner.
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Figure 82. In-situ species along axis of burner.
Table 14. Fired coal composition on the 670-tph boiler Proximate analysis, Wt % (as received) Moisture
Ash
9.20 33.68 Ultimate analysis, Wt % (as received) Carbon Hydrogen 45.88 3.23
Volatile matter 23.20
Fixed carbon 33.92
Net heating value (KJ/kg) 18343
Oxygen 6.38
Nitrogen 0.92
Sulfur 0.71
At 160MWe load, the furnace exit O2 kept to be constant. Then, NOx emission of boiler was measured with damper of the central air at different positions. Each case lasted about four hours. The coal fired is shown in Table 14. MSI compact analyzer made in German was used. Resolutions of NO and NO2 are 1ppm. The volume concentration of NOx is the sum of volume concentrations of NO and NO2. As position of the damper of the central air were changed from 0% to 100% open, NOx emission of boiler (Via O2=6%) increased from 216ppm to 226ppm. The increased value was only 10ppm. Effect of the central air on NOx formation can be explained as follows. With the increase of ratio of the central air, recirculated-mass flowrate decreases and gas temperature of the zone of the reverse flow decreases. It is advantageous to reduce the formation of thermal NOx. On the other side, with the increase of ratio of the central air, O2 increases and CO decreases. Thus, the oxidizing atmosphere is enhanced around the PF combustion zone. This is advantageous to the formation of fuel NOx. Therefore, the central air has a relatively small effect on NOx formation.
3. Conclusion (1) The central air will change the type of flow pattern. When the ratio of the central air is small, the part of the reverse flow zone at the burner exit in the central zone of the
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners… 1013 burner is blown away. A zone, where the axial velocity is positive, is formed like a taper cone. (2) As ratio of the central air increase, gas temperature greatly decreases and the oxidizing atmosphere is enhanced in the central zone of burner. NOx emissions of boiler increase slightly.
2.4.3. Influence of Air Supply on Nox Formation and Coal Burnout
1. Effect of the Burner Primary Air Ratio on Flow And Mixing Characteristics of Jet Experiments were carried out on a single-phase test facility to investigate the effect of the burner primary air ratio on flow and mixing of jet. The size ratio of the burner model to utility burner in a 670-tph coal-fired boiler is 1: 3. During the experiments, the fuel-rich primary air flux, total air flux, ratio of swirling secondary air to non-swirling secondary air (80%:20%) are constant. The burner primary air ratio is the ratio of the burner primary air flux to the burner total air flux. It was changed by changing the proportion between primary air and secondary air in the experiments. The primary air was heated to 60℃ and the other airflows were at ambient temperature. The profiles of air temperature near the burner outlet were measured. The maximum ratio of primary air shows the mixing of primary air and secondary air. With the increase of the burner primary air ratio, the primary air velocity and the air axial momentum of jet increase, but the total swirl number decreases because the burner primary air of the radial biased combustion burner is non-swirling. Figures 83, 84 and 85 show experiment results, where r1 is the burner primary air ratio. With the increase of the burner primary air ratio, the secondary air ratio declines, the divergent angle of jet, the length and diameter of central recirculation zone decreases sharply. Those phenomenons also appear in the air cold experiment of the utility burner. Otherwise, with the increase of the burner primary air ratio, the ratio of primary air and the maximum ratio of primary air at the measured points increase. It shows that the mixing of primary air and secondary air decreases.
Figure 83. Effect of the burner primary air ratio on central recirculation zone and divergent angles of jet.
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Figure 84. Effect of the burner primary air ratio on characteristics of mixing of primary air and secondary air.
Figure 85. Effect of the burner primary air ratio on the maximum ratio of primary air.
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2. Effect of Stoichiometric Ratio on the Nox Formation and Coal Burnout (1) Experimental Boiler Experiments were carried out on a 220-tph boiler of a power plant (see 2.4.1 Section). In cold air experiments, the results of measured velocities at the burner outlet show that the secondary air fluxes of the burners from the same air box are uniform. The stoichiometric ratio of the burner is the ratio of air mass supplied by burner to the theoretical air mass which is used for coal to burn out completely. It can be calculated according to the excess air coefficient at the furnace outlet, the secondary air mass fluxes of up and bottom air boxes and the primary air mass flux, which were measured in the experiments. There is no central air during the experiments. While the primary air mass flux is constant, the secondary air supply to up and bottom burners is changed by adjusting the opening of dampers in the air boxes. The total air mass flux and stoichiometric ratio of a burner are changed respectively. In the reacting low experiment, the boiler operational parameters such as the load, the furnace exit O2, and the coal feed rate were kept constant. The boiler load was 195.5tph. The secondary air dampers of burners are 0% open. Table 15 shows the characteristics of the coal used in the experiments. Table 15. Burned coal composition on the 220-tph boiler Proximate analysis, Wt % (as received) Moisture
Ash
3.20 36.38 Ultimate analysis, Wt % (as received) Carbon Hydrogen 52.55 3.16
Volatile matter 20.43
Fixed carbon 39.99
Net heating value (KJ/kg) 19881
Oxygen 3.62
Nitrogen 0.60
Sulfur 0.50
Notes: R90=39.12%，R200=5.35%.
(2) Effect of Stoichiometric Ratio on the Nox Formation of the Burner Near the burner region, gases were sampled by a water-cooled gun. Figures 86-89 show profiles of gas components on the central axis of the burner [19, 54], where db is the diameter, Ф798mm, and SR is the stoichiometric ratio of the burner. Cold air test in the boiler show that the central recirculation zone of jet with the length of 1.29 db and diameter of 0.65 db, begins at the central cone of the burner. In the experiments, components of gases were measured in the central recirculation zone. Figure 86 shows that with the jet developing, the Nox concentration on the central axis of the burner increases in the measured zone and rises sharply ahead of x=0.2 db where the fuel Nox is mainly formed. With SR=1.02, the NOx mean concentration is the largest and larger at the burner outlet. As SR is more or less than 1, the more or the less the SR is, the more the NOx mean concentration decreases. With SR1, the supplied secondary air is larger and the primary air ratio is less. The divergent angle of jet, the diameter and length of central recirculation zone increase. It is advantageous to the coal ignition in time. Figure 89 shows with the increase of SR, the distance from the position of the minimum O2 concentration to the burner decrease. Therefore, the position of coal ignition is closer to the burner outlet. It makes the temperature of the fuel-rich primary air/coal mixture rise fast. The rapid increase of coal temperature makes the volatile release fast. Then, the large volatile concentration is formed. Because the fuel-rich primary air/coal mixture is non-swirling and the particle inertia is large, the quantity of pulverized coal entering the central recirculation zone increases with the increase of central recirculation zone diameter. The combustion of those pulverized coal reduces the O2 concentration in the central recirculation zone and increases the CO concentration (see Figs. 87 and 89). It is advantageous to reducing the fuel-volatile NOx [28]. Furthermore, the rapid ignition of pulverized coal and the larger central recirculation zone increase the time of pulverized coal in the reducing atmosphere. It reduces the fuel NOx formation. So, the NOx mean concentration decreases in the central zone of the burner.
Figure 90. Profiles of NOx concentration of No. 4 burner with different SR at x =2.4 db (1920mm).
Figure 90 shows profiles of NOx concentration, where x is the distance from the measured points to the burner outlet along the jet flow direction. The NOx concentrations of No. 4 burner were measured by a water-cooled gun through the monitor port at the side wall near the burner. In Figure 90, r is the distance from sampling point to the burner axis. As SR increases from 0.79 to 1.02 or decreases from 1.66 to 1.02, the NOx concentration declines. The results are in concordance with the above analysis.
Radial-Bias-Combustion and Central-Fuel-Rich Swirl Pulverized Coal Burners… 1019 In conclusion, when the stoichiometric ratio of burner is more or less than 1, the oxidative atmosphere decreases and the reducing atmosphere increases in the center of burner region so that the NOx formation reduces.
(3) Effect of Air Supply of Up and Bottom Burners on Nox Emission and Coal Burnout With different openings of dampers in the up and bottom air boxes, the O2 concentration at the outlet of economizer is at the range from 3.0% to 3.5%, the furnace gas temperature is 1291-1359℃ at the elevation of 6100mm and 1374-1443℃ at the elevation of 8300mm. It shows that the different air supply of up and bottom burners has no influence on the total air supply and normal coal combustion in the furnace. Figure 91 shows the effect on the unburned combustible loss (q4) and the NOx emission in flue gas, where SR1 is the stoichiometric ratio of up burners and SR2 is the stoichiometric ratio of bottom burners. As the SR1 and the SR2 are farther from 1, the NOx emission is less and the unburned combustible loss is larger. The unburned combustible loss with SR1>1 and SR2 Φ + (am ) and Φ − (ai ) < Φ − (am ) ⎫ ⎫ ⎪ I ⎪ + ⎪⎪ + − − if ⎪ai P am (a i outrank a m ) ⎨Φ (ai ) = Φ (am ) and Φ (ai ) < Φ (am ) ⎬ ⎪ ⎪ ⎪ + ⎪⎪ + − − ⎪ ⎩Φ (ai ) > Φ (am ) and Φ (ai ) = Φ (am ) ⎭ ⎪ ⎪⎪ ⎪⎪ ⎬ ⎨ I Φ + (ai ) = Φ + (am ) and Φ − (ai ) = Φ − (am ) ⎪ ⎪ai I am (a i is indifferent to a m ) if ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ I ⎪⎭ ⎪⎩ai R am (a i and a m are incomparable) otherwise
(7)
where PI, II, and RI stand for preference, indifference and incomparability. Finally ai outranks am if:
Φ + (ai ) ≥ Φ + (am ) and Φ − (ai ) ≤ Φ − (a m )
(8)
Equality in Φ+ and Φ- indicates indifference between the two compared alternatives. Under the Promethee I method some actions remain incomparable, in the case that a complete preorder is required that eliminates any incomparable items, then Promethee II can give a complete ranking as follows [31]:
Φ net (ai ) = Φ + (ai ) − Φ − (ai )
(9)
The net flow is the difference between the out-flow and the in-flow.
4. EVALUATION OF ALTERNATIVE ENERGY PROJECTS USING PROMETHEE 4.1 The Proposed Energy Options 4.1.1. Photovoltaic Photovoltaic conversion technology (PV) was initially developed in the late 1950s as part of the space programme which required a reliable and inexhaustible source of energy. PV has been known since the end of the last century but the first commercial application was achieved in 1954; by Bell laboratory researchers in the United States when they perfected the first photovoltaic cell using monocrystalline silicon. Nowadays, its use is spreading very
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rapidly, in part due to advances in technology, even to terrestrial applications such as fuel for isolated users or for installations in buildings linked up to a pre-existing electricity grid. The growth in the PV market certainly represents one of the long term strategic objectives for future worldwide energy policy and poses a research challenge in the field of RES. In general, commercial competitiveness is the element that most heavily affects the extent of the spread of installations exploiting RES as this is heavily affected by the cost of building the installations and their operating and maintenance costs. The production costs of technologies that exploit solar energy are unfortunately still extremely high but these could be reduced in the future if production volumes improve. From a theoretical point of view, cost reductions can come about when a combination of improvements is seen: in technological performance of production together with the optimisation of production cycles to enhance levels of the amounts produced. The crucial parameter for shifting the production cost curve is represented by capacity to innovate that is generated by research activity. Thus cost reductions can be achieved by steady market growth together with research efforts and spinoffs from other high-tech sectors of industry, such as micro-electronics, nanotechnology, the car industry and space sector. As has happened in other technological sectors, new products will come onto the market thereby allowing further cost reductions. The world PV market has seen considerable development over recent years, with a recorded annual growth rate of more than 30% and reached a total installed capacity of over 5000 MW in 2005 [33]. According to data from the report Marketbuzz, 2006 [34], despite the high price of silicon, new installations worldwide in 2005 amounted to 1,460 MW; a growth of 34% compared to 2004. 57% of the installations were in Germany alone leading it to exceed 1,500 MW of total power [33]. Market conditions differ substantially from country to country and this is due to the different energy policies implemented by different governments, whether there are support programmes for renewable sources and the differing degree of liberalisation of the electricity market. It is interesting to note that the specific legal provisions and regulations adopted by each country affect the effectiveness of any measures adopted to develop this sector. In some states where the rules do not include a system of charges to cover expenditure then the market impact is fairly marginal. In other countries, where prices are sufficiently high, effectiveness can be limited by allowing incentive tariffs for too short a period of validity or by bureaucracy and administration that is overly complicated and labyrinthine. In Europe, the markets in Germany and Spain have been highly dynamic and production of cells and modules has grown more rapidly than in other member states. Undoubtedly, this is attributable not only to a model of incentives that is clear, transparent and streamlined, but also to stable political and socio economic conditions that have favoured the creation of a secure and trustworthy climate for investors. Such a scenario has not only persuaded private and commercial investors to install PV plants but has, above all, boosted investments in R&D and has created the conditions to expand production capacity of cells and modules of industries in this sector[35].
4.1.2. Wind Power Nowadays, wind energy is without a doubt the most mature and commercially competitive of the new renewable sources and represents the segment of the market enjoying the highest growth rate in the entire energy sector. The expansion and the commercialisation of wind turbines has always coincided with their technological development. Now the market and technologies are specialising in order to maximise production under all conditions. Thus,
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there are now wind turbines specifically designed for offshore applications, to handle variable windspeeds and direction, turbines for turbulent winds and for small scale applications (from farms on the American flatlands to villages in developing countries). Modern wind turbines have modular features, they are reliable and can be installed on site in a very short space of time, they are built to operate continuously, are low maintenance and require few personnel over their lifespan lasting more than 20 years [36]. Areas for research and development (R&D) are numerous and concern mainly the use of innovative materials in order to build increasingly larger systems at contained prices and to increase the efficiency and reliability of the system. The geographical area that is most widely equipped with wind power installations is Europe, accounting for around 74% of the total, with 50% of this being the German Wind Park. Spain, Denmark and Italy are the other countries in Europe with significant wind energy installations whilst in the rest of the world the USA takes the lead with 14% of the total, India accounts for 6%, while China and Japan the figure is around’1.5%. Whilst Germany is the undisputed world leader in the sector, the USA has shown an upward but inconstant trend in wind power development and India has also shown marked development in recent years [36]. Electricity production from wind power in the EU amounted to 69 TWh in 2005 with Germany (27.2 TWh) and Spain (21 TWh) accounting for more than 50% of this. Denmark came in third place (6.6 TWh), followed by Italy, Holland and the UK with production of around 2 TWh [33]. The industry that produces wind generators is highly concentrated, with the four leading firms accounting for around 70% of total power in Europe in 2005: the Danish company Vestas with 35%, the German Enercon with 14.4%, Gamesa from Spain with 13.4%, and the US business GEWind with 12.4% [33]. The costs of generating electricity from wind sources have come down steadily and visibly over the last 15 years as a result of the increased efficiency of wind turbines as well as their lower cost due not only to economies of scale that have been seen in the sector but also as a result of research and new technologies available, especially in the processes involved in manufacturing the various component parts of the aerogenerators.
4.1.3. Solar Chimney The thermal solar chimney is a recently developed technology patented by “Schlaich Bergermann und Partner” which uses a large cylindrical tower that is able to exploit energy from the sun to produce electricity. The system comprises a glass collector, a chimney and wind turbines. It works on the basis of the following principle: a large mass of cold air enters freely underneath a large glass roof (glass collector) that is open around its periphery. Solar radiation heats this air until it reaches a temperature in excess of 35°C, thus creating an artificial greenhouse. The hot air tends naturally to move towards the centre of the collector where a cylindrical tower made of cement is located. This mass of hot air rises (hot air being less dense and thus lighter than cold) up the chimney tower thereby supplying a natural convective force (see Figure 4) [37] [38]. This flow of air, which rises at a speed of 14-16 m/s, is captured by a set of wind turbines located at the chimney base which convert kinetic energy from the wind induced by solar heat into mechanical energy and then into electricity.
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4.1.4. Parabolic Solar Trough The technology relating to linear parabolic troughs is at a more advanced stage than other types of concentrated solar power technologies (parabolic dish and solar tower). Systems using linear parabolic mirrors called SEGS (Solar Electric Generating Systems) are to date the most developed commercially speaking, typically ranging in size from 30 to 80 MWatt.
Figure 4. Solar chimney principle [37].
Figure 5. Diagram of a parabolic trough power plant with two-tank molten salt storage[41].
These devices first appeared in 1984 when the LUZ Company installed a 14 MW solar energy power plant (SEGS I) in southern California, using parabolic trough solar collectors and supplementing it with natural gas as fuel to allow the system to work during periods when there is little sun or while closed down for maintenance. A parabolic trough power plant with heat storage is made up of three basic parts [39] [40] [41]: 1) the solar field fitted with a circuit for heat transfer; 2) a system for storing heat; 3) a power block comprising a turbine, a
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generator and a cooling system (see Figure 5). This technology uses a curved mirror system to concentrate solar radiation onto a high thermal performance absorbent pipe laid along the focal line of the concentrators inside of which flows a fluid for heat transfer. In such an installation, the solar field has a modular structure composed of linear parabolic collectors linked in series laid out in parallel rows up to several hundred metres in length. The fluid that carries the heat absorbed from the sun is generally a mineral oil and is pumped through receiver pipes to a power plant. Here a heat exchanger converts the heat into steam which is then sent to a turbine to produce electricity.
4.1.5. Solar Tower The technology relating to Solar power towers is commercially at a less advanced stage than linear parabolic trough collectors. Despite this, a number of experimental stations have been tested on the field in a variety of sites scattered all over the world in the last 15 years. These have demonstrated their project feasibility and the economic potential of this technology. The plant consists of a set of mirrors, called heliostats, that track the movement of the sun on a double axis and which reflect solar energy onto a receiver (heat exchanger) mounted on the top of a tower positioned at the centre of the array of mirrors. A fluid transfers the heat from the receiver to a steam generator that drives a turbine. The heat transfer medium can be: steam/water, molten salts, liquid sodium or air. If gas or compressed air is used then extremely high temperatures can be reached thus achieving a very high level of efficiency [42]. As for other renewable energy sources, one of the limitations solar energy has to overcome is the inconstancy of the energy available which means that storage systems are a highly important feature that affect the advancement and spread of the technologies developed. A storage system has to guarantee energy supply even when no solar energy is available (at night or when the sky is overcast or cloudy). The energy produced by thermal solar installations may not necessarily be limited only to hours of sunshine and by cloud movements. The central receiver can heat the fluid, for example molten salts, which also serve as energy storage. The hypothetical installation consists of a type of solar power tower like the ones known as PS10 with a power 11 MWe which are to be built in Spain. The PS10 solar tower according to designers should be capable of producing 23 million kWh of electricity annually, that is enough energy to satisfy the demand of 10.000 families. The
Figure 6. Flow diagram of the PS10 solar tower power plant [44].
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project envisages the use of saturated steam as Heat Transfer Fluid (HTF). The system combines a field of 624 heliostats (each with a surface area of 121 m2) produced by the Spanish firm Solucar, for a total reflective surface area of 75,216 m2, a 100 metre high tower, a receiver that is able to produce saturated steam at 40 bar and 250 C° and heat storage system for steam with a capacity of 15 MWh able to supply 50 minutes of plant operation time at 50% load [43].
4.1.6. Dish - Stirling Dish – Stirling systems have been tested mainly in the United States and in Europe since the mid 1980s and the results have been highly encouraging. In these systems the conversion of solar energy into electricity is particularly efficient with a net average annual yield rate ranging between 18 and 23%, higher than any other solar energy system, and have attained a record rate of 29% for a brief time. The dish concentrator reflects solar rays onto a concave receiver positioned at the focal point of the concentrator. Solar radiation is absorbed by the receiver which heats a gas (helium or hydrogen) in the Stirling engine up to a temperature of around 650°C [44]. The heat from the sun is converted into mechanical energy by the Stirling engine and this mechanical energy is subsequently converted into electricity by a generator directly connected to the engine. Optimal functioning requires that the concentrator is perfectly orientated towards the sun, therefore it is mounted on a two-axis tracking system that allows the concentrator to be aligned vertically and horizontally (see Figure 7).
Figure 7. Scheme of the Dish/Stirling system [44].
The alignment towards the sun is controlled by a tracking sensor of the sun or by a special software that instantaneously and continuously calculates the position of the sun [45] [46]. The choice of installing a Stirling engine is dictated by the fact that the Stirling cycle is the most efficient thermodynamic cycle for transforming heat into mechanical energy and electricity, thus its extraordinary properties make it suitable for this type of application. The size of individual installations can vary between 5 and 50 kWatt. The most important feature
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of these systems is their modularity allowing installations of any size or power to be built. The beauty of this technology is that its size can be adjusted to fit user needs: from a few kW, for use in remote sites or islands, up to hundreds of kW for “distributed generation” uses connected to the electricity grid. Unfortunately, the high unit costs reflect the fact that these systems have not reached a high level of technological maturity. The technology is still at the prototype stage of development and the industrialisation that would allow it to be commercially exploited on a large scale is not foreseen in the short term.
4.1.7. Biomass The case studied envisaged the construction of a 10 MWe installation using a steam boiler fuelled by energy crops, in particular by “Miscanthus” which is capable of producing 38,6 MWth with a 25% yield. A fluid bed combustion system was chosen over a oven grid combustion system despite its higher cost because it offers greater assurances in terms of environmental performance. Environmental performance levels are important because this system can reduce SOx by as much as 90% to stable gas residues and NOx as a result of the lower temperature for combustion. The phase to remove pollutants concludes with the extraction of particulate from smoke by the use of filters.
4.2. Sets of Criteria: Identification and Selection The criteria are the tools that enable alternatives to be compared from a specific viewpoint. Undoubtedly, selecting criteria is the most delicate part in formulating the problem before the decision maker, and thus it is requires the utmost care and attention. The number of criteria is heavily dependent on the availability of both quantitative and qualitative information and data. Here 14 criteria were selected; 9 of these technical-economic and 5 socio-environmental. Quantitative measures apply to 8 of the criteria while the remaining 6, being qualitative in nature, were scored by applying impact scales from either 1-4 or 1-5.
Economic and Technical Criteria These criteria refer to the costs that must be borne in order to realize the various projects included in each strategy and to guarantee the supply of energy. These factors are of special interest to State authorities. •
•
•
Investment costs. This includes all costs relating to the purchase of mechanical equipment, technological installations, to construction of roads and connections to the national grid, to engineering services, drilling and other incidental construction work. This criterion is measured in Euros; Operating and maintenance costs. This includes all the costs relating to plants, employees’ wages, materials and installations, transport and hire charges, and any ground rentals payable. This criterion is measured in Euros; Levelized electricity cost (LEC). This measures the production cost per kWh of the electricity generated by the plant expressed as Euro cents. This parameter is important and useful for assessing how commercially competitive the system is compared with conventional energy production technologies;
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•
•
•
•
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Financial risk. This identifies the degree of financial risk attached to the technological options proposed and is measured using the following scale of values: − Low risk=1 − Medium=2 − High=3 − Very high=4 Primary energy saving. This refers to the amount of fossil fuel currently used by power plants to produce electricity that could be saved. It is measured in ton/per annum; Maturity of technology. Measures the degree of reliability of the technology adopted as well as how widespread the technology is at both national and European level. This is appraised using a qualitative judgment transformed into the following fourpoint scale [6]: − Technologies at theoretical level=1 − Technologies tested in laboratory= 2 − Technologies only performed in pilot plants and/or under construction =3 − Technologies requiring further improvements to increase their efficiency levels=4; − Commercially mature technologies on the market=5; Continuity of power supply: This criterion indicates whether the energy supply is subject to interruptions (e.g. PV does not work at night, wind generators cannot function when there is no wind, etc.) and thereby affects the stability of the electricity grid. This case is also evaluated qualitatively and expressed via the following fourpoint scale: − Highly discontinuous activity =1 − Moderately discontinuous activity =2 − Slightly discontinuous activity =3; − Stable and continued activity (except when the plant undergoes maintenance)=4; Storage capacity : this criterion indicates whether any storage systems are fitted that are able to ensure continuity of electricity supply (e.g. in the absence of solar radiation or other factors ) and is calculated on the basis of the number of hours of autonomy provided; Realization time. This measures the time to realize and put into operation the plants designed. It is expressed in number of months.
Environmental and Social Criteria These criteria refer to protection of the environment and to the principle of sustainability: •
•
Sustainability of Climate Change: This refers to the amount of CO2 emissions avoided as a result of the production of the proposed plants. It is measured in tons/per annum. Sustainability of other impacts: This criterion takes into account other impacts: the visual nuisance that may be created by the development of a project in a specific area or any noise disturbance and odours arising from productive activity of plants, the potential risk to eco-systems caused by the production operations of the various
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Fausto Cavallaro projects included in the strategies. This is also measured qualitatively and translated into the following five-point scale [6]: − Extremely high impact=1 − High impact=2 − Moderate impact=3 − Slight impact=4 − No impact =5. Social acceptability. Expresses the index of acceptance by the local population regarding the hypothesized realization of the projects under review. The following four-point qualitative scale was applied: − The majority of inhabitants are against the installation of any plant whatsoever regardless of where it is =1 − The opinion of the population regarding the installations is split =2 − The majority accepts the installations provided they are located far from residential areas =3 − The majority of inhabitants are favourably disposed towards the installations =4 Contribution to local development. This criterion estimates the global social and economic effects that may be felt in the areas affected by the initiatives. The potential effects are: the creation of new jobs, new supply chain businesses, emerging energy sector businesses, industrial districts etc. The following rating scale was applied: − Impact on local economy rated weak =1 − Impact on local economy rated moderate (some permanent jobs)=2 − Impact on local economy rated medium-high (jobs + supply chain businesses)=3 − Impact on local economy rated high (strong impetus to local development, creation of small industrial districts)=4 Land use. This criterion quantifies the area occupied by the plants and not available for possible alternative uses (i.e. agriculture or other economic activities). It is measured in m2 of land used.
4.3. The Evaluation Matrix Table 1 shows the matrix containing the alternatives and how these perform with respect to the evaluation criteria selected. The options proposed are the following: wind power, a medium sized installation made up of 15 turbines of 600 kW each giving a total power of 9 MW (W.1) and a larger 30 MW installation using 15 turbines of 2000 kW each (W.2). The two photovoltaic options considered are a 5MW installation (PV.1) and one of 15 MW (PV.2).
Table 1. Evaluation matrix Criteria Alternatives
A.1 Investment costs
A.2 O&M cost
A.3 LEC
A.4 Financial risk
B.1 Primary energy saving
B.2 Maturity of technology
B.3 Continuity of power supply
B.4
B.5
Storage
Realization
capacity
time
C.1
C.2
Sustainabilty
Other
of climate
environmental
change
impacts
C.3 Social acceptability
C.4 Contribution to local development
C.5 Land use
Euro (000)
Euro (000)
c/Euro
qualitative
ton/y
qualitative
qualitative
hours
months
ton/y
qualitative
qualitative
qualitative
Km2
W.1
Wind 600kW
10,800
324
0.07
low
10,180
commercial
slight disc.
0
18
17,720
slight
accept
moderate
0.02
W.2
Wind 2000kW
45,000
1,350
0.065
low
35,650
commercial
slight disc.
0
36
62.000
high
majority no
moderate
0.065
30,000
450
0.6
middle
3,431
further impr
high disc.
0
24
5,900
slight
favorable
moderate
0.09
75,000
1,125
0.5
high
10,290
further impr
high disc.
0
36
17,910
moderate
split
medium-high
0.27
153,000
11,800
0.17
very high
34,000
theory
10
36
59,160
high
majority no
medium-high
6.831
99,000
6,800
0.15
very high
21,000
theory
10
36
36,540
high
majority no
medium-high
4.153
117,000
2,879
0.106
middle
70,000
pilot
3
36
121,800
moderate
split
weak
1.459
91,000
2,670
0.12
middle
55,900
pilot
high disc.
0
24
97,200
moderate
split
weak
0.855
36,000
2,175
0.22
middle
12,000
pilot
high disc.
0.5
36
20,880
slight
split
moderate
0.372
180,000
8,035
0.38
very high
26,300
lab
high disc.
0
48
45,700
moderate
accept
moderate
0.84
40.000
1,025
0.9
low
6,690
commercial
slight disc.
0
24
19,400
high
majority no
medium-high
0.06
PV.1 PV.2 SCh.1 SCh.2 PST.1 PST.2 STo DS Biom
Photovoltaic 5MW Photovoltaic 15MW Solar Chimney 30MW Solar Chimney 15MW Parabolic solar trough 50MW Parabolic solar trough 50MW Solar Tower 11MW Solar DishStirling Biomass 20MW
middle disc. middle disc. middle disc.
Table 2. Thresholds
A.1
A.2
A.3
A.4
B.1
B.2
B.3
B.4
B.5
C.1
C.2
C.3
C.4
C.5
Min/Max
Minimize
Minimize
Minimize
Minimize
Maximize
Maximize
Maximize
Maximize
Minimize
Maximize
Maximize
Maximize
Maximize
Minimize
Weight
0.8
0.8
0.9
0.7
0.9
0.4
0.7
0.4
0.4
0.9
0.9
0.5
0.5
0.8
V-Shape
V-Shape
Linear
Linear
Linear
Linear
Linear
V-Shape
V-Shape
Linear
Linear
Linear
Linear
Linear
-
-
5%
0.5
5%
0.5
1
-
-
5%
0.5
0.5
0.5
5%
10%
10%
15%
1
10%
1
1.5
2
10
10%
1
1
1
10%
Percent
Percent
Percent
Absolute
Percent
Absolute
Absolute
Absolute
Absolute
Percent
Absolute
Absolute
Absolute
Percent
Preference function Indifference threshold Preference threshold Threshold unit
Table 3. Preference flows Actions W.1 W.2 PV.1 PV.2 SCh.1 SCh.2 PST.1 PST.2 STo DS Biom
Φ+ 0.6531 0.5524 0.4385 0.3218 0.2752 0.2582 0.449 0.4503 0.407 0.276 0.4035
Φ0.181 0.238 0.404 0.484 0.511 0.555 0.371 0.363 0.407 0.559 0.412
Net flow Φ(a) = Φ+ (a) − Φ− (a) 0.473 0.315 0.034 -0.16 -0.24 -0.3 0.078 0.088 0 -0.28 -0.01
Ranking 1 2 5 8 9 11 4 3 6 10 7
Table 4. Weight stability interval
Criteria A.1 A.2 A.3 A.4 B.1 B.2 B.3 B.4 B.5 C.1 C.2 C.3 C.4 C.5
Figure 8. Partial ranking.
Weight 0.8 0.8 0.9 0.7 0.9 0.4 0.7 0.4 0.4 0.9 0.9 0.5 0.5 0.8
Absolute values Min 0.621 0.384 0.799 0 0.766 0.03 0 0.027 0.302 0.69 0.846 0.399 0 0.489
Max 1.067 1.039 1.476 0.815 1.316 0.458 0.801 0.501 0.485 1.342 1.471 0.826 0.59 0.912
Weight 8.33% 8.33% 9.38% 7.29% 9.38% 4.17% 7.29% 4.17% 4.17% 9.38% 9.38% 5.21% 5.21% 8.33%
Relative values (%) Min 6.59% 4.18% 8.41% 0.00% 8.09% 0.33% 0.00% 0.30% 3.18% 7.35% 8.86% 4.20% 0.00% 5.27%
Max 10.81% 10.56% 14.50% 8.39% 13.14% 4.74% 8.25% 5.16% 5.01% 13.36% 14.46% 8.32% 6.08% 9.39%
Figure 9. Final ranking.
Figure 10. Partial ranking (equal weight for criteria).
Figure 11. Final ranking (equal weight for criteria).
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The options using solar chimney technology relate to one installation with a power capacity of 30 MW (SCh.1) installed on a site where solar radiation amounts to 1,800 kWh/m2/y (typical of the southern Mediterranean), and the other of 15MW (SCh.2) which is designed to be installed in areas with solar radiation of 2,300 kWh/m2/yThe proposed options for linear parabolic trough collectors are a 50MW installation (PST.1), fitted with an energy storage system and the other of the same capacity but without any storage system (PST.2), The remaining options proposed are one using solar power tower technology with a power capacity of 10MW (STo), an installation containing parabolic dish-stirling concentrators (DS) and a steam boiler of 20 MW fuelled by biomass (energy crops) (Biom).
Figure 12. GAIA plane.
The performance data relating to items measured quantitatively were extrapolated from published findings in the literature. The data evaluated qualitatively are the outcome of assessments and estimates. Before looking at the results in detail it is important to clarify a number of points regarding the data reported in the matrix. The costs relating to investment and maintenance, the industrial cost of production per kWh and the level of energy production, have been calculated based on data extracted from the following publications: [41] [43] [44] [45] [46] [47] [48] [49]. The criterion relating to financial risk based on market estimates shows a very high risk profile for options SCh.1, SCh.2 and DS reflecting the fact
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that the technologies are still in the preliminary study phase or in the experimental phase in the laboratory, thus their economic and financial profile is highly uncertain. The continuity of energy supply is an extremely important criterion to ensure that the grid is stable and not liable to black-outs. Nearly all the technologies analysed, with the exception of those equipped with a storage system, are subject to a fair degree of discontinuity, either because of differences between daytime and night or varying meteorological/climatic conditions. Environmental impact is probably the most delicate item of the whole assessment. The most significant impact is found for the option using biomass due to emissions of some pollutants (not harmful), and for the solar chimney options as result of the large area of land required to build the installation on, as well as the great visual impact created by the tower. It is also reasonable to assume that the wind energy installation will also be visually intrusive because the wind turbines are so large in size. These also constitute a potential collision hazard to birds in flight. The alternatives relating to parabolic trough and solar tower technologies apart from occupying a certain amount of land do not give rise to any other significant changes to the environment therefore their environmental impact are judged to be moderate. The greatest uncertainties attach to the evaluation of social acceptability and their contribution to local development as these could be strongly affected by prejudices that bias the results. Generally speaking, the population views installations using renewable sources favourably, but only if they are built far from human settlements and do not cause any nuisance to the population. The level of acceptance will therefore depend greatly on the exact locations of the installations. Estimates relating to these two criteria come from a survey carried out on a sample of the population that did not show react positively to the proposed projects.
4.4. Main Results Two distinct rankings of alternatives are computed and displayed. The first is PROMETHEE I which gives a partial ranking. It is based on strongly established preferences so some actions remain incomparable under this method. Figure 8 graphically illustrates the positions of each alternative in the partial ranking and it is immediately apparent that the best performers are W.1, W.2 and PST.2. The first two of these also come out top in the final ranking and thus attest to the credibility of both the method and to the findings. Clearly, wind power is at a more commercial and competitive stage of development compared to other new energy technologies and the results obtained are comforting in that they are consistent with a well-consolidated fact. Next in the ranking come the options PST.1, PV.1, STo, Biom, and PV.2. The lowest ranked are the options SCh.1 and SCh.2 which are shown to be incomparable with the DS option. These technologies are still heavily penalised by high costs of investment and maintenance. The highly innovative status of these projects means that technologically they are still very immature and this greatly affects the economic-financial risks attached to these initiatives. Figure 9 shows the results from PROMETHEE 2 which gives a complete ranking: all actions are ranked from the best to worst leaving no incomparable pair of actions. This information is easier to use than partial ranking but does reflect less reliable preferences. Table 4 gives the weights assigned to the criteria together with the weight stability intervals
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that give for each criterion the limits within which its weight can be modified without changing the PROMETHEE II complete ranking. The results of multi-criteria analysis hinge on the weightings allocated and thresholds set. As stated earlier, the weights express the importance of each criterion and obviously may deeply influence the final outcome of the entire calculation procedure. For some authors, the problem of how to determine the weights to assign is still unresolved since the different outranking methods do not lay down any standard procedure or guidelines for determining them. In order to examine any changes in the final outcome after correcting the weights previously assigned to the various criteria a sensitivity analysis was performed by assigning an equal weight to all the criteria selected. This calculation revealed that the position in the ranking did change for some options although the overall structure of the ranking from the previous analysis was more or less unchanged. The options PV.1 and Biom moved up from 5th and 7th place to 3rd and 4th and emerged as incomparable with each other. The options PST.1 and PST.2 slid from 2nd and 3rd place down to 5th and 6th place and were also found to be incomparable (see Figure 10 and 11). The GAIA (geometrical analysis for interactive aid) plane provides the decision maker with a comprehensive graphical image of the decision problem and it is complementary to the multicriteria analysis. This tool provides clear graphical information regarding the conflicting characters of the criteria and about the weights on the final decision. Figure 12 illustrates this analysis: actions are represented as triangles and criteria as lines. The direction of the PI axis (the line that joins the two dots) identifies the compromise solution, in our case the axis is moving towards alternative W.1 and W.2. By examining a GAIA graph it is possible to see where the action lies in relation to the criteria, measure how intensely the criteria affect each action and thereby identify the criteria that are in line with or conflict with the various alternatives.
CONCLUSION Figure 8 graphically illustrates the positions of each alternative in the partial ranking and it is immediately apparent that the best performers are W.1, W.2 and PST.2. These are followed by the options PST.1, PV.1, STo, Biom, and PV.2. The bottom ranking positions are occupied by the options SCh.1 and SCh.2, which are shown to be incomparable with the DS option. A sensitivity analysis was performed by equally weighting all the criteria and comparing the ranking obtained with the original. The two rankings were found to be similar although the position of some options shifted slightly; with the options PV.1 and Biom moving up from 5th and 7th place to 3rd and 4th and emerged as incomparable with each other whilst PST.1 and PST.2 moved down from 2nd and 3rd place to 5th and 6th and were also found to be incomparable with each other. This work has therefore attempted to test the soundness and strength of multicriteria analysis as a means to serve energy planners as an unambiguous tool for decision making. DSS are well-suited to dealing with highly structured problems or semi-structured ones (for which it is not possible to produce an ideal solution). DSS help the user in all phases of the decision making process by using relevant information in order to make choices that can be documented and are transparent.
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Assessment procedures and energy planning may appear complex because of the number and diversity of the items to evaluate, the uncertainty of data and conflicts between interested parties. The decision making process of an energy project is the closing link in the process of analysing and handling different types of information: environmental, technical, economic and social. As this work demonstrates, multicriteria analysis can provide a technical-scientific decision making support tool that is able to justify its choices clearly and consistently.
ACKNOWLEDGMENT I wish to thank Dr. Maria Cristiana Laurà and Ms Susan H. Parker B. A., A.C.A. for their precious help and cooperation.
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[31] Brans J.P., Mareschal B. (1994). The Promcalc and Gaia decision support system for multicriteria decision aid. Decision Support System, 12, 297-310. [32] Brans J.P., Mareschal B. (1998). Multicriteria decision aid the Promethee-Gaia solution. Working paper, Vrije Universiteit Brussel, STOOTW/288. [33] Nomisma Energia (2007). Le nuove fonti rinnovabili per l’energia elettrica in Europa. [34] www.marketbuzz.com. [35] Arnulf Jäger-Waldau, PV Status Report 2005 - Research, Solar Cell Production and Market Implementation of Photovoltaics. European Commission, DG JRC, Institute for Environment and Sustainability, Renewable Energies Unit. EUR 21836 EN. [36] ENEA (2005). Rapporto Energia e Ambiente. [37] Schlaich J., Bergermann R., Schiel W., Weinrebe G., (2005). Design of Commercial Solar Updraft Tower Systems— Utilization of Solar Induced Convective Flows for Power Generation. Journal of Solar Energy Engineering, 127, 117-124. [38] Von Backstrom T.W., Gannon A.J. (2004). Solar chimney turbine characteristics. Solar Energy, 76, 235–241. [39] www.solarmillenium.de. [40] Price H., Kearney D. (1999). Parabolic-Trough Technology Roadmap: A Pathway for Sustained Commercial Development and Deployment of Parabolic- Trough Technology. NREL Report. [41] Herrmann U., Kelly B., Price H. (2004). Two-tank molten salt storage for parabolic trough solar power plants. Energy, 29, 883–893. [42] Reilly H.E., Kolb G.J., (2001). An evaluation of molten salt power towers including results of the solar two project. Sandia National Laboratories - USA. [43] Osuna R., Olavarría R., Morillo R., Sánchez M., Cantero F., Fernández-Quero V., Robles P., López del Cerro T., Esteban A., Cerón F., Talegón J., Romero M., Téllez F., Marcos M.J., Martínez D., Valverde A., Monterreal R., Pitz-Paal R., Brakmann G., Ruiz V., Silva M., Menna P. (2006). PS10- Construction of a 11MW solar thermal tower plant in Seville - Spain. Proceedings of 13th International Symposium on Concentrated Solar Power and Chemical Energy Technologies SolarPACES2006 A4S3, Seville –Spain. [44] Pitz-Paal R., Dersch J., Milow B. (editors). European Concentrated Solar Thermal Road-Mapping – Roadmap Document (SES-CT-2003-502578) ECOSTAR. [45] Marketaki K., Gekas V. (1999). Use of the thermodymamic cycle Stirling for electricity production. Proceedings of the 6th Panhellenic Symposium of Soft Energy Sources. [46] Tsoutsos T., Gekas V., Marketaki K. (2003). Technical and economical evaluation of solar thermal power generation. Renewable Energy, 28, 873–886. [47] Trieb F., Langnib O., Klaib H. (1997). Solar electricity generation – a comparative view of technologies, costs and environmental impact Solar energy, 59, 89-99. [48] Weinrebe G., Bergermann R., Schlaich J., Schiel W., Hornidge D. (2006). Commercial Aspects of Solar updraft towers. Proceedings of 13th International Symposium on Concentrated Solar Power and Chemical Energy Technologies, SolarPACES2006 A4S3, Seville – Spain.. [49] Kearney D., Kelly B., Herrmann U., Cable R., Pacheco J., Mahoney R., Price H., Blake D., Nava P., Potrovitza N. (2004). Engineering aspects of a molten salt heat transfer fluid in a trough solar field. Energy, 29, 861–870.
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 1139-1172
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 35
GAS TURBINES AND ELECTRIC DISTRIBUTION SYSTEM* Francisco Jurado† University of Jaén, Department of Electrical Engineering 23700 Alfonso X, nº 28, EPS Linares (Jaén), Spain
ABSTRACT Lately, the use of gas turbines following the deregulation of the electricity supply industry has become greater quickly. The motivation for modeling the gas turbines and their controllers is determinant to the interpreting of their impacts on distribution systems. The model predictive control (MPC) is used to damp the oscillation when the power distribution system is subjected to a disturbance. MPC is selected because it can explicitly handle the nonlinearities, and constraints of many variables in a single control formulation. The IEEE 13 node power distribution system is employed to demonstrate the effectiveness of MPC to damp the oscillations of gas turbines. Among fossil fuels, gas is the most quickest, with a growth rate nearly double that of coal and oil. The electricity generation field is the leading market for gas. The natural gas business has a great interaction with the electricity market in terms of fuel consumption and energy conversion. On the other hand, the transmission and distribution activities are very similar with the natural gas transportation through pipelines. The power losses in gas and electric systems are compared. It is also demonstrated that the electricity system results more convenient for longer distances of gas wells from electricity consumption area.
Keywords: Distribution networks, gas turbines, modeling, power loss, predictive control.
*
A version of this chapter was also published in Leading-Edge Electric Power Research edited by C.M. O’Sullivan published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research. † E-mail:
[email protected] Telephone: +34-953-648518 Fax: +34-953-648586.
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NOMENCLATURE Ao a, b, c cpa cpg cps
compressor exit flow area valve parameters specific heat of air at constant pressure (J/(kg K)) specific heat of combustion gases (J/(kg K)) specific heat of steam (J/(kg K))
Dk
internal diameter of pipe between nodes (m)
e1 f Fd
Fk
valve position vector of mass flow rates through branches fuel demand signal Fanning friction coefficient
fk
flow rate through compressor (m3/s)
f kij
pipeline flow rate (m3/s)
G
Hk KI KP kf kLHV LHV
Lk ma N
NP
gas specific gravity horsepower required to pump gas down PID parameter PID parameter fuel system gain constant factor which depends on LHV lower heating value (MJ/kg) pipeline length between nodes (m) polytropic index rotation speed of the turbine (rad/s) branches in the system
PDi
compressor power consumption (W) air pressure at compressor inlet (Pa) air pressure at compressor outlet (Pa) real power required at the ith bus
PGi
real power generated at the ith bus
PL Pm PT pTin pTout rc t T Tcout Tis
real power loss mechanical power delivered by turbine (W) total mechanical power delivered by turbine (W) pressure of combustion gases at turbine inlet (Pa) pressure of combustion gases at turbine outlet (Pa) pressure ratio (outlet/inlet) time (s) mechanical torque delivered by turbine (Nm) outlet air temperature (K) temperature of injected steam (K)
Pc pcin pcout
Gas Turbines and Electric Distribution System
Tka
average gas temperature (K)
Tki
compressor suction temperature (K)
T0
standard temperature (K)
TTin U(t) Vi Y T , UT w wa wf wg wis
wL
turbine inlet gas temperature (K) control signal voltage magnitude at the ith bus finite time Fourier transforms vector of gas injections at each node air mass flow into the compressor (kg/s) fuel mass flow (kg/s) turbine gas mass flow (kg/s) injection steam mass flow (kg/s) vector of gas demands
wS
vector of gas supplies
Yij
Za
magnitude of the i-jth element of the bus admittance matrix average gas compressibility factor
Z ki
gas compressibility factor at compressor inlet
⎛ cp ⎞ ⎟ ⎝ cv ⎠
specific heat ratio ⎜
ηk
angle of the i-jth element of the bus admittance matrix specific enthalpy of reaction at reference temperature of 25ºC (J/kg) isentropic enthalpy change for a compression from pcin to pcout (J/kg) isentropic enthalpy change for a gas expansion from pTin to pTout (J/kg) rotation speed deviation of the turbine (rad/s) phase angle of the voltage pipeline efficiency overall compressor efficiency compressor efficiency
ηT ηtrans η∞c
overall turbine efficiency transmission efficiency from turbine to compressor compressor polytropic efficiency
πi
pressure at node i (Pa)
πj
pressure at node j (Pa)
πic
compressor suction pressure (Pa)
π jc
compressor discharge pressure (Pa)
π0
standard pressure (Pa)
ρi τf
inlet air density fuel system time constant (s)
γij Δh25 ΔhIC ΔhIT ΔN δi
ε
ηc
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1. INTRODUCTION Gas turbines can offer solutions to today’s energy situation as a supplement or support function to the conventional central generation and power system (Willis and Scott, 2000). Complimentary answers are needed to meet projected growth in new load and peak demand while providing power system stability, security and end-user power quality solutions. Distributed generation (DG) integration into the existing power grid can enhance asset utilization without demanding major capital investment in new large generation or energy delivery facilities. Synchronous machine stability surveys have been a discipline of interest for many years. Much of the work produced has been based on steam- or hydro-turbine generating units. Power system stability is normally associated only with large utility systems. However, with DG operating in parallel with the utility, stability has become an issue that is crucial to preserve critical functions (Jurado and Carpio, 2005). Compared to the transmission system, the distribution system has several important characteristics. The power of DG is relatively small compared to the capacity of the substation. The substation is stiff enough to keep the frequency constant, thus can be conceived as an infinite bus. Model predictive control (MPC) is a control strategy that uses a model of the system to predict the response over a future interval, called the costing or prediction horizon (Maciejowski, 2002; Richalet, 1993; Qin and Badgwell, 2000). The application of MPC to control the gas turbine was introduced in (van Essen and de Lange, 2001; Vroemen et al., 1999). Model based control schemes are highly related to the accuracy of the process model. Evans concentrated on testing the gas turbine using small amplitude multisine signals and frequency domain techniques to identify linear models of high accuracy at a range of different operating points (Evans et al., 2000). The implementation of an efficient method for computing low order linear system models of gas turbines from time domain simulations is presented in (Jurado and Cano, 2004). This method is the Box-Jenkins algorithm for calculating the transfer function of a linear system from samples of its input and output.
The fact that the dynamics of these models change with operating points evidenced that the gas turbine is nonlinear, so the need was evident for a more accurate nonlinear modeling of the gas turbine. The work was formulated further by Chiras who used Nonlinear AutoRegressive Moving Average with eXogenous inputs (NARMAX), to represent the global dynamics of the gas turbine. It was
showed that both models were suitable for representing engine dynamics throughout its operating range (Chiras et al., 2002).
The Hammerstein model is a special kind of nonlinear systems which has applications in many engineering problems (Narendra and Gallman, 1996). A
frequency domain identification approach for Hammerstein models is proposed in (Jurado, 2005). By exploring the fundamental frequency, the linear part and the nonlinear part can be identified. The power system stability mostly depends on the excess kinetic energy stored in the generators during the fault duration period. The efficient control of the extra energy can be the most direct method to reach the system stabilization. There are various types of energy
Gas Turbines and Electric Distribution System
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storage devices which can be applied to control the surplus energy. However, all of the energy storage devices have the common shortcomings that they are very costly and require highly advanced control strategy for the operations. It is attractive if the excess kinetic energy could be controlled through the adjustment of the fuel control valve. The MPC is designed for this purpose. In this work, the MPC is used to prevent the transient instability in power distribution system with DG. The unbundling of the electricity sector and the force of competition have developed new technologies of the generation and the delivery of electricity which mean less pollutant, higher efficiency, and less costly means of supplying the load. These technologies often apply to conventional (coal, oil, gas, hydro, nuclear) and unconventional (solar, wind, fuel cells, microturbines) sources of energy. The possible alternative of replacing coal and oil burning plants with natural gas plants could greatly meliorate the sustainability of forests, waters, and farmlands, which are negatively affected by acid deposition. Natural gas is produced primarily at remote sites and transmission pipelines, distribution pipelines, vast underground storage facilities, and compressors are fabricated to deliver the natural gas from wellheads to power generating sites and end users. Despite the strong worldwide growth in demand for natural gas, the reserves continue to rise, thanks to the improvements in gas exploration technologies. The exploitable proven reserves are of around 150 tera cubic meters (Tm3), with a residual life, at present consumption rate, of around 65 years; considering another 200 Tm3 of potential discoveries, gas has a future potential nearly twice that of oil. The electricity generation field is the leading market for gas. This extraordinary growth in the electricity sector is driven by various factors (DOE, 2001 a; DOE, 2001 b): (1) Of all forms of energy consumption, electricity is becoming the most important for final consumers, with an ever increasing penetration rate: today around 37% total. (2) The new technologies for combined cycle gas turbines plants allow a very high efficiency (close to 60%), low emissions and environmental impact, very attractive investment costs and short completion times. (3) The ever increasing environmental concerns for power plant emissions and the explosion of Independent Power Producers in a deregulated market that is quickly changing the rules of the game. A great number of pipeline systems are under study and for the medium/long term very long and high capacity pipelines are being considered (e.g. Yamal - Europe and Turkmenistan- Europe), analyzing also new technology solutions (high pressure pipelines) to reduce the gas transmission costs. This paper compares power losses between gas and electricity distribution systems, of interest when natural gas is needed for electricity generation. The article is organized as follows. In Section 2, general principles of gas turbines are explained. In Section 3, the Hammestein model is introduced. The MPC is formulated in Section 4. Section 5 presents a review of the components of gas system. Some basic concepts of the gas steady-state equations are presented in Section 6. Section 7 describes electric power losses. Section 8 depicts some simulation results and discussion. Finally, conclusions are presented in Section 9.
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2. GAS TURBINE MODEL The plant model is a physics based component level model (CLM) of this gas turbine configuration. This model is very detailed, high-fidelity, and models each component. A thorough introduction to the gas turbine theory is provided in (Cohen et al., 1998). There exist a large number of publications on the modeling of gas turbines. The model complexity varies according to the intended application. A detailed first principle modeling based upon fundamental mass, momentum and energy balances is reported in (Fawke et al., 1972). These models describe the spatially distributed nature of the gas flow dynamics by dividing the gas turbine into a number of sections. Throughout each section, the thermodynamic state is assumed to be constant with respect to location, but varying with respect to time. Mathematically, the full partial differential equation model is reduced to a set of ordinary differential equations, which are facilitated easily within a computer simulation program. For a detailed model, a section might consist of a single compressor or turbine stage. Much simpler models result if the gas turbine is decomposed into just three sections corresponding to the main turbine components, i.e. compressor, combustor and turbine, as in (Hussain and Seifi, 1992). Instead of applying the fundamental conservation equations, as described above, another modeling approach is to characterize the gas turbine performance by utilizing the real steady state engine performance data, as in (Hung, 1991). It is assumed that transient thermodynamic and flow processes are characterized by a continuous progression along the steady state performance curves, which is known as the quasi-static assumption. The dynamics of the gas turbine, e.g. combustion delay, motor inertia, fuel pump lag etc. are then represented as lumped quantities separate from the steady-state performance curves. Very simple models result if it is further assumed that the gas turbine is operated at all times close to the rated speed (Rowen, 1983). This model was utilized in a simulation of an island grid (Sharma, 1998). System simulation based on dynamic coupling equations is widely assumed and introduced (Schobeiri et al., 1994; and Garrard, 1996) with respect to aero engines and (Botros et al., 1991; Botros, 1994) with regard to compressor stations. For control purposes, fast simulation is demanded and the model configuration is kept as simple as possible. Air at the atmospheric pressure enters the gas turbine at the compressor inlet. After compression of the air to achieve the most favorable conditions for combustion, the fuel gas is mixed with the air in the combustion chamber. Then, the combustion takes place and the hot exhaust gases are expanded through the turbine to produce the mechanical power. In terms of energy conversion, the chemical energy present in the combustion reactants is transferred to the gas stream during combustion. This energy - measured in terms of gas enthalpy- is then converted into the mechanical work by expanding the gas through the turbine. Thus the excess mechanical power available for application elsewhere, after accounting for the power required to drive the compressor, is derived ultimately from the combustion process. Without combustion, assuming 100 percent efficient compressor and turbine operation, the power developed by the turbine would be exactly matched by the power required to drive the compressor. The main modeling assumptions are as follows:
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(1) air and combustion products are treated as perfect gases (2) specific heats are assumed constant for combustion products, air and injected steam (3) flow through nozzles is described by a one dimensional adiabatic uniform polytropic process (4) energy storage and transport delay in the compressor, turbine and combustion chamber are relatively small, thus steady state equations are applied. (5) inlet kinetic energy of gas flows into the compressor and turbine are treated as negligible (6) air mass flow through the compressor is controllable via inlet guide vanes. The compressor is described by one dimensional steady flow nozzle equation for a uniform polytropic compression. This can be expressed as (Jurado and Cano, 2004): 1/2 ma +1 ⎞ ⎤ ⎡ ⎛ ⎞ 2ma 2/ ma m ⎟⎥ ⎢⎛ wa = Ao ⎢⎜ − rc a ⎟ ⎥ ρ p ⎜r ⎜ η ( m − 1) ⎟⎟ i cin ⎜ c ⎜ ⎟⎥ ⎠ ⎢⎣⎝ ∞c a ⎝ ⎠⎦
(1)
Compressor power consumption equation is given by
Pc =
wa Δ hIC
(2)
ηcηtrans
Combustion energy equation is expressed as
w g c pg (TTin − 298 ) + w f Δ h25 + wa c pa (298 − Tcout ) +
(3)
+ wis c ps (298 − Tis ) = 0
Power delivery equation is written as
PT = ηT wg ΔhIT
(4)
Pm = PT − Pc
(5)
Figure 1 shows the block diagram of the gas turbine. The concept of the gas turbine control system, which is applied in this paper, is based on the Speedtronic Mark 4 description as presented in (Rowen, 1988). The fuel flow out from the fuel systems results from the inertia of the fuel system actuator and of the valve positioner. The fuel system actuator equation is:
wf =
kf e τ f s +1 1
(6)
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Francisco Jurado
The valve positioner equation is:
e1 =
a Fd bs + c
(7)
The turbine torque function is given by:
T = k LHV ( w f − 0.23 ) + 0.5( Δω )
(8)
where the input variable to the fuel system is Fd. The output variable from the fuel system model is wf . A single gas turbine does not require the digital setpoint feature. The kLHV factor depends on the LHV. The kLHV and 0.23 factors cater for the typical turbine power/fuel rate characteristic, which rises linearly from zero power at 23 % fuel rate to rated output at 100 % fuel rate.
Figure 1. Block diagram of gas turbine control model.
Equation (8) allows the turbine torque to be calculated algebraically. This torque is used in the equations which model the mechanical system:
Pm = TN
(9)
In this paper, input variable to the turbine is wf and output variable from the turbine is N.
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3. HAMMERSTEIN MODEL Since MPC is a model-based control an internal model is needed to predict the future responses of the plant to control inputs. As the CLM is a very large and complicated model, a new model is developed to be used in the MPC. Following the model structure proposed in (Jurado, 2005), a Hammerstein model of a gas turbine is applied that meets the above specifications. The model is designed to replicate both transient and steady state performance. Consider the Hammerstein model shown in Figure 2, where u(t), v(t), y(t) and yf(t), are the system input, noise, output and filtered output, respectively. x(t) denotes the unavailable internal signal. These are continuous time signals. u(iTs) and yf(iTs) denote the sampled input and sampled filtered output signals respectively with the sampling interval Ts. The filter is a lowpass filter at the designer’s disposal.
Figure 2. Hammerstein model.
The goal of the frequency domain identification is to apply inputs of the form,
u ( t ) = A cos (ωk t ) ,
ωk ≠ 0,
t ∈ [ 0, T ]
(10)
and then, to determine a pair of the estimates fˆ (.) and Gˆ ( s ) based on the finite sampled inputs and filtered outputs u(iTs) and yf (iTs) so that
fˆ (.) → f ( .) ,
Gˆ ( s ) → G ( s )
(11)
in some sense. Note that the continuous time model Gˆ ( s ) , not its discretized model, is our interest.
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4. MODEL PREDICTIVE CONTROL
4.1. Theoretical Background Model Predictive Control (MPC) refers to a class of control algorithms in which a dynamic process model is used to predict and optimize system performance. MPC is rather a methodology than a single technique. The methodology of controllers belonging to the MPC family is characterized by the following strategy illustrated in Figure 3.
Figure 3. Strategy of model predictive controller.
As shown in Figure 3, in MPC, the future outputs (gas turbine speed) for a determined prediction horizon Hp are predicted at each instant k using a prediction model. These predicted outputs yˆ ( k + j ) , j = 1,..., H p depend on the state of the model at the current time k (given, for instance, by the past inputs and outputs) and on the future control signals
u (k + j) .
The control signal (mass flow) change only inside the control horizon, Hc, remaining constant afterwards,
u ( k + j ) = u ( k + H c − 1) , j = H c ,..., H p
(12)
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The set of control signals is calculated by optimizing a cost function in order to keep the process as close as possible to the reference trajectory (gas turbine speed reference), ω ( k + j ) , j = 1,..., Hp. This criterion usually requires a quadratic function of the errors between the predicted output signal and the reference trajectory. The control effort is included in the objective function in most cases. An explicit solution can be obtained if the criterion is quadratic, the model is linear and there are no constraints. Otherwise an iterative optimization method has to be used. In practice all systems are subject to restrictions. The actuators have a limited field of action, as in the case of valves. Constructive reasons, safety or environmental ones can cause limits in the system variables such as fuel flow or maximum temperatures and pressures. All of them lead to the introduction of constraints in the MPC problem. Usually, input constraints like
umin ≤ u ( k + j ) ≤ umax , j = 1,..., Hc
(13)
Δumin ≤ Δu ( k + j ) ≤ Δumax , j = 1,..., Hc − 1
(14)
are hard constraints in the sense that they must be satisfied. Conversely, output constraints can be viewed as soft constraints because their violation may be necessary to obtain a feasible optimization problem:
ymin ≤ y ( k + j ) ≤ ymax , j = j1 ,..., H p
(15)
where j1 represents the lower limit for output constraint enforcement.
4.2. Linear Model Based Predictive Control The basic idea is to use the linear model to predict the future system behavior. This model is used throughout the entire prediction horizon. Even if this model is very accurate at the linearization point, its accuracy decreases over the prediction horizon. As a consequence, there may be a significant prediction error at k + H p .
4.3. Hammerstein Model Based Predictive Control Due to the relatively simple block-oriented structure, the application of Hammerstein models in MPC is more straightforward than the application of the general Nonlinear AutoRegressive Exogenous (NARX) or NARMAX models. In this section, the Hammerstein model is implemented in MPC by inverting the static nonlinear model element f(u), as indicated in Figure 2. As the remaining part of the prediction model is the linear dynamic part of the Hammerstein model, the MPC optimization can be solved by quadratic programming.
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The combination of the inverse static nonlinear model element and the nonlinear system results in a transformed dynamical system. This system is linear if the system is of the Hammerstein type. As the inversion of the single-input single-output and multiple-input single-output static nonlinear model element is a straightforward analytical procedure, the computational demand of the controller is quite comparable to the linear generalized predictive control (GPC). This is a significant advantage compared to other nonlinear models which require the use of nonlinear programming or linearization techniques. In order to cope with the model-plant mismatch and also with disturbances (load changes), the internal model control (IMC) scheme (Garcia and Morari, 1982) is used. The resulting scheme is depicted in Figure 4.
Figure 4. Hammerstein model based predictive control scheme.
4.4. Optimization
{
}
In general, the GPC algorithm computes the control sequence Δu ( k + j ) , j = 1,..., Hc , such that the following quadratic cost function is minimized:
J ( H p1 , H p 2 , H c , λ ) =
Hp2
∑ (ω ( k + j ) − yˆ ( k + j ) )
j = H p1
2
Hc
+λ ∑ Δu 2 ( k + j − 1) j =1
(16)
Here, yˆ ( k + j ) denotes the predicted system output, ω ( k + j ) the modified setpoint that is assumed to be known in advance, H p1 is the minimum costing horizon, H p 2 is the maximum costing or prediction horizon, H c is the control horizon, and suppression coefficient.
λ
is the move
Gas Turbines and Electric Distribution System
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5. COMPONENTS OF GAS SYSTEM Delivering the natural gas from a gas wellhead to end customers is comprised by a tremendous segment of the gas industry, which implicates gas wells, transmission and distribution pipelines, underground storages, compressors, and valves (Tobin, 2001; California Energy Comm., 2001). Gas Well: A gas well is usually located at sites which are far from load centers. Gas wells can be sorted into offshore and onshore. Transmission Pipelines: Transmission pipelines tackle the duty of transporting natural gas from wellheads or producers to local distribution companies or directly to large commercial and industrial users. Distribution Pipelines: Distribution pipelines generally allow the final link in the natural gas delivery chain. Distribution pipelines, which constitute the largest section in the natural gas system, deliver natural gas from city gate stations, underground storage facilities, and other gas supply sources to local industrial, as well as commercial and residential, customers. These pipelines work at a lower pressure level than transmission pipelines and offer different pressure services for different customers by adjusting the associated pressure regulators. for example, pipelines connected to gas-burning power plants require high-pressure services. Nevertheless, residential customers would need low-pressure gas for appliances. Underground Storage: Unlike electric power systems, which must uninterrupted monitor the entire system and adapt to changes instantaneously as electricity demand fluctuates, the gas industry can inject gas into certain underground storage facilities during off-peak periods for mitigating the high demand during peak hours and maintaining a steady flow through other pipelines when contingencies occur. Compressor: A compressor operates similar to step-up transformers in electric power systems. As gas is carried through a pipeline, its pressure would drop. Thus, the compressor must be an essential component in natural gas systems to maintain the desired pressure level in the transmission and distribution pipelines. Other compressors can be installed along pipelines (ordinarily at 50–100-mi intervals). The optimized location of compressors in pipeline planning could diminish the operation cost dramatically, improve the market competition, and assure a reliable gas supply to customers. Valve: A valve is a protective device which serves similar to breakers, fuses, and switches in electric power systems. It can insulate faulted sections and maintain the operation of other components in natural gas systems by holding a desired pressure level.
6. GAS STEADY-STATE EQUATIONS The steady-state flow of gas in a pipeline may be represented by equations that vary according to the gas working pressure and friction. These factors influence the gas flows that can vary from small values, in low-pressure distribution systems, to vary 1arge values, in high-pressure transportation systems. The effects of friction are difficult to measure and are the main reason for variations in the flow equations. The friction factor is not a constant for a given section of a pipeline and it is dependent on the roughness of the internal pipe surface, gas velocity, gas density, gas viscosity and the internal diameter of the pipe.
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After defining the gas operating conditions, the problem of static simulation is to estimate the values of pressure at the nodes and the flows in the individual pipes for known values of sources pressures and of gas consumption in the nodes. The pressures at the nodes and the flow in the pipes first satisfy the flow equation, and together with the values of loads and values of sources must accomplish the similar Kirchhoff’s laws for the electrical systems. The above general flow equation implies assumptions which are: 1. 2. 3. 4.
Isothermal flow due to insignificant temperature changes. Negligible kinetic energy change and constant compressibility across the pipe. Validity of the Darcy friction loss relationship across the pipe. Constant friction coefficient along the pipe length.
Under normal conditions, either an isothermal or an adiabatic approach is assumed. For the case of slow transients caused by fluctuations in demand, it is adopted that the gas in the pipe has sufficient time to reach thermal equilibrium with its constant-temperature environment. Likewise, when rapid transients were under consideration, it was assumed that the pressure changes occurred without any delay, allowing no time for heat transfer to take place between the gas in the pipe and the surroundings. Sometimes, this supposition of a process having a constant temperature or is adiabatic is not valid. The Darcy–Weisbach equation for the friction loss in pipes yields better precision than other equations such as Hazen–Williams because the friction factor it involves is determined as a function of both the relative pipe wall roughness and the Reynolds number. The others, like Hazen–Williams, Manning, and Scobey assume that the flow is in the rough pipe zone and neglect the effect of Reynolds number. Many methods of meshed gas flow simulation may be used, such as, the Newton-nodal method, Hard-Cross nodal method, Newton-loop method and Hard-Cross loop method. The Newton-loop method has a respectable convergence compared with the other ones (Gay, 1971; Gay and Preece, 1975; Cochran, 1996). Three basic types of entities are considered for the modeling of natural gas transmission network: pipelines, compressor stations, both of which are symbolized by branches, and interconnection points, represented by nodes (Osiadacz, 1989; Wong and Larson, 1968; Olorunntwo, 1981; Wu et al., 2000; Carter, 2001).
6.1. Flow Equation For isothermal gas flow in a long horizontal pipeline, say number k, which begins at node i and ends at node j, the general steady-state flow rate is often expressed by the following formula (Osiadacz, 1989) derived from energy balance:
T f k = f kij = Sij × 6.18* 10 0 π0 −6
Sij
(π
2 i
)
- π 2j Dk5
Fk GLk Tka Z a
(17)
Gas Turbines and Electric Distribution System
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where
⎪⎧+1 if πi - π j > 0 ⎨ ⎪⎩ -1 if πi - π j < 0
Sij
In equation (1), the friction factor Fk depends on the flow region (laminar flow, mixed or transition flow, or fully turbulent flow), For fully turbulent flow (Reynolds number» 4000) region in a high-pressure network, Weymouth suggested that the friction factor Fk varies as a function of the diameter Dk ( Weymouth, 1942)
Fk =
0.1089
(18)
1
Dk 3
In terms of field units, equation (17) becomes
(
f k = f kij = 8.41* 10 −7 Sij M k Sij πi2 - π 2j
)
(19)
where 8
Mk = ε
1.22* 10 −10 T0 Dk 3 π0 GLk Tka Z a
As suggested in equation (19), the gas flow can be found once πi and π j are known for given conditions. Equation (19), known as Weymouth flow equation, is most acceptable for large diameter ( ≥ 0.254 m) lines with high pressures.
6.2. Compressor Modeling During transportation of gas in pipelines, the gas flow loses a part of its initial energy due to frictional resistance which results in a loss of pressure. To compensate the loss of energy and to move the gas, compressor stations are established in the network. The key factor to establish the representation of the centrifugal compressor is the horsepower consumption, which is a function of the amount of gas that flows through the compressor and the pressure ratio between the suction and the discharge. After empirical adjustment to describe for deviation from ideal gas behavior, the actual adiabatic compressor horsepower equation (Olorunntwo, 1981) at T0 = 15.5 °C (= 288.65 K) and π0 = 101.00819 kPa becomes
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H k = H kij
⎛ α −1 ⎞ ⎡ Z ki ⎜ ⎤ α ⎟ ⎢⎛ π jc ⎞ ⎝ ⎠ ⎥ = 0.0155Bk f k ⎢⎜ − 1⎥ ⎜ π ⎟⎟ ⎢⎣⎝ ic ⎠ ⎥⎦
(20)
where
Bk =
1972.47Tki ⎛ α ⎞ ⎜ ⎟ ηk ⎝ α −1 ⎠
6.3. Conservation of Flow The mass-flow balance equation at each node can be expressed in a matrix form as
( A+U ) f
+ w − Tτ = 0
(21)
where if branch k enters node i, ⎧+1, ⎪ Aik = ⎨ -1, if branch k leaves node i, ⎪ 0, if branch k is not connected to node i. ⎩ ⎧ +1, if the kth compressor has its outlet at node i, ⎪ U ik = ⎨ -1, if the kth compressor has its inlet at node i, ⎪ 0, otherwise. ⎩ ⎧+1, if the kth turbine gets gas from node i, Tik = ⎨ 0, otherwise. ⎩
The matrix A, known as the branch-nodal incidence matrix (Osiadacz, 1989), corresponds the interconnection of pipelines and nodes. In addition, it is defined the matrix U, which describes the connection of compressors and nodes. The vector of gas injections w is found by (22)
w = wS − wL
Thus, a negative gas injection means that gas is taken out of the network. The matrix T and the vector τ represent where gas is withdrawn to power a gas turbine to operate the compressor. Therefore if a gas compressor, say k, between nodes i and j, is driven by a gasfired turbine, and the gas is tapped from the suction pipeline i, the following representation is obtained:
Tik = +1,
T jk = 0,
and τ k = amount tapped
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Conversely, if the gas were tapped at the compressor outlet, it would have Tik = 0,
T jk = +1,
and τ k = amount tapped
Analytically, τ k can be approximated as
τ k = αTk + βTk H kij + γ Tk H kij2
(23)
where H k = H kij is the horsepower demanded for the gas compressor k in equation (20).
6.4. Power Losses During transportation of gas in pipelines, the gas stream loses a part of its initial energy due to frictional resistance which results in a loss of pressure. The losses of gas distribution system can be indicated as
∑
NP k=1
(
f k πi - π j
)
(24)
where
N P branches in the system.
7. ELECTRIC POWER LOSSES Differences between natural gas and electricity systems are established as follows. • •
•
•
Electricity displaces at the speed of light, while natural gas travels 40–60 mi/h. Electricity is not a storable article of commerce. So the contingency-constrained network flow operation could forbid transmission systems from employing their maximum capacity. Consequently, the value of a transmission line may not necessarily be reflected in its current flow. The possibility to store gas in tanks and in pipelines palliates this problem for gas. Natural gas utilities typically trust on the natural gas storage to increase supplies flowing through the pipeline system and to meet the total natural gas demand. Economies of scale are very great in electric power transmission projects. It is much cheaper to install the required capacity of a transmission line initially than to retrofit the line later. However, gas pipelines are normally operated at a lower pressure and the pressure is elevated later to obtain additional capacity. Natural gas pipeline flows can be operated independent of the gas network constituents.
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Electric power systems may suffer significant losses. The losses depend on the line resistance and currents and are usually referred to as thermal losses. While the line resistances are fixed, the currents are a complex function of the system topology and the location of generation and load. Consider the well known power flow equations, with complex power Si = Pi + jQi , injected at bus i as (Grainger and Stevenson, 1994)
Pi = Vi ∑ j =1 YijV j cos (δ i − δ j − γ ij )
(25)
Qi = Vi ∑ j =1 YijV j sin (δ i − δ j − γ ij )
(26)
n
n
In this article, only the real power injections as they relate to electric losses are of concern. The system losses can be expressed as (27)
PL = ∑ i =1 PGi −∑ i =1 PDi n
n
8. RESULTS 8.1. Identification of the Gas Turbine Model A second-order term is sufficient to model the static nonlinear behavior of the engine and the linear part is a second order transfer function. The noise v(t) is a random signal uniformly distributed and the input is
u ( t ) = A cos (ωi t ) ,
A = 1,
i = 1, 2,3
with ω1= 0.6, ω2=1.2, ω3=6 and Ti= 100((2π)/ωi). For the input frequency ωi, the sampling interval is set to be π/(50ωi). No lowpass filter is used in simulations, i.e., y(t) = yf(t). Thus, the estimates of fˆ ( .) and Gˆ ( s ) are given by
f ( u ) = 0.002u 2 + 0.816u + 3.458
G (s) =
0.066 ( s + 0.428 ) s + ( 0.932 )( s + 0.429 )
which are very close to the true but unknown f ( u ) and G ( s ) . The true (solid line) and the estimated (circle) nonlinearities are shown in Figure 5. They are basically indistinguishable.
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Figure 5. True (solid) and the estimated (circle) nonlinearities.
8.2. Model Based Predictive Control The gas turbine-generator is natural gas operated, with the rating of 1 MW. The systems are modeled dynamically (MATLAB®, 2007). The nominal operating conditions of the gas turbine and generator considered in this paper are given in Table 1 (Brown Energy Systems, 2007). Permanent magnet generator provides rapid response to varying loads and constant excitation under all conditions. The gearbox is created to ensure optimal performance. The control system displayed in Fig. 4 is applied to enable the control of speed of the gas turbine. A future control trajectory is generated as a possible solution by the optimizer based on the Hammerstein model using proposed method. At each sampling instant, only the first predicted input signal from the obtained control trajectory is applied to control the gas turbine. The load is the major disturbance affecting the gas turbine. The amount of mass flow can be controlled according to the load. Hammerstein MPC is employed to illustrate the performance of the gas turbine. The MATLAB implementation of quadratic programming is used (Coleman and Branch, 2004). The MPC parameters are selected according to the tuning rules given in (Soeterboek, 1992). Minimum prediction horizon H p1 is always set to the model time-delay d. There is no reason for choosing it smaller because the d-1 first predictions depend on past control inputs only and cannot be affected by the first action u(t). From another point of view, it is not recommended to select it bigger because this can lead to unpredictable results. For the gas turbine, it is set to l (sampling period) and not tuned. A rule of thumb is that the prediction horizon H p 2 should be taken close to the rise time of system (Clarke et al., 1987). Nevertheless, often it is not possible to choose it this long since the calculation time required by MPC is too demanding. Commonly it is tuned through empirical observation.
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Francisco Jurado Table 1. Operating point data
Power output Efficiency (LHV) Fuel Mass flow Turbine speed Exhaust temperature Permanent magnet generator Type Rated Capacity (kVA) Rated Capacity (kW) Speed Voltage Current Gearbox
GAS TURBINE 1000 kW 25 % Natural gas 0.07 kg/s 100 r/s 950 F Synchronous, brushless 1500 kVA, 3 phase 1200 kW, PF 0.8 30 r/s 480/460 V 1806/1884 A 100 r/s -30 r/s
From repeated tests on the gas turbine, H p 2 is set around 30 (sampling periods) for the best control performance for both small and large random step changes. The sample time is limited to 0.1 s. Soeterboek advises H c is equal to the number of output lag terms (Soeterboek, 1992). If
H c is made longer, the control performance is slightly ameliorated and the calculating time is also increased. Based to the simulation results, it is set to 2 (sampling periods), which is the same as the number of output lag terms. The purpose of the move suppression coefficient λ is to punish large changes in the process input and reduce actuator wear. It is usual to set λ as a constant in the range [0, 1]. For the gas turbine, to achieve the best control performance, it is set to 0.05. With the MPC variables set to H p1 =1, H p 2 =30, H c =2 and λ =0.05, the controller results in the system responses are shown in Figures 6 and 7. The responses are for large random step changes. The results depict that a fast rise rime is attained, with almost no overshoot, evidencing proposed method offers a near optimal performance for both small and large random step changes. This result illustrates the capabilities of the MPC controller to track a reference trajectory.
8.3. Simulation Results The IEEE 13 node test feeder (Kersting, 2001) is a 4.16 kV short and highly loaded feeder. Also, its overhead and underground lines, shunt capacitor banks and spot and distributed loads provide a useful distribution system model.
Gas Turbines and Electric Distribution System
Figure 6. Performance of MPC on several large random set point changes. Comparison between rotational speed and speed reference.
Figure 7. Performance of MPC on several large random set point changes. Mass flow for set point changes.
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Francisco Jurado
This node test feeder is used as the test system to investigate the dynamic characteristics of the distribution system with two gas turbines and the effectiveness of the MPC on the stability of distribution system. Figure 8 shows this test system.
Figure 8. One line diagram of IEEE 13 node feeder with gas turbines.
Figure 9. Rotor speed deviation of GT1.
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The two gas turbines are connected at nodes 652 and 634, the initial active power of gas turbine GT1 is 1 p.u., and initial active power of gas turbine GT2 is 0.5 p.u. To investigate the dynamic behavior of the gas turbines under large disturbance conditions, a three-phase fault is applied on node 671 for 400 ms. At t = 0 s, the fault occurs at node 671 and the fault is cleared at t= 0.4 s. Figures 9 and 10 show the responses of rotor speed of the gas turbines to the three-phase fault when the MPC is applied in the governor-gas turbine system. GT1 has a greater oscillation than that of the GT2. This is because the initial power of GT1 is higher than that of GT2. The simulation results demonstrate that MPC can effectively damp the oscillation of both gas turbines, thus the MPC can ameliorate the dynamic characteristic of the whole distribution system.
Figure 10. Rotor speed deviation of GT2.
8.4. Distribution Systems A series of comparisons between gas and electricity systems has been performed. It is of no use to consider a generic possible substitution of gas pipelines with electric lines: pipelines are clearly the basic solution for multipurpose gas utilization (electricity generation, industrial and domestic uses, petrochemicals, etc.), particularly when very large gas flow rates are involved. The same reliability/availability assumptions for the delivered electricity have been taken into account for both gas and electricity systems. This hypothesis is secure on the basis of the actual performance of both gas and electricity systems.
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The IEEE 37-bus test system shown in Figure 11, which can be considered as a distribution system, is applied to verify the method presented. A gas turbine is integrated into electric distribution network. While a gas well is incorporates into the gas distribution system. The electric power losses are obtained from the results of power flow studies using MATLAB®. Figure 12 shows the electric power losses. In Figure 13 the power losses are reported as a function of the node (bus) and pipeline in the gas distribution system. The simulations have been developed by NEPLAN®. The total power loss of the electricity distribution system reaches 34 kW, while the total power loss of the gas distribution system is only 2.131 kW. Lengths of electric lines and equivalent gas pipelines are reported in Table 2.
Figure 11. IEEE 37- bus test system.
16000 14000 12000 10000 8000 6000 4000 2000 0 L1-2 L2-3 L3-4 L4-5 L5-6 L6-7 L7-8 L8-9 L9-10 L10-11 L11-12 L12-13 L12-26 L9-25 L25-35 L25-36 L7-24 L6-23 L6-22 L3-14 L14-15 L15-16 L16-33 L33-34 L16-30 L30-32 L15-28 L28-29 L30-31 L3-17 L17-18 L17-27 L4-19 L19-20 L20-21 L20-37
Power loss (W)
IEEE-37 Bus
Line
Figure 12. Power losses of the IEEE 37-bus test system. Electricity distribution system.
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IEEE-37 Bus
Power loss (W)
300 250 200 150 100 50 0 1
3
5
7
9
11 13 15 17 19 21 23 25 27 29 31 33 35 37 Location-Bus Nº
Power loss (W)
IEEE- 37 Bus 800 600 400 200 0
Pipeline
Figure 13. Power losses of the IEEE 37-bus test system. Gas distribution system.
Table 2. Lengths of electric lines and gas pipelines. IEEE 37-bus test system Pipeline L-1-2 L-2-3 L-3-4 L-4-5 L-5-6 L-6-7 L-7-8 L-8-9 L-9-10 L-10-11 L-11-12 L-12-13 L-12-26 L-9-25 L-25-35 L-25-36 L-7-24 L-6-23 L-6-22 L-3-14
Length (m) 643,8 334 459 208 69,6 111,3 111,3 195 222,7 139 139 139,2 69,6 181 69,6 445 111,3 0,001 208 125
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Francisco Jurado Table 2. (Continued)
Pipeline L-14-15 L-15-16 L-16-33 L-33-34 L-16-30 L-30-32 L-15-28 L-28-29 L-30-31 L-3-17 L-17-18 L-17-27 L-4-19 L-19-20 L-20-21 L-20-37
Length (m) 181 27,8 208,8 97,4 320,1 41,7 27,8 180,9 264,5 139 111,3 83,5 83,5 97,4 97,4 69,6
Figure 14 shows the next system studied. It represents a six-bus 25 kV distribution network with lines ranging in length from 16 to 32 km. Node 1 is the reference bus. It is assumed that nodes 1 and 2 are connected to gas turbines. They are voltage controlled buses.
Figure 14. IEEE 6- bus test system.
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Figure 15 displays the electric power loss and Figure 16 the power loss in the gas distribution system. The total power loss of the electricity system extends to 495 kW, whereas the total power loss of the gas system reaches 126.6 kW. Lengths of electric lines and equivalent gas pipelines are described in Table 3. The computation of losses is illustrated by means of Tables 4 and 5. IEEE-6 Bus
Power loss (kW)
200 150 100 50
L1-6
L1-5
L3-4
L4-5
L5-6
L2-1
L2-3
0
Line
Figure 15. Power losses of the IEEE 6-bus test system. Electricity distribution system.
IEEE- 6 Bus
Power-Loss (kW)
100 80 60 40 20 0 3
2
1
6
5
4
Location-Bus Nº
IEEE-6 Bus
Power loss (kW)
50 40 30 20 10
Pipeline
Figure 16. Power losses of the IEEE 6-bus test system. Gas distribution system.
L-1-6
L-1-5
L-3-4
L-4-5
L-5-6
L-1-2
L-2-3
0
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Francisco Jurado Table 3. Lengths of electric lines and gas pipelines. IEEE 6-bus test system Pipeline L-1-2 L-2-3 L-3-4 L-4-5 L-5-6 L-1-6 L-1-5
Length (km) 16 16 16 16 16 17,6 32
Table 4. Lengths of electric lines and gas pipelines. IEEE 30-bus test system Pipeline L1-2 L1-3 L2-4 L2-6 L2-5 L4-6 L3-4 L5-7 L8-28 L6-28 L6-8 L7-6 L12-14 L12-15 L12-16 L14-15 L16-17 L15-18 L18-19 L19-20 L10-20 L10-17 L10-21 L10-22 L21-22 L15-23 L23-24 L22-24 L24-25 L25-27 L27-29 L27-30 L29-30 L25-26 L6-9 L6-10 L4-12 L27-28 L9-10
Length (km) 71,5 91,9 132,8 204,3 204,3 102,2 51,2 26,6 204,3 204,3 106,2 30,6 61,3 34,7 28,6 34,7 53,1 32,7 36,8 16,3 53,1 38,8 46,9 40,8 18,4 40,9 51,1 47,0 20,4 30,6 30,6 61,3 57,2 51,1 0 0 0 0 0
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Table 5. Computation of losses. Electricity distribution system L1-2 L1-6 L1-5 L2-1 L2-3 L3-2 L3-4 L4-3 L4-5 L5-4 L5-6 L5-1 L6-5 L6-1 Losses (kW)
Line flow (kW) 15 8.140 5.620 -15 7.913 -7.760 3.754 -3.718 -3.518 3.550 -2.988 -5.524 3.009 -7.983 495
The power losses depend on the ambient temperature as formulated in Sections 6 and 7. Figure 17 displays the power losses for different temperatures in this gas distribution system.
Figure 17. Power losses for different temperatures. Gas distribution system.
8.5. Subtransmission System The proposed method is tested on the IEEE 30-bus test system shown in Figure 18, which can be considered as a meshed subtransmission system. The system has 30 buses (mainly 132- and 33-kV buses) and 41 lines. Six gas turbines are considered to be connected to the system.
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Francisco Jurado
Figure 18. IEEE 30- bus test system.
Gas compressors stations constitute a major part of the operational plant on each transmission system. Their purpose is to restore the gas pressure reduction induced by frictional pressure losses. The compressors are driven mostly by gas turbines which use natural gas as fuel, taken directly from the transmission pipelines. The compressor unit comprises three main components, a gas generator, a power turbine and a centrifugal gas compressor. The maximum shaft powers of the units range from 5.5 MW to more than 20 MW. At each compressor station, there are installed between two and three centrifugal compressors, driven by gas turbines. In this paper, the compressors are installed at 60 mi intervals. Figure 19 displays the electric power loss and Figure 20 the power loss in the gas distribution system. The total power loss of the electricity system corresponds to 17.86 MW, however the total power loss of the gas system represents 202.34 MW. Lengths of electric lines and equivalent gas pipelines are depicted in Table 6.
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6 5 4 3 2 1 0 L1-2 L5-7 L7-6 L6-8 L27-28 L27-29 L29-30 L27-30 L27-25 L25-26 L1-3 L3-4 L4-6 L4-12 L14-15 L12-14 L16-17 L12-16 L24-22 L23-24 L15-23 L21-22 L10-21 L22-10 L20-10 L19-20 L6-10 L2-4 L12-13 L9-10 L9-11 L6-9 L18-19 L15-18 L12-15 L24-25 L17-10 L2-6 L2-5 L8-28 L6-28
Power loss (MW)
IEEE-30 Bus
Line
Figure 19. Power losses of the IEEE 30-bus test system. Electricity distribution system.
50 0
Power loss (MW)
100
IEEE-30 Bus
1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
Location-Bus Nº IEEE-30 Bus
Pip eline
Figure 20. Power losses of the IEEE 30-bus test system. Gas distribution system.
It is quite clear that in distribution systems, due to better efficiency of gas system, the losses are larger in case of electricity system. For the shortest lengths here considered (IEEE 37-bus test system) the losses are the lowest ones. For the longest lengths (IEEE 30-bus test system), the losses are larger in case of gas system. Also for the shorter distances the gas pipeline feeding a local power plant in the consumption area is an interesting and attractive option to be considered with respect to a distribution of electricity.
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Francisco Jurado Table 6. Computation of losses. Gas distribution system
N-1 N-2 N-3 N-4 N-5 N-6
fk (m3/s) 0 0 0.345 0.625 0.431 0.431
Δπ (mbar) 0 0 653.62 2255.12 724.23 3.7705
Losses (kW) 0 0 13.529934 84.6421707 18.7454865 9.75931083 126.676902
CONCLUSIONS In this article, a Hammerstein model of a gas turbine plant and its MPC has been presented. The model is suitable for use in power system stability studies. A MPC is designed for the gas turbine in order to improve system dynamic performance. The proposed model was tested on a simple distribution system. The simulation results with and without MPC are compared. It was observed that the proposed model with MPC improves the dynamic performance of the system. Due to the continuous developments of gas turbines, combined cycle power plants allow a very high efficiency, low emissions and very attractive investments cost. This and environmental concerns are enhancing gas consumption for electric power generation. The performed comparison between gas and electricity systems, of interest when natural gas is needed for electricity generation, highlights that in the investigated cases the power losses are larger in case of electricity transmission over short distances than in case of gas transport and electricity generation close to final users. However for longer distances the use of electric transmission systems is an attractive option to a gas pipeline feeding a power plant located into the consumption area.
REFERENCES Botros K.K., Campbell P.J., Mah D.B., 1991. Dynamic simulation of compressor station operation including centrifugal compressor and gas turbine. Journal of Engineering for Gas Turbines and Power-Transactions of the ASME, Vol. 113, No. 2, pp. 300–311. Botros K.K., 1994. Transient phenomena in compressor stations during surge. Journal of Engineering for Gas Turbines and Power-Transactions of the ASME, Vol. 116, No. 1, pp. 133–142. Brown Energy Systems, 2007. New 1 MW Multi-Fuel Gas Turbine Generator. Available: http://www.brownmarine.com/tg01.htm. California Energy Comm., 2001. Natural gas infrastructure issues, Sacramento, CA. Carter R., Goodreau M., Rachford H., 2001. Optimizing pipeline operations through mathematical advances. Pipeline and Gas Journal, Vol. 228, No. 10, pp. 51-53.
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Chiras N., Evans C., Rees D., 2002. Global nonlinear modeling of gas turbine dynamics using NARMAX structures. ASME Journal of Engineering and Power, Vol. 124, No. 4, pp. 817-826. Clarke D.W., Mothadi C., Tuffs P.S., 1987. Generalized predictive control. Part I. The basic algorithm, Automatica, Vol. 23, No. 2, pp. 137-148. Cochran T.W., 1996. Calculate pipeline flow of compressible fluids. Chemical Engineering, Vol. 103, No. 2, pp. 115-122. Cohen H., Rogers G.F.C., Saravanamuttoo, H.I.H., 1998. Gas turbine theory. 4th ed. Longman, England. Coleman T., Branch M.A., Grace A., 2004. Optimization Toolbox, Version 2.2. The MathWorks, Inc., Natick, MA. DOE, 2001 a. Annual energy outlook 2002 with projections to 2020. Energy Inf. Admin. (EIA). DOE, 2001 b. U.S. natural gas markets: Recent trends and prospects for the future. Energy Inf. Admin. (EIA). Evans C., Rees D., Borrell A., 2000. Identification of aircraft gas turbine dynamics using frequency-domain techniques. Control Engineering Practice, Vol. 8, No. 4, pp. 457-467. Fawke A.J., Saravanamuttoo H.I.H., Holmes M., 1972. Experimental verification of a digital computer simulation method for predicting gas turbine dynamic behaviour. Institution of Mechanical Engineers Proc. Vol. 186, No. 27, pp. 323–329. Garcia C.E., Morari M., 1982. Internal model control: 1. A unifying review and some new results. Ind. Eng. Chem. Process Design and Development, Vol. 21, No. 2, pp. 308-323. Garrard D., 1996. ATEC: The aerodynamic turbine engine code for the analysis of transient and dynamic gas turbine engine system operations, part 1: Model development. ASME paper 96-GT-193. Gay B., 1971. Middleton P. Solution of gas network problems. Chemical Engineering Science, Vol. 26, No. 1, pp. 109-123. Gay B., Preece P.E., 1975. Matrix methods for the solution of fluid network problems. Trans. of the Institution of Chemical Engineers, Vol. 53, No.1, pp. 12-15. Grainger J.J., Stevenson Jr. W.D., 1994. Power system ana1ysis. New York: McGraw-Hill, Inc. Hung W.W., 1991. Dynamic simulation of gas-turbine generating unit. IEE Proc.-C Generation Transmission and Distribution, Vol. 138, No. 4, pp. 342-350. Hussain A., Seifi H., 1992. Dynamic modeling of a single shaft gas turbine. Proc. of the IFAC Symposium on Control of Power Plants and Power Systems, Munich, Germany, Pergamon Press, pp. 43-48. Jurado F., Cano A., 2004. Use of ARX algorithms for modelling micro-turbines on the distribution feeder. IEE Proceedings Generation Transmission and Distribution, Vol. 151, No. 2, pp. 232-238. Jurado F., Carpio J., 2005. Enhancing the distribution networks stability using distributed generation. The International Journal for Computation and Mathematics in Electrical and Electronic Engineering (COMPEL), Vol. 24, No. 1, pp. 107-126. Jurado F., 2005. Modelling micro-turbines using Hammerstein models. International Journal of Energy Research, Vol. 29, No. 9, pp. 841-855. Kersting W.H., 2001. Radial distribution test feeders. Proc. IEEE/PES Summer Meeting, Vol. 2, pp. 908 –912.
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Maciejowski J.M., 2002. Predictive Control with Constraints. Prentice Hall, London. MATLAB®, 2007. Version 7. The Mathworks Inc., Natick, MA. Narendra K., Gallman P., 1996. An iterative method for the identification of nonlinear systems using a Hammerstein model. IEEE Trans. Automatic Control, Vol. 11, No. 3, pp. 546–550. NEPLAN®, 2005. Power Systems Engineering, Erlenbach, Switzerland. Olorunntwo F.O., 1981. Natural gas transmission system optimization. PhD thesis, The University of Texas at Austin. Osiadacz A.J., 1989. Simulation and Analysis of Gas Network. Houston: Gulf Publishing Company. Qin S.J., Badgwell T.A., 2000. An overview of nonlinear predictive control applications, in Allgöwer, F., and Zheng, A. (Eds.), Nonlinear Model Predictive Control. ser. Progress in Systems and Control Theory, MA: Birkhäuser, Vol. 26, pp. 369–392. Richalet J., 1993. Industrial applications of model based predictive control. Automatica, Vol. 29, No. 5, pp. 1251–1274. Rowen W.I., 1983. Simplified Mathematical Representations of Heavy-Duty Gas Turbines. ASME Journal of Engineering for Power, Vol. 105, No. 4, pp. 865-869. Rowen W.J., 1988. Speedtronic Mark IV control system. Alsthom Gas Turbine Reference Library, AGTR 880. Schobeiri M.T., Attia M., Lippke C., 1994. GETRAN: A generic, modularly structured computer code for simulation of dynamic behavior of aero- and power generation gas turbine engines. Journal of Engineering for Gas Turbines and Power-Transactions of the ASME, Vol. 116, No. 3, pp. 483–494. Sharma C., 1998. Modeling of an Island Grid. IEEE Trans. Power Systems, Vol. 13, No. 3, pp. 971-978. Soeterboek A.R.M., 1992. Predictive Control; A Unified Approach. Prentice-Hall, Upper Saddle River, NJ. Tobin J., 2001. Natural gas transportation-infrastructure issues and operational trends. Energy Inf. Admin. (EIA)/Natural Gas Div. van Essen H.A., de Lange H.C., 2001. Nonlinear model predictive control experiments on a laboratory gas turbine installation. Journal of Engineering for Gas Turbines and PowerTransactions of the ASME, Vol. 123, No. 2, pp. 347-352. Vroemen B.G., van Essen H.A., van Steenhoven A.A., Kok J.J., 1999. Nonlinear Model Predictive Control of a Laboratory Gas Turbine Installation. Journal of Engineering for Gas Turbines and Power-Transactions of the ASME, Vol. 121, No. 4, pp. 629–634. Weymouth T.R., 1942, Problems in natural gas engineering. ASME Trans., Vol. 34, pp. 185234. Willis H.L., Scott W.G., 2000. Distributed Power Generation: Planning and Evaluation. Marcel Dekker, New York. Wong P.J., Larson R.E., 1968. Optimization of natural-gas pipeline systems via dynamic programming. IEEE Trans. Automatic Control, Vol. 13, No. 5, pp. 475-481. Wu S., Rios-Mercado R.Z., Boyd E.A., Scott L.R., 2000. Model relaxations for the fuel cost minimization of steady-state gas pipeline networks. Mathematical and Computer Modelling, Vol. 31, No. 2-3, pp. 197-220.
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 1173-1197
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 36
MICRO CCHP: FUTURE RESIDENTIAL ENERGY CENTER *
R. Z. Wang and D. W. Wu Institute of Refrigeration and Cryogenics, Shanghai Jiao Tong University, China
ABSTRACT Combined cooling, heating and power (CCHP) system, as a distributed energy system, can work all the year and provide cooling/hot-water/power in summer, heating/hot-water/power in winter and hot-water/power in other seasons. In CCHP systems, the total energy efficiency increases to over 85%, while the average energy efficiency of conventional fossil fuel fired electricity generation systems is around 40%. The energy efficiency promotion of CCHP systems results in emission reduction compared to the conventional methods of generating heat and electricity separately. And as a distributed energy resource, CCHP systems also increase in the reliability of the energy supply. With the overall development of CCHP systems and related technologies, the utilization of micro CCHP systems in the residential sector is emerged as a growing potential. The article focuses on the micro CCHP systems for single-family applications (around 10 kW) and multi-family or residential district applications (under 200 kW). The status quo of micro CCHP systems is briefly presented and diverse combinations of technologies existing in applications or experimental units are listed through comprehensive literature review. Various technologies available or under development are introduced, such as reciprocating internal combustion engine, micro-turbine, fuel cell, Stirling engine, absorption chiller, adsorption chiller and so on. Afterward, the tendency and issues of micro CCHP systems are discussed. The review shows that micro-CCHP
*
A version of this chapter was also published in Leading-Edge Electric Power Research edited by C.M. O’Sullivan published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research.
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applications are entering into average families as a next-generation residential energy supply center.
INTRODUCTION The conventional way to cover electricity, heating and cooling demands is to purchase electricity from the local grid, generate heat by burning fuel in a boiler and obtain space cooling power from diverse air-conditions. But in a CCHP system, byproduct heat that can be up to eighty percent of total primary energy in combustion-based electricity generation is recycled for different uses. CCHP, generally, is defined as combined production of electrical and useful thermal energy from the same primary energy source [1]. In some literatures, CCHP systems are also named as Tri-generation and BCHP (Building Cooling Heating and Power) systems.
Figure 1. Energy Flow of Traditional mode.
Figure 2. Energy Flow of CCHP System.
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Recent development of CCHP systems, to large extent, is related to the emergence of DER (Distributed/Decentralized Energy Resources) - a novel technical concept in the region of energy supply. DER is defined as an electricity generation system located in or near users, providing electrical and thermal energy synchronously to meet the demands of local users in priority. The CCHP systems discussed in this article is in the category of DER, and they are different from traditional CHP systems, which, mostly, are large-scale centralized power plants without cooling power generated. Distributed CCHP systems share some advantages [2,3,4,5] compared to traditional energy supplies, along with their developing tendency and promising prospect. First of all, overall energy efficiency is dramatically improved, ranging from 70% to more than 90% compared to up to 40-45% of typical centralized power plants. With the primary energy saving, vast cost reductions including fuel costs, transmission and distribution savings can be achieved. Secondly, environment benefits derive from emission reduction. This benefit can be viewed from two aspects sorted by different kinds of prime movers. Some prime movers with new technologies like fuel cells, micro-turbines do expel much less emissions including NOx, CO2 than the traditional technologies taken by centralized power plants do. However, other prime movers equipped in CCHP systems with smaller capacity as their same kinds of large counterpoints in centralized power plants, emit a bit more amount of NOx and CO2 per kW electricity generated. Nevertheless, energy efficiency promotion of CCHP systems should be taken into account at this time. Burning much less fuel to meet same demands results significant emission reduction, which surely exceeds the impact of emission augment caused by slight decrease of small-scale prime mover convert efficiency. Last but not the least, CCHP systems increase in the reliability of the energy supply. Obviously, generation/distribution system malfunctions, terrible weather and terrorism are fatal threatens leading to disruptions of centralized power plants. A smaller, more flexible and dispersed system as distributed CCHP unit is possible to avoid these threatens being realities, and then limited influences and fast recovery could be achieved if these situations unluckily happened. A study following the 11th September attacks suggested that a system based more on distributed generation plants may be five times less sensitive to systematic attack than a centralized power system [6]. Distributed CCHP systems are suitable for various industrial, institutional, commercial and residential applications, and the capacities of these systems range widely from less than 1 kW in domestic dwellings to more than 1 MW in some industries or university campuses. Since last decade, many CCHP applications have been set up in hospitals, university campuses, commercial complexes, hotels, clubs, leisure centers, office buildings and residential districts. With the progress of some critical technologies such as fuel cells and micro-turbines, more and more literatures focus on small, even micro level CCHP systems recently, which are especially for single- family (1-5kW) or multi-family residential buildings and small residential districts, ranging from 5kW up to 200kW.
MICRO RESIDENTIAL CCHP SYSTEMS Different prime movers with heat recovery equipments and further connecting with different cooling or dehumidification options can result in various kinds of CCHP systems, but only several modes of combination are adopted in recent commercial market, other
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promising possibilities still remain in laboratory to overcome their disadvantages in technology or economy. Reciprocating engines, micro-turbines, electrical chillers and absorption chillers are currently predominant for the maturity and stability of these technologies. Reciprocating internal combustion engines plus absorption or electrical (engine driven) chillers are popular for small scale utilizations. Jacket cooling fluids, lubricating oil systems, and engine exhaust are three heat recovery options which can produce hot water using exchangers, for heat demands and other cooling and dehumidification usages, seen in Figure 3. This kind of configuration has existed for quite a few years, and there are many applications ranging form 100kW up to 1MW in industrial, institutional, commercial sectors. But distributed CCHP applications with engines below 100kW for residential dwellings can be seldom found until recent years. In 2001, M.A. Smith [8] analyzes a micro CCHP system with an engine and a heat pump in his articles. The rated capacity of the engine is as low as 1.5kW and with the help of a heat pump the heat generated is around 4.5kW. Miguez [9, 10] also illustrates design and performance of a CCHP system with engine (9.6kW) and heat pump equipment. In 2004, a micro CCHP system at Shanghai Jiao Tong University with novel adsorption chiller generating cooling power, which uses heat recovered from a gas engine of 12kW rated capacity, was experimented [11]. Commercial compact micro CCHP products also can be found in US and Europe now. The ‘ecopower’ micro CCHP unit of Marathon Engine Co. fueled by natural gas or propane gas, generates 2-5kW electricity and up to 13.8kW thermal power at the max. temperature of 75 . Typical applications of these units are single and multi-family homes [12].
Figure 3. Schematic of reciprocating engine heat recovery [6, 7].
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Recently, a household size CCHP unit based on a small-scale diesel engine generator set (9.5kW) is reported [13]. An absorption refrigerator driven by the exhaust heat from the engine is as the cooling option of this system. It is point out in the paper that the CO2 emission per unit (kWh) of useful energy output from this micro CCHP system is dramatically reduced compared to that of conventional generations.
Figure 4. Schematic diagram of micro-turbine [6, 7].
Another popular prime mover, micro-turbines are classified into two categories: combustion turbine and Rankine cycle turbine according to literatures. Capstone Turbine Co. is the leading competitor in the field of micro combustion turbines. Current production microturbines range in net power output from 30 to 250kW. Their low maintenance and clean exhaust make them a reliable choice for base load CCHP applications. Integrating hot water heat recovery into the micro-turbine package has proven cost effective, and a growing number of commercial installations are saving money using this technology [14]. Absorption chillers and desiccant dehumidifiers driven by recovery heat of micro combustion turbines are employed to meet cooling demands of users. This configuration of CCHP systems is applied in many locations, especially in the US, where turbine-based units have become serious competitors with engine-based units in the CCHP market. But micro turbine unit is not applied separately for single dwellings. In most cases, several modularized minimal units of 30kW can be combined together to fit user’s electricity profiles, while they still share flexibility in operation. The capacity of most applications with micro combustion turbines, especially in hotels, hospitals and university campus buildings, are beyond the micro level. One obvious drawback of this technology is prominent high initial investment cost, which prevents its popularities in residential sector. Average residential building owners maybe cannot afford to this advanced technology. In the other category, some micro Rankine cycle turbines combined with solar collection are reported. Both W. Yagoub [15] and S.B. Riffat [16] introduced a solar energy-gas driven micro-CHP system. Solar energy collector of 25kW thermal capacity, supplemented by a
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condensing gas boiler, was used to drive a 1.5 kW Rankine cycle micro-turbine generator unit. The literatures of micro CCHP units with Rankine cycle micro-turbine are limited. This type of turbine is not a popular choice in the residential building field till now.
Figure 5. STM 4-120 power unit packaged DG system [17].
Among the newly emerged prime mover technologies, the Stirling engine is viewed as a promising prime mover in small commercial and residential applications for their low emissions, fewer moving parts, low noise, small-scale availability and relatively low byproduct heat. The Stirling engine CCHP systems are also suitable for modular installation as micro combustion turbines. And due to temperature limitations of the engine components, heat recovery from coolant systems account for almost 50% of the heat input. This results in a significant amount of heat suitable for space heating, cooking, potable hot water, and low temperature processes. The possible cooling and dehumidification options for Stirling engines are absorption chillers, dehumidifiers and adsorption chillers. There has also been research on the feasibility of CCHP driven by Stirling engines [18]. Currently, only a few commercial Stirling engine units can be found in the CCHP market. The most active company developing Stirling engine distributed generation technology is STM Power, Inc. STM has conducted field tests of this application with their 25kW model, STM 4-120 [17], which is the first commercialized Stirling engine in the world. The new prototype, STM’s 55kW engine, can produce 92kW, while a 3kW engine will produce 6kW. Other companies in this industry reported systems under development that range from 55 watts to 3,000 watts. Sigma co. is developing a 3 kW electrical output and 9 kW thermal output engine for a single-family dwelling. The electrical efficiency of the unit is reported to be 25% [19]. And SOLO, a German Company has developed Stirling engine CHP unit fueled by natural gas. The unit generates electrical power of 2–9 kW and thermal power of 8–24 kW and has an overall efficiency of 92–96% [20]. In Canada, a project was initiated to integrate a prototype micro CCHP unit into a residential house that would provide electricity and heat to the house, and supply surplus electricity back to the grid [21]. This Stirling engine based micro CCHP unit,
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fuelled by natural gas, had an electrical output of 736W and a thermal output of 6.5kW. In general, Stirling engine is an ideal technology for residential micro CCHP systems, but it also has the disadvantage as micro turbine has, its high capital cost. Though still on the brink of market entry, fuel cells are the focus of interest as the prime mover technology for micro CCHP systems to serve a variety of residential buildings in the future. Fuel cells are electrochemical devices that convert the energy of a chemical reaction directly into electricity and heat. They are similar in principle to primary batteries except that the fuel and oxidant are supplied to the cell, rather than stored internally. They are silent in operation, modular without moving parts, which are perfect merits for residential sector, but there is limited experience to validate potential applications. Moreover, fuel cells micro CCHP systems carry high capital costs and higher project risk due to unproven durability and reliability. At the beginning of this century, several first prototype systems were reported by utility companies, heating appliance manufacturers and RandD centers in Europe, Japan, and the US. After that, further steps towards industrialization and product development were reported. Yasuhiro Hamada et al. tested the performance of a 1kW polymer electrolyte fuel cell as a residential energy system, of which the electrical efficiency and heat recovery efficiency are 42.5% and 49.2% respectively [22]. Afterward, Tokyo Gas Co., Ltd. marketed the first domestic polymer electrolyte fuel cell with 1kW capacity and 31% generation efficiency in 2005 [23]. G. Gigliucci et al. [24] introduced a PEM fuel cell CHP system supplied by HPower in Italy. The system converts natural gas into electricity and heat, at nominal conditions, 4kW of electric power and 6.8kW of thermal power: the former is delivered to local loads using electric load following capability; the latter is delivered to the experimental area hydraulic refrigeration circuit. S. Giddey et al. [25] describes the design and assembly of a 1kW PEM stack tested, analysis of the results and problems encountered during operation. The electrical efficiency of the stack varies from 39 to 41%. The recoverable combined heat and power efficiency of the stack is 65% without external thermal insulation and 80% with external thermal insulation. A PEMFC system is studied by Charles-Emile Hubert [26]. Five units were installed from November 2002 to May 2003 and have been operated in real life conditions. They deliver up to 4kW of AC power and about 6kW of heat. P. Koenig et al. [27] analyzes a prototype PEMFC CHP system for decentralized energy supply in domestic applications. The complete system supplies 2kW electricity and approximately 4 kW heating power at 60 for domestic hot water and space heating. The tests include steady state measurements under different electrical and thermal loads as well as an analysis of the dynamic behavior of the system during load changes. While polymer electrolyte fuel cell keeps developing, solid oxide fuel cell remains one of the most promising options for distributed CCHP applications, with the prospect for incredibly high electrical generation efficiency. Several companies are keen on developing SOFC technology for the residential CCHP market since 1995. Fuel Cells Bulletin [28] reports that a Home Energy Centre, provided by the Baxi Group, supplied all the heat and electricity for a new four-bedroom house in Scotland. The Home Energy Centre is based around a PEM fuel cell combined with a natural gas reformer. It provides 1.5kW of electricity and 18kW of heat, sufficient for all of an average domestic property’s heat requirements and up to 75% of its electrical power needs, all year round. At the same time, some other researchers try to make SOFC applications more suitable for modern family dwellings. A.D.
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Hawkes et al. [29] point out that SOFC-based micro CCHP applications have a low heat-topower ratio and may benefit from avoidance of thermal cycling.
Figure 6. A solid polymer fuel cell system [29].
They also find that these units suit to slow space heating demands, where the heating system is on constantly during virtually all of the winter period. R.J. Braun et al. [30] evaluate five different SOFC system designs in terms of their energetic performance and suitability for meeting residential thermal-to-electric ratios. Effective system concepts and key performance parameters are identified. The results indicate that maximum efficiency is achieved when cathode and anode gas recirculation is used along with internal reforming of methane. System electric efficiencies of 45% and combined heat and power efficiencies of 88% are described. In the near future, fuel cell based residential micro-CCHP systems will compete with traditional energy supplies. Some literatures assess energy utilization, emission aspect or economic feasibility of this type of micro CCHP in the residential sector. V. Dorer [31] establishes a methodology for assessing the performance of SOFC and PEMFC systems in terms of primary energy demand and the CO2 emissions by transient computer simulations. Adam Hawkes [32] explores the performance of a hypothetical SOFC system under UK market conditions at that time. He indicates that the optimized result of a household SOFC micro CHP system depends on system size, energy import prices, electricity export price, stack capital costs or an improvement in stack life time. Another financial analysis of SOFC units is carried out by Kari Alanne et al. [33], to evaluate the sensitivity of the maximum allowable capital cost with respect to system sizing, acceptable payback period, energy price and the electricity buyback strategy of an energy utility. Based on this financial analysis, micro (1–2kW) SOFC systems seem to be feasible in the considered case.
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STATUS AND DEVELOPMENT OF MICRO CCHP TECHNOLOGIES A typical CCHP system consists of five basic elements: prime mover; electricity generator; heat recovery system; thermally activated equipment (or other cooling options) and management and control system. Among them, prime movers obviously play a critical role; they are the keystones of CCHP systems and, to some extent, they determine possibilities and availability of other related technologies. (Seen in Table 2). Although steam turbine and combustion turbine are two crucial technologies for centralized CHP plants, there is almost no small capacity product in the residential level. For micro CCHP systems, the options of prime movers can be reciprocating internal combustion engine, micro-turbine, stirling engine and fuel cell. All the options can be selected by users to meet dissimilar demands and limitations from site to site: especially local heat and electricity profiles, regional emissions and noises regulations and installation place restrictions. Thermally activated equipment is another essential part of a CCHP system to provide cooling or dehumidification. Commercialized thermally activated technologies include absorption chillers and desiccant dehumidifiers. Moreover, novel adsorption chillers approaching commercial stage can be another choice for micro CCHP systems. Some existed systems also apply electric chillers or engine-driven chillers integrated with prime movers to fulfill cooling demands, which combined with thermally activated technologies to be called cooling options of CCHP system in some literatures.
Prime Movers Reciprocating Internal Combustion Engines [1,6,7,17,34-36] Two types of internal combustion engines are currently in use; spark ignition engines, which are operated mainly with natural gas; and compression ignition engines, which can use diesel fuel, as well as other petroleum products, such as heavy fuel oil or biodiesel. In addition to fast start–up capability and good operating reliability, relatively high efficiency at partial load operation gives users a flexible power source. Reciprocating engines are by far the most commonly used power generation equipment under 1 MW. Although they are a mature technology, reciprocating engines have obvious drawbacks. Relatively high vibrations require shock absorption and shielding measures to reduce acoustic noise. A large number of moving parts with frequent maintenance intervals, increase maintenance costs and strongly offset fuel efficiency advantages. Moreover, high emissions, -particularly nitrogen oxides-- are the underlying aspect of this technology and need to be improved. Major manufacturers around the world continuously develop new engines with lower emissions; at the same time, emissions control options, such as selective catalytic reduction (SCR), have been utilized to reduce emissions. Micro-Turbines [1,7,17, 34,35,37] Micro-turbines extend combustion turbine technology to smaller scales. They are primarily fuelled with natural gas, but they can also operate with diesel, gasoline or other similar high-energy fuels. Research on biogas is ongoing. Micro-turbines have only one
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moving part; they use air bearings and do not need lubricating oil, although they have extremely high rotational speed, up to 120000 rpm. A striking characteristic is their flexibility that small-scale individual units can be combined readily into large systems of multiple units. Additionally, there are environmental advantages, such as low combustion temperatures assuring low NOx emissions levels and less noise than an engine of comparable size. This technology has been commercialized for only a few years and is offered by a small number of suppliers. The main disadvantage at this stage is its high costs compared with engine. Other flaws include relatively low electrical efficiency and sensitivity of efficiency to changes in ambient conditions.
Stirling Engines [1,17,34,35] Compared to conventional internal combustion engines, Stirling engines have an external combustion device in which the cycle medium--generally helium or hydrogen--is not exchanged during each cycle, but remains within the cycle while the energy driving the cycle is applied externally. Stirling engines can operate on almost any fuel (gasoline, alcohol, natural gas or butane), with the external combustion that facilitates the control of the combustion process and results in low air emissions, low noise and more efficient process. In addition, fewer moving parts compared to conventional engines limit wear on components and reduce vibration levels. Stirling engine is still in its development. High cost also prevents popularization of this technology. Nevertheless, the promising prospects of stirling engines stimulate further research, especially for CCHP applications. Small size and quiet operation mean that they will integrate well into residential or portable applications. Some literature indicates the possibility of using a solar dish to heat the Stirling engine, thus eliminating the need for combustion of a fuel. Fuel Cells [1,6,7,34,35,37,38] Fuel cells are quiet, compact power generators without moving parts, which use hydrogen and oxygen to make electricity; at the same time, provide heat for a wide range of applications. In general, fuel cells show high electrical efficiencies under varying load, and which results in low emissions. Besides transportation sector, power generation is another promising market. Five major fuel cell technologies listed below have the most attractive prospects. A detail comparison of the characteristics of these fuel cells appears in Table 1. Proton Exchange Membrane Fuel Cell (PEMFC) Also known as Polymer Electrolyte Membrane Fuel Cell, PEM fuel cells are quite simple and can be made very small to adjust to variable power demands. They are easier to start up and they apply solid electrolyte that reduces corrosion. At the same time, the low operating temperature requires the use of an expensive platinum catalyst, which limits the cogeneration potential. As for the fuel sources, this fuel cell technology is highly sensitive to fuel impurities and hydrogen storage; delivery and reforming technology has yet to evolve. With relatively low quality heat, PEM fuel cell is unlikely to be widely used for high voltage stationary power generation; but small–scale domestic CCHP applications --the simplest thermal load of which is hot water-- would be considerable.
Table 1. Characteristics of fuel cells [17,34,35] PEMFC
AFC
PAFC
MCFC
SOFC
Charge Carrier Type of Electrolyte
H+ ions Polymeric membrane
H+ ions Phosphoric acid solutions
CO3= ions Phosphoric acid (Immobilized liquid)
Typical Construction
Plastic, metal or carbon
OH- ions Aqueous potassium hydroxide soaked in a matrix Plastic, metal
Carbon, porous ceramics
Catalyst Oxidant
Platinum Air or O2
Platinum Purified Air or O2
Fuel
Hydrocarbons or methanol
Operational Temperature Size Range Electrical Efficiency Primary Contaminants
50-100°C 3-250kW 30-50% CO, Sulfur, and NH3
Clean hydrogen or hydrazine 60-80°C 10-200kW 32-70% CO, CO2, and Sulfur
Platinum Air or Oxygen- Enriched Air Hydrocarbons or alcohols 100-200°C 100-200kW 40-55% CO>1%, Sulfur
High temp metals, porous ceramic Nickel Air
O= ions Stabilized zirconia ceramic matrix with free oxide ions Ceramic, high temp metals Parasites Air
Clean hydrogen, nature gas, propane, diesel 600-700°C 250kW-5MW 55-57% Sulfur
Natural gas or propane 600-1000°C 100kW-10MW 50-60% Sulfur
Table 2. Characteristics and parameters of prime movers in CCHP systems [1,17,34,35,37,47,48] Diesel engines Capacity range
Micro-turbines
String Engines
Fuel Cells
15-300kW Gas, Propane, Distillate Oils, Biogas
1kW-1.5MW Any (Gas, Alcohol, Butane, Biogas)
Efficiency electrical (%)
35-45
25-43
15-30
~ 40
5kW-2MW Hydrogen and fuels containing hydrocarbons 37-60
Efficiency overall (%)
65-90
70-92
60-85
65-85
85-90
Power to Heat Ratio
0.8-2.4
0.5-0.7
1.2-1.7
1.2-1.7
0.8-1.1
Output heat temperature (℃)
*
*
200-350**
60-200
260-370
Noise
Loud
Loud
Fair
Fair
Quiet
CO2 emissions (kg/ MWh)
650
500-620
720
672***
430-490
NOx emissions (kg/ MWh)
10
0.2-1.0
0.1
0.23****
0.005-0.01
Availability (%)
95
95
98
N/A
90-95
Part load performance
Good
Good
Fair
Good
Good
Life cycle (year)
20
20
10
10
10-20
Average cost investment ($/kW)
340-1000
800-1600
900-1500
1300-2000
2500-3500
Operating and maintenances costs ($/kWh)
0.0075-0.015
0.0075-0.015
0.01-0.02
N/A
0.007-0.05
Fuel used
5kW-20MW Gas, Propane, Distillate Oils, Biogas
Spark ignition engines 3kW-6MW Gas, Biogas, Liquid Fuels, Propane
Up to a third of the fuel energy is available in the exhaust at temperatures from 370-540ºC; other rejected heat is low temperature, often too low for most processes. (Jacket cooling water at 80 to 95ºC, lube oil cooling at 70ºC and intercooler heat rejection at 60ºC, all difficult to use in CHP). ** 650ºC without recuperator. *** Stirling Engine Emission Characteristics / STM 4–260. Gas-Fired Distributed Energy Resource Technology Characterizations. *
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Alkaline Fuel Cell (AFC) Alkaline fuel cells are the first fuel cells used on spacecrafts and space shuttles. The technology shares obvious merits, such as low operating temperature, rapid start–up time, readily available non-precious metal electrodes, and high efficiency, up to 70%. However, the primary disadvantage is the tendency to absorb carbon dioxide, converting the alkaline electrolyte to an aqueous carbonate electrolyte that is less conductive. Thus, the fuel input should be restricted to pure hydrogen, which limits applications to those in which pure hydrogen are available. If the CO2 is removed from fuel and oxygen streams, the operating costs are much greater. Although the attractiveness of AFC has declined substantially with the interest and improvements in PEMFC technology, recent developers still believe that it can be used for many applications, such as stationary power generation, but also mobile applications including both marine and road vehicles. Phosphoric Acid Fuel Cell (PAFC) Phosphoric acid fuel cells are the most mature of the technologies in commercial production, although its costs remain uncompetitive with other non-fuel cell technologies. Hydrogen is still the ultimate fuel for the reaction in the phosphoric acid fuel cell, but various fuels, including natural gas, LPG and methanol, can be used as raw input converted by a reformer. Other advantages are its resistance to fuel impurities, and the ability to use a less expensive catalyst. The drawbacks of this fuel cell include a lower efficiency than other fuel cell technologies and corrosive liquid electrolyte. In the near future, with lower operating temperatures, PAFC would be ideal for small and mid–size power plants, replacing large electrical generators and other types of CCHP utilities in hospitals, hotels and airports. Molten Carbonate Fuel Cells (MCFC) A molten carbonate fuel cell uses a molten carbonate salt mixture as its electrolyte. The composition of the electrolyte varies, but usually consists of lithium carbonate and potassium carbonate, which is chemically aggressive and puts strain on the stability and wear of the cell components. As a result, MCFC is more expensive than either SOFC or PEMFC in terms of capital cost. Fuel reforming of MCFC occurs inside the stack and tolerates impurities; therefore, this technology may use a variety of fuels. In addition, the high operating temperature allows for combined heat and power generation and high fuel–to–electricity efficiency. Nevertheless, the long start–up time to reach operating temperatures, and poorer flexibility in output, make MCFC ideally suited to base load power generation where continuous operation is necessary, such as heavy industries and national electrical grid networks. Solid Oxide Fuel Cell (SOFC) Due to all–solid–state ceramic construction, solid oxide fuel cells share important characteristics, such as stability and reliability. A variety of hydrocarbon fuels can be used, like gasoline, methanol and natural gas. As another asset, the high operating temperature makes internal reforming possible and removes the need for a catalyst, which also produces high grade waste heat suited well to CCHP applications. But the high temperature also creates some difficulties: expensive alloys for components are required, quit a long time is needed for the electrolyte to heat. Start-up time is less of an issue for stationary and continuous
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applications. They generally achieve around 60% efficiency in a 5MW plant, compared to around 30% for a traditional gas turbine. The last critical problem that prevents its commercialization is the comparatively high costs of SOFC.
Thermally–Activated Technologies An important difference between CCHP systems and conventional cogenerations is that CCHP systems –including some cooling or dehumidification components– provide not only electricity and heating but also cooling capacity for space or process. These cooling or dehumidification options can employ advanced thermally–activated technologies as well as traditional technologies. But recent research indicates that thermally–activated technologies are favored, as the overall efficiency of CCHP systems is promoted with applications of these thermally–activated technologies. In addition to high efficiency, other benefits such as low emissions and cost reduction are also achieved with thermally–activated technologies. Major thermally–activated technologies include absorption chillers, adsorption chillers and desiccant dehumidifiers. These cooling and dehumidification systems can be driven by steam, hot water or hot exhaust gas derived from prime movers. However, waste heat from various prime movers falls into different temperature ranges; at the same time, cooling and dehumidification systems have their own suitable working temperature. As a result, optimal matching of recoverable energy streams with thermally driven technologies is shown in Table 3. Table 3. Recoverable energy qualities with matching technologies [39] Power Source Solid Oxide Fuel Cell Micro-turbine Phosphoric Acid Fuel Cell
Temp. ~ 480°C ~ 320°C ~ 120°C
Stirling Engine
~ 90°C
IC Engine
~ 80°C
PEM Fuel Cell
~ 60°C
Matching Technology Triple-effect/ Double-effect absorption Triple-effect/ Double-effect absorption Double-effect/ Single-effect absorption Single-effect absorption, adsorption or dehumidification Single-effect absorption, adsorption or dehumidification Single-effect absorption, adsorption or dehumidification
Absorption Chillers [7,39,40,41] Absorption chillers are one of the commercialized thermally–activated technologies widely applied in CCHP systems; they are similar to vapor compression chillers, with a few key differences. The basic difference is that a vapor compression chiller uses a rotating device to raise the pressure of refrigerant vapors, while an absorption chiller uses heat to compress the refrigerant vapors to a high–pressure. Therefore, this “thermal compressor” has no moving parts. Depending on how many times the heat supply is utilized; absorption chillers can be divided into single–effect, double–effect and triple–effect. The parameters and traits of different absorption chillers can be viewed in Table 4.
Table 4. Characteristics of absorption technologies [49] System
Operating Temp. ( ) Heat source Cooling
Working Fluid
Cooling Capacity (ton)
COP
Current Status
Single effect cycle
80–110
5–10
LiBr/ water
10-1500
0.50.7
Large water chiller
Single effect cycle
120–150
150
High–temperature waste heat
Space cooling, refrigeration
Solar energy, low–temperature waste heat
Low temperature, ice making
Solar energy, low–temperature waste heat
Low temperature, ice making
95
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The most common working fluids for absorption chillers are water/NH3 and LiBr/water, although there are 40 refrigerant compounds and 200 absorbent compounds available in theory [49]. Lithium–bromide/water absorption chillers play a predominant role in the absorption chiller market in Asia-Pacific countries like China, Japan, Korea, and in the US. In contrast, ammonia/water absorptions chillers are more popular in Europe.
Adsorption Chillers [42-45] Adsorption–cooling technology is a novel, environmentally–friendly and effective means of using low–grade heat sources. Unlike conventional vapor compression systems which require a mechanical compressor assembly, this new technology uses a thermally–driven static sorption bed, saving as much as 90% of the required input power typically used to drive a mechanical compressor. The system takes advantage of the ability of certain sorbent material, stored in a sorption bed, to soak up a relatively large quantity of refrigerant vapor at some low temperature and pressure. At this stage, cooling capacity is achieved in the evaporator because of the evaporation of the refrigerant. The refrigerant is subsequently released to the condenser at a higher pressure simply by applying heat to the sorbent bed. To increase the efficiency and provide continuous cooling, more than one sorption bed is often used. A heat regeneration fluid also can be used to increase system efficiency by transferring heat from a hot to a cold bed. As a critical part of this technology, the characteristics of various adsorbent–adsorbate working pairs are listed in the Table 5. Since there are no moving parts, except for valves, the sorption system is considerably simpler, requiring no lubrication and thus, little maintenance. Other advantages include quiet operation and modularity so it is readily scalable for increased heating and cooling capacity by additional beds. Furthermore, any heat source, such as waste heat or renewable energy, can be used, so energy saving can be potentially significant. Desiccant Dehumidifiers [3,40,41] Desiccant dehumidifiers can work in concert with sorption chillers or conventional air conditioning systems to significantly increase overall system energy efficiency by avoiding overcooling air and precluding oversized capacity to meet dehumidification loads. The desiccant process involves exposing the desiccant material (such as silica gel, activated alumina, lithium chloride salt or molecular sieves) to a moisture-laden process air stream, retaining the moisture of the air in desiccant and regenerating desiccant material via a heated air stream. System capacity is often expressed in volume of airflow or in moisture removal rate. Table 6 shows some specifications. Table 6. Performance of desiccant dehumidification systems [41] Flux (m3/min)
Thermal Input (W/m3/min)
Maximum Latent Removal (W/m3/min)
40-140 140-280 280+
300-1000 300-1000 300-1000
300-600 300-600 300-600
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Dehumidification technology is divided into two major types, solid desiccant dehumidifiers and liquid desiccant dehumidifiers; both are useful for the mitigation of indoor environmental quality and security problems and for humidity control in buildings. Dehumidification technology in the commercial sector remains a young technology with a premium price. Yet, commercial desiccant technologies have not been designed for integration into CCHP systems.
Other Options Although thermally–activated technologies indicate the trend in cooling and dehumidification options in CCHP systems, electric vapor-compression refrigeration systems still play an important role for their maturity and reliability. Therefore, quite a few CCHP systems in research and practical utilization still employ these conventional technologies as their cooling options. Nonetheless, it is unwise for a CCHP system to drive chillers using electricity generated by prime movers, since smaller prime movers have lower efficiency than larger types used in power plants. Engine–driven chillers emerge to substitute electric chillers in CCHP units, avoiding the losses in energy conversion. Engine–driven chillers, including reciprocating types, centrifugal types and screw types, are conventional chillers driven by an engine, in lieu of an electric motor. An advantage of engine–driven chillers is better variable speed performance, which improves partial–load efficiency. Engine–driven chillers can also operate in a CCHP system for hot water loads when the waste heat produced by the engine is recovered.
RESEARCH TENDENCY OF MICRO RESIDENTIAL CCHP Development of distributed CCHP systems has been undergoing for almost two decades, while many related technologies have been employed and ameliorated in this field through comprehensive researches. Micro residential CCHP systems for single- or multi-family buildings as new applications emerge in recent years. The technologies used in distributed CCHP systems are miniaturized and improved to better fit for micro residential utilizations [50,51,52,53]. Besides that, some novel technologies are also invented as new alternatives. Except for detail improvement or invention in specific technologies, new design methods for the whole micro CCHP systems are introduced in some literatures. Andrew Wright et al. [54] describe exploratory analyses of domestic electricity-profiles recorded at a high time resolution of 1 min on eight houses, while most load data are available at half-hour intervals. It is included that for dwellings with micro CCHP, a better understanding of electricity profiles is important for the economic analysis of systems, and to examine the effects of widespread onsite generation on local electricity-networks. In Adam Hawkes’s paper [55], it is also indicated that coarse temporal precision profiles of 1-h demand blocks in heat and power demands become questionable for applications where demand exhibits substantial volatility such as for a single residential dwelling—an important potential market for the commercialization of small-scale fuel cells. Total CO2 emissions reduction is overestimated by up to 40% by the analyses completed using coarse demand data for a given micro CCHP unit. The economic difference is also significant at up to 8% of lifetime costs. H. Lund [56]
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presents the Danish experience with methodologies and software tools, which have been used to design investment and operation strategies for almost all small CCHP plants in Denmark during the decade of the triple tariff. Moreover, the changes in such methodologies and tools in order to optimize performance in a market with fluctuating electricity prices are discussed. For existed CCHP systems, various criteria are employed to compare different systems and obtain the best configuration of a typical application. Some simulation models are also presented in some papers to optimize operating performance, system configuration and control strategy. Aiying Rong [57] illustrates a long-term planning model based on hourly load forecasts to obtain cost-efficient operation of a CCHP system. This linear programming model with a joint characteristic for three energy components minimizes simultaneously the production and purchase costs of three energy components, as well as CO2 emissions costs. S.M. Ameli [58] presents the works which have been done and yielded results about the requirements of developing integrated distributed energy evaluation software. The comprehensive software package is for designing, optimizing and monitoring of distributed energy systems based on micro-turbine, fuel cell and internal combustion engine driven systems. A.D. Peacock et al. [59] employs a 50 dwelling data set of heat and power demands to investigate the implementation of various penetrations of micro CHP system on the resultant electrical load profile using two control methodologies: heat-led and a proposed method for modulating the aggregate electrical load. And they point out that further improvements in the modulating capability of this control approach may be realized if prime movers capable of rapid start-up, shut-down and cycling can be developed. A.D. Hawkes et al. [60] investigate cost effective operating strategies for three micro CCHP technologies; Stirling engine, gas engine, and solid oxide fuel cell. In this paper, central estimates of price parameters are used, which is shown that the least cost operating strategy for the three technologies is to follow heat and electricity load during winter months, rather than using either heat demand or electricity demand as the only dispatch signal. Least cost operating strategy varies between technologies in summer months. In another paper, A.D. Hawkes et al. [61] develop a techno-economic modeling of a solid oxide fuel cell stack for micro CHP system. Some literatures of internal combustion engine for residential sector also can be found. Hycienth I. Onovwiona et al. [62] present a parametric model that can be used in the design and techno-economic evaluation of internal combustion engine based CCHP systems for residential use. The model, which is suitable to provide system performance information in response to a building’s electrical and thermal demands, and is capable of simulating the performance of these systems in 15-min time steps. After focusing on the design, assessment and simulation of typical novel micro residential CCHP systems, some researchers begin to consider the future scenario of micro CCHP systems in residential sector, the relationship between distributed micro residential CCHP systems with centralized power plants and comparison in emission, economy and social cost–benefit between them. Samuel Bernstein [63], H. Lund [64], Ineke S.M. Meijer [65], Jeremy Cockroft [66], discuss various aspect of the development situation of residential CCHP applications in US, Lithuania, Netherlands and UK, while Neil Strachan [67] and Francesco Gulli [68] provide a brand-new view point toward distributed CCHP systems including micro residential CCHP units, which deserves to investigate further.
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CONCLUSION Micro residential CCHP systems share some important advantages with distributed CCHP systems: high overall energy efficiency ranging from 70% to more than 90%; less prime energy consumption; emission reduction and increase in the reliability of the energy supply. The electricity, heating and cooling demands of a family can be covered by micro CCHP systems simultaneously and independently, which is similar to larger systems, although larger systems have already well proven in quite a few applications of industrial, institutional and commercial buildings. A review of the current applications, demonstrations and experimental systems for residential single- or multi-family buildings has been presented. The prime movers applied in these systems include small traditional reciprocating internal combustion engine as well as micro-turbines, novel Stirling engine and fuel cells, especially PEMFC and SOFC. These technologies are suitable for residential applications to meet electricity demands. Although most systems listed are just cover the electricity and heat demands, some applications are also combined with certain thermally activated cooling options, such as small absorption chiller or adsorption chiller, to meet the space cooling demands in summer. In general, micro residential CCHP systems include both these two types of family energy supply centers. The review of micro CCHP applications illustrate that such kind of energy supply for families develops rapidly in recent years and many of them are in the edge of market entry. A further review analyzes the technologies used in micro residential systems comprehensively. Generally speaking, reciprocating engine based micro CCHP systems are the most realistic and reliable product for single- or multi- family buildings in current market. Micro turbine based systems are also feasible in technology, but too expensive to be afforded. Stirling engine based systems become an important competitor in the market, because of their versatility in fuel and other advantages compare with internal combustion engines. However, several obstacles need to be surmounted, especially high initial investment cost. In long views, fuel cell based micro CCHP systems are the most promising technologies. SOFC and PEMFC systems are in the beginning stage of commercialization. With technology improvement and large scale production, the capital costs of fuel cells will reduce rapidly in next decade. It is also critical to develop micro scale thermal initialized cooling technologies for single-family dwellings. Most demonstrations and applications of micro CCHP systems are actually only micro CHP (combined heating and power) systems. But in many places of the world, cooling demand of a family dwelling in summer is even larger than heating demand in winter. Consequently, micro scale absorption chiller, adsorption chiller and desiccant dehumidifiers are also an important part of future residential energy center. Research issues indicate the future tendency and direction of micro residential CCHP systems. Development of specific CCHP technologies is always the most critical research content, which is to find ways to overcome drawbacks of certain technology, pursuit higher energy efficiency, diminish emissions, reduce the capital cost and follow users’ electricity and heat profiles more precisely and economically. At the same time, new design methods for the whole micro CCHP system are necessary to be built up. While basic equipment technologies are available, a core thought is needed to optimize CCHP configuration, control strategies and economical operation. Besides that, various criteria are discussed to better estimate and compare different existed micro CCHP systems, which also stimulate and assist the
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development of the core designing thought. Similarly, simulation models of typical technologies or the whole systems also help to optimize operating performance, system configuration and control strategy. Diverse research results of the future scenario of micro residential CCHP systems indicate that distributed micro residential CCHP system is, to some extent, a controversial energy supply mode. The relationship between distributed micro residential CCHP systems with centralized power plants is necessitated to be further compared in energy, emission, economy, environment and social benefit aspects. Despite of some discussion, it is believed that micro residential CCHP systems would be the next generation of family energy supply center in decades.
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[49] A Review of Absorption Refrigeration Technologies. Renewable and Sustainable Energy Reviews, 5, 343-372. Pongsid Srikhirin, Satha Aphornratana, Supachart Chungpaibulpatana. (2001). [50] Absorption chiller crystallization control strategies for integrated cooling heating and power systems. International Journal of Refrigeration 1-8, (Article in press). Xiaohong Liao, Reinhard Radermacher. (2007). [51] The influence of feedstock drying on the performance and economics of a biomass gasier–engine CHP system. Biomass and Bioenergy, 22, 271 – 281. J.G. Brammer, A.V. Bridgwater. (2002). [52] The influence of operating temperature on the efficiency of a combined heat and power fuel cell plant. Journal of Power Sources, 122, 37–46. S.F. Au, S.J. McPhail, N. Woudstra, K. Hemmes. (2003). [53] Thermodynamic and economic performance of the LiBr–H2O single stage absorption water chiller. Applied Thermal Engineering, 26, 2103–2109. Tomasz M. Mroz. (2006). [54] The nature of domestic electricity-loads and effects of time averaging on statistics and on-site generation calculations. Applied Energy, 84, 389–403. Andrew Wright, Steven Firth. (2007). [55] Impacts of temporal precision in optimisation modeling of micro-Combined Heat and Power. Energy, 30, 1759–1779. Adam Hawkes, Matthew Leach. (2005). [56] Optimal designs of small CHP plants in a market with fluctuating electricity prices. Energy Conversion and Management, 46, 893–904. H. Lund, A.N. Andersen. (2005). [57] An efficient linear programming model and optimization algorithm for trigeneration. Applied Energy, 82, 40–63. Aiying Rong, Risto Lahdelma. (2005). [58] Integrated distributed energy evaluation software (IDEAS) Simulation of a microturbine based CHP system. Applied Thermal Engineering, (Article in press). S.M. Ameli, B. Agnew, I. Potts. (2005). [59] Controlling micro-CHP systems to modulate electrical load profiles. Energy, 32, 1093– 1103. A.D. Peacock, M. Newborough. (2007). [60] Cost-effective operating strategy for residential micro-combined heat and power. Energy, 32, 711–723. A.D. Hawkes, M.A. Leach. (2007). [61] Techno-economic modelling of a solid oxide fuel cell stack for micro combined heat and power. Journal of Power Sources, 156, 321–333. A.D. Hawkes, P. Aguiar, C.A. Hernandez-Aramburo, M.A. Leach, N.P. Brandon, T.C. Green, C.S. Adjiman. (2006). [62] Modeling of internal combustion engine based cogeneration systems for residential applications. Applied Thermal Engineering, 27, 848–861. Hycienth I. Onovwiona, V. Ismet Ugursal, Alan S. Fung. (2007) [63] MICRO-CHP: U.S. market potential and complex challenges. www.energyint.com. Samuel Bernstein. (2004). [64] Implementation strategy for small CHP-plants in a competitive market: the case of Lithuania. Applied Energy, 82, 214–227. H. Lund, G. Siupsinskas, V. Martinaitis. (2005). [65] How perceived uncertainties influence transitions; the case of micro-CHP in the Netherlands. Technological Forecasting and Social Change, (Article in press). Ineke S.M. Meijer, Marko P. Hekkert, Joop F.M. Koppenjan. (2006).
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[66] A comparative assessment of future heat and power sources for the UK domestic sector. Energy Conversion and Management, 47, 2349–2360. Jeremy Cockroft, Nick Kelly. (2006). [67] Emissions from distributed vs. centralized generation: The importance of system performance. Energy Policy, 34, 2677–2689. Neil Strachana, Alexander Farrell. (2006). [68] Small distributed generation versus centralised supply: a social cost–benefit analysis in the residential and service sectors. Energy Policy, 34, 804–832. Francesco Gulli. (2006).
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 1199-1218
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 37
SENSITIVITY CALCULATION IN REAL TIME TRANSMISSION NETWORK AND ENERGY MARKETS* Jizhong Zhu† AREVA T & D Corporation 10865 Willows Rd. NE Redmond, WA 98052, USA
ABSTRACT The calculations of the several sensitivities such as loss sensitivity, voltage sensitivity, generator constraint shift factor, and area based constraint shift factor become very important in energy management system (EMS) and energy markets. This chapter focuses on the analysis and implementation details of the above-mentioned sensitivities calculations in the practical transmission network and energy markets. The power operator uses them to study and monitor market and system behavior and detect possible problems in the operation. These sensitivities calculations are also used to determine whether the on-line capacity as indicated in the resource plan is located in the right place on the network to serve the forecasted demand. If the congestion or violation exists, the generation scheduling based on the sensitivities calculations can determine whether or not a different allocation of the available resources could resolve the congestion or violation problem. This chapter also comprehensively discusses how to compute and use the sensitivities under the different references such as the market-based reference, and the energy management system based reference. The calculation results of the several sensitivities are illustrated using the IEEE 14 bus system and AREVA T & D 60-bus system.
*
A version of this chapter was also published in Leading-Edge Electric Power Research edited by C.M. O’Sullivan published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research. † E-mail:
[email protected] 1200
Jizhong Zhu
I. INTRODUCTION The electric power industry is being relentlessly pressured by governments, politicians, large industries, and investors to privatize, restructure, and deregulate. Despite the changes with different structures, market rules, and uncertainties, an energy management system (EMS) control center must always be in place to maintain the security, reliability, and quality of electric service [1]. It means that EMS in the open energy market must respond quickly, reliably and efficiently to the market changes. In order to achieve the optimal objective in energy markets, the calculations of the several sensitivities such as loss sensitivity, voltage sensitivity, generator constraint shift factor, and area based constraint shift factor become very important. This chapter focuses on the analysis and implementation details of the above-mentioned sensitivities calculations in the practical transmission network and energy markets. The power operator uses them to study and monitor market and system behavior and detect possible problems in the operation. These sensitivities calculations are also used to determine whether the on-line capacity as indicated in the resource plan is located in the right place on the network to serve the forecasted demand. If the congestion or violation exists, the generation scheduling based on the sensitivities calculations can determine whether or not a different allocation of the available resources could resolve the congestion or violation problem. In the early energy market, the transmission losses are neglected for reasons of computational simplicity, but are recently addressed in the Standard Market Design (SMD) [2-4]. The loss calculation is considered for the dispatch functions of SMD such as locationbased marginal prices (LMP). Loss allocation does not affect generation levels or power flows; however it does modify the value of LMP [5]. The early and classic loss calculation approach is the loss formula – B coefficient method [6], which is replaced by the more accurate inverse Jacobian transpose method [7]. Numerous of loss calculation methods have been proposed in the literature and can be categorized into pro-rata [8], incremental [9], proportional-sharing [10], and Z-bus loss allocation [11]. The calculation of loss sensitivity is based on the distributed slack buses in the energy control center [6, 11-13]. In the real-time energy markets, LMP or economic dispatch is implemented based on market-based reference, which is an arbitrary slack bus, instead of the distributed slack buses in the traditional energy management system. Meanwhile, the existing loss calculation methods in traditional EMS systems are generally based on the generator slacks or references. Since the units with automatic generation control (AGC) are selected as the distributed slacks, and the patterns or status of AGC units are variable for the different time periods in the real time energy market, the sensitivity values will keep changing, which complicates the issue. This chapter presents a fast and useful formula to calculate loss sensitivity for any slack bus [14]. The simultaneous feasibility test (SFT) performs the network sensitivity analysis under the base case and contingency cases in the power system. The base case and post-contingency MW flows are compared against their respective limits to generate the set of critical constraints. For each critical constraint, SFT calculates constraint coefficients (shift factors) that represent linearized sensitivity factors between the constrained quantity (e.g. MW branch flow) and MW injections at network buses. The B-matrix used to calculate the shift factors is constructed to reflect proper network topology.
Sensitivity Calculation in Real Time Transmission Network and Energy Markets 1201 The objective of SFT is to identify whether or not network operation is feasible for a real power injection scenario. If operational limits are violated, generic constraints are generated that can be used to prevent the violation if presented with the same network conditions. In the energy market systems, the trade is often considered between the source and the sink (i.e., the point of resource, POR and point of demand, POD). The source and the sink may be an area or any bus group. Therefore, the area based sensitivities are needed, which can be computed through the constraint shift factors within area. Voltage sensitivity analysis can detect the weak buses/nodes in the power system where the voltage is low. It can be used to select the optimal locations of VAR support service [1520]. According to the sensitivity values – voltage benefit factor (VBF) and loss benefit factor (LBF), a ranking of VAR support sites can also be obtained. This chapter presents the implementation details of the several sensitivities calculations in the practical transmission network and energy markets. Section 2 describes the calculation of the market-based loss sensitivities. Section 3 describes the implementation of SFT and the calculation of the constraint’s shift factors. Section 4 describes the calculation of the voltage sensitivity. Section 5 shows the simulation results of the above-mentioned sensitivities.
II. LOSS SENSITIVITY CALCULATION This section presents a fast and useful formula to calculate loss sensitivity for any slack bus. The formula is based on the loss sensitivity results from the distributed slacks without computing a new set of sensitivity factors through the traditional power flow calculation. Especially, the loads are selected as the distributed slacks rather than the usual generator slacks. The loss sensitivity values will be the same for the same network topology no matter how the status of the AGC units changes. In the energy market, the formulation of the optimum economic dispatch can be represented as follow:
Min F = ∑ C j Pj
j ∈ NG
(1)
j ∈ NG
(2)
j
such that
s.t.
∑P
∑S
D
ij
+ PL = ∑ PGj
Pj ≤ Pi max
j
j ∈ NG , i ∈ K max
(3)
j
PGj min ≤ PGj ≤ PGj max where PD: The real power load.
j ∈ NG
(4)
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Pimax: PGj: PGjmin: PGjmax: PL: Sij: Cj : Kmax: NG:
The maximum requirement of power supply at the active constraint i. The real power output at generator bus j. The minimal real power output at generator j. The maximal real power output at generator j. The network losses. The sensitivity (shift factor) for resource or unit j and active constraint i with respect to the market-based reference. The real time price for the resource (or unit) j. The maximum number of active constraints. The number of units.
The Lagrangian function is obtained from equations (1) and (2).
FL = ∑ f i ( PDi ) + λ (∑ PDi + PL − ∑ PGj ) i
i
(5)
j
Traditionally, generation reference (single or distributed slack) is used in the calculation of loss allocation. This works, but may be inconvenient or confusing for the users who frequently use the loss factors. The reason is that the AGC status or patterns of units are variable in the real time EMS or energy markets. The loss sensitivity values based on the distributed unit references will keep changing due to the change of unit AGC status. Thus, the distributed load slack or reference is used here. The optimality criteria of the Lagrangian function (5) are written as follow:
⎛ ∂FL ∂P ⎞ df = i + λ ⎜⎜1 + L ⎟⎟ = 0 i ∈ ND ∂PDi dPDi ⎝ ∂PDi ⎠ ⎞ ⎛ ∂P df ∂FL = i + λ ⎜ L − 1⎟ = 0 j ∈ NG ⎟ ⎜ ∂P ∂PGj dPGj ⎠ ⎝ Gj df i LDi = λ i ∈ ND dPDi
LDi = −
1 ∂P 1+ L ∂PDi
df i LGj = λ dPGj
(6)
(7)
(8)
i ∈ ND
(9)
j ∈ NG
(10)
Sensitivity Calculation in Real Time Transmission Network and Energy Markets 1203
LGj =
1 ∂P 1− L ∂PGj
j ∈ NG
(11)
where, λ:
the Lagrangian multiplier.
∂PL : ∂PDi
the loss sensitivity with respect to load at bus i.
∂PL : ∂PGj
the loss sensitivity with respect to unit at bus j.
We use both
∂PL , which is the loss sensitivity with respect to an injection at bus i, stand for ∂Pi
∂PL ∂PL and . Since the distributed slack buses are used here, all loss sensitivity ∂PDi ∂PGj
factors are non-zero. If an arbitrary slack bus, k, is selected, then Pk is the function of the other injections, i.e.
Pk = f ( Pi )
i ∈ n, i ≠ k
(12)
where n is the total number of buses in the system, and Pi is the power injection at bus i, which includes the load PDi and generation PGj. Actually, the load can be treated as a negative generation. Then equation (9) and (11) can be expressed as (13), and equation (8) and (10) can be expressed as (14).
Li =
1 ∂P 1− L ∂Pi
i∈n
df i Li = λ dPi
i∈n
(13)
(14)
Equation (2) will be rewritten as
PL = Pk + ∑ Pi i≠k
i∈n
(15)
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Jizhong Zhu
The new Lagrangian function can be obtained from (1) and (15).
FL* = ∑ f i ( Pi ) + λ ( PL − Pk − ∑ Pi )
(16)
i≠n
i
The optimality criteria can be obtained from the Lagrangian function (16).
⎛ ∂P ∂P ⎞ ∂FL* df i df k ∂Pk + λ ⎜⎜ L − k − 1⎟⎟ = 0 i∈n, i≠k = + ∂Pi dPi dPk ∂Pi ⎝ ∂Pi ∂Pi ⎠
(17)
From (15), we get
∂PL ∂P =1+ k ∂Pi ∂Pi
(18)
From (17) and (18), we get
df i * df k Li = dPk dPi L*i =
1 ∂P 1− L ∂Pi
(19)
i ∈ n, i ≠ k
(20)
It is noted that Li and Li* are similar, but they have different meaning [14]. The former is based on the distributed slack buses, and the latter is based on an arbitrary slack bus k. Similarly, the loss sensitivity in Li is based on the distributed slack, i.e.
∂PL ∂Pi
(The DS
subscript DS means the distributed slack); the loss sensitivity in Li* is based on an arbitrary single slack bus k, i.e.
∂PL . Note that the k-th loss sensitivity, with bus k as the slack bus, is ∂Pi k
zero. From (14) and (19), we have the following equation.
L*i =
Li , L*k = 1 Lk
(21)
Sensitivity Calculation in Real Time Transmission Network and Energy Markets 1205 From the above equations (13), (20) and (21), we get
1 ∂P 1− L ∂Pi
1−
∂PL ∂Pk
DS
∂P 1− L ∂Pi
DS
1− = k
∂PL = ∂Pi k
∂PL ∂Pi
DS
∂P 1− L ∂Pk
DS
1−
(22)
(23)
Hence, with one set of the incremental transmission loss coefficients for the distributed slack buses, the loss sensitivity for an arbitrary slack bus can be calculated from the following formula.
∂PL = ∂Pi k
∂PL ∂Pi
− DS
∂PL ∂Pk
∂P 1− L ∂Pk
DS
(24)
DS
The formula of loss sensitivity calculation is very simple, but is accurate and efficient for real-time energy markets. It will avoid computing a new set of the loss sensitivity factors whenever the slack bus k changes. Consequently, it means huge time savings. In addition, the loss factors based on the distributed load reference will not be changed no matter how the AGC statuses of units vary, as long as network topology is the same as before.
III. IMPLEMENTATION OF SFT The objective of SFT is to identify whether or not network operation is feasible for a real power injection scenario. If operational limits are violated, generic constraints and the corresponding sensitivities (the shift factors) are generated, which can be used to prevent the violation if presented with the same network conditions. Meanwhile, the shift factors can also be used in the generation scheduling or economic dispatch to alleviate the overload of transmission lines. The SFT calculations include the contingency analysis (CA), in which the decoupled power flow (DPF) or DC power flow is used. The set of component changes that can be analyzed include transmission line, transformer, circuit breaker, load demand and generator
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Jizhong Zhu
outages. SFT informs the user of contingencies that could cause conditions violating operating limits. These limits include branch overloads, abnormal voltages, and voltage angle differences across specified parts of the network. SFT reports the sensitivity (shift factor) of the constraint with respect to the controls. These controls include unit MW control, phase shifter, and load MW control.
3.1. Unit MW Control The unit MW control is the most efficient and cheap control among these available controls. The formulation of sensitivity for unit can be written as follows.
S ij =
∂ Ki ∂Uj
i = 1,......, K max ,
j = 1,......U max
(25)
where, Sij: Ki: Uj: Kmax: Umax:
The sensitivity of the constraint i to the unit MW control j. The constraint i. The unit MW control j. The maximum number of constraints. The maximum number of generator unit MW controls.
3.2. Phase Shifter Control The phase shifter is another efficient control among these available controls. There are some assumptions for phase shifter in the SFT design. The phase shifter control variable is tap number. Normally tap number is an integer, but it can be handled as a real number in the practical SFT calculation. In addition, all opened phase shifters will be skipped over, that is, the sensitivity for the phase shifter that is open at any end will not be calculated. The step on the tap-type is the sensitivity of angle with respect to tap number. The formulation of sensitivity for phase shifter can be written as follows.
Sijp =
∂ Ki ∂ PS jp
i = 1,......, K max ,
jp = 1,......PSmax
where, Sijp: Ki: PSjp: Kmax: PSmax:
The sensitivity of the constraint i to the phase shifter control jp. The constraint i. The phase shifter control jp. The maximum number of constraints. The maximum number of phase shifter controls.
(26)
Sensitivity Calculation in Real Time Transmission Network and Energy Markets 1207 It is noted that there is a special “branch in constraint” logic that must be implemented when the phase shifter branch itself is in the constraint. Basically the artificial flow through transformer branch must be subtracted from constraint flow.
3.3. Load MW Control The load MW control should be last control when other controls are not available. The formulation of sensitivity for load MW control can be written as follows. S ijd = −
∂ Ki ∂ LD jd
i = 1,......, K max ,
jd = 1,...... LD max
(27)
where, Sijd: Ki: LDjd: Kmax: LDmax:
The sensitivity of the constraint i to the load MW control jd. The constraint i. The load MW control jd. The maximum number of constraints. The maximum number of load MW controls in whole system.
It is noted that the sensitivity sign for load MW control is negative. The reason is that increasing load will cause more serious constraint violation, rather than reduce the constraint violation. According to the sensitivity relationship between the constraint and the load MW control, it is needed to reduce / shed load for alleviating or deleting the constraint violation.
3.4. Constraint Value For each constraint, constraint value (DC value) is computed from the control values multiplied by sensitivities. The formulation can be written as follows.
DCVAL i =
U max
∑ VAL _ U j =1
j
* S ij
(28)
where, DCVALi: VAL_Uj: Sij: Umax:
The constraint value for the constraint i. The value of control j. Here, controls including unit MW control, phase shifter and load MW control. The sensitivity or shift factor of the constraint i to the control j. The maximum number of controls.
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Jizhong Zhu
The shift factors computed in SFT is based on the reference bus in EMS topology, but it can be easily converted to any market-based reference. Let k be market-based reference unit, and the shift factor of the constraint i with respect to any unit j that is obtained based on EMS reference bus is Sij. For unit k, the shift factor of the constraint i is Sik. Then, the shift factors after converting to market-based reference unit k can be computed as follows.
S ik ' = 0
i = 1,......, K max
S ij ' = S ij − S ik
i = 1,......, K max ,
(29)
j≠k
(30)
where, S’ij: The shift factor of the constraint i with respect to unit j that is based on the marketbased reference k. S’ik: The shift factor of the constraint i with respect to unit k that is based on the marketbased reference k. Let PFj be the participation factor of unit j, and the shift factor of the constraint i with respect to any unit j is Sij. For area A, the area based shift factor of the constraint i is SiA, which can be computed as follows.
S iA =
∑ (PF S ) j∈ A
j
∑ PF j∈ A
ij
i = 1,......, K max ,
j∈ A
(31)
j
where, SiA: PFj:
The area based shift factor of the constraint i. The participation factor of the unit j.
As we know that the shift factor of the constraint is related to the selected reference, i.e., the value of shift factor will be different if the reference is different even the system topology and conditions are the same. Sometimes the system operators would like to have the stable shift factor values without caring about the selection of reference bus/unit. Thus, the distributed load reference will be used to get the unique constraint shift factors if the system topology and conditions are unchanged. Let Sildref be the sensitivity of load distribution reference for the constraint i, and the shift factor of the constraint i with respect to any control j that is obtained based on EMS reference bus is Sij. Then, the shift factors based on the load distribution reference LDREF can be computed as follows.
Sij ' = Sij − Sildref
i = 1,......,Kmax
(32)
Sensitivity Calculation in Real Time Transmission Network and Energy Markets 1209 where Sildref: the sensitivity of load distribution reference for the constraint i, that is, LDmax
∑ (S
ijd jd =1 LDmax
Sildref =
∗ LDjd )
∑ LD jd =1
i = 1,......, Kmax
(33)
jd
In the practical energy markets such as independent system operator (ISO), the system consists of many areas but one is a major area in the ISO system that is called the internal area, and others are called as external areas. If the internal area is major concerned during the price calculation for this market system, the load distribution reference can be selected based on the internal area only. Similarly, Let LDAmax be the total number of load controls in the internal area of ISO system, which is less than the total number of load controls in whole ISO system LDmax. The shift factors based on the area load distribution reference LDAREF can be computed as follows.
Sij ' = Sij − Sildaref
i = 1,......,Kmax
(34)
where Sildaref: the sensitivity of load distribution reference in area A for the constraint i, that is, LDAmax
S ildaref =
∑ (S jd =1
ijd
i = 1,......, K max LDAmax ∈ LDmax
LDAmax
∑ LD jd =1
LDAmax:
∗ LD jd ) (35)
jd
The maximum number of load MW controls in area A.
IV. VOLTAGE SENSITIVITY ANALYSIS The purpose of the voltage sensitivity analysis is to improve the voltage profile and to minimize system real power losses through the optimal VAR control. These goals are achieved by proper adjustments of VAR variables in power networks. Therefore, if the voltage magnitude at generator buses, VAR compensation (VAR support) and transformer tap position are chosen as the control variables, the optimal VAR control model can be represented as:
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Jizhong Zhu min PL(QS, VG, T)
(36)
such that Q(QS, VG, T, VD) = 0
(37)
QGmin ≤ QG(QS, VG, T) ≤ QGmax
(38)
VDmin ≤ VD(QS, VG, T) ≤ VDmax
(39)
QSmin ≤ QS ≤ QSmax
(40)
VGmin ≤ VG ≤ VGmax
(41)
Tmin ≤ T ≤ Tmax
(42)
where VG: QS: QG: T: VD:
the voltage magnitude at generator buses. the VAR support in the system. the VAR generation in the system. the tap position of the transformer. the voltage magnitude at load buses
Two kinds of sensitivity-related factors can be computed through (36) – (42). Here they are called as voltage benefit factors (VBF) and loss benefit factors (LBF), which are expressed as follows.
LBFi =
VBFi =
∑
( PL 0 − PL (Qsi ))
i
Qsi
∑
(Vi (Q si ) − Vi 0 )
i
Qsi
× 100% i ∈ ND
× 100% i ∈ ND
(43) (44)
where Qsi: LBFi: VBFi: PL0: PL(Qsi): Vi0:
the amount of VAR support at the load bus i. the loss benefit factors from the VAR compensation Qsi . the voltage benefit factors from the VAR compensation Qsi . power transmission losses in the system without VAR compensation. the power transmission losses in the system with VAR compensation Qsi. the voltage magnitude at load bus i without VAR compensation.
Sensitivity Calculation in Real Time Transmission Network and Energy Markets 1211 Vi(Qsi): ND:
the voltage magnitude at load bus i with VAR compensation Qsi. the number of load buses.
V. SIMULATION RESULTS The calculation results of the several sensitivities are illustrated using the IEEE 14 bus system and AREVA T&D 60-bus system. The one-line diagram of the AREVA T&D 60-bus system is shown in Figure 1. The 60-bus system, which has three areas, consists of 24 generation units (15 units are available in the tests), 32 loads, 43 transmission lines and 54 transformers. CHENAUX
CHFALLS
ECAR
NANTCOKE
MARTDALE
BRIGHTON
HUNTVTIL
CEYLON
RICHVIEW
MITCHELL KINCARD
REDBRIDG
HEARN HANDOVER PICTON PARKHILL M’TOWN HOLDEN
STRATFRO LAKEVIEW
J’VILLE
WEST COBDEN
B’VILLE
EAST DOUGLAS
GOLDEN
STINSON
W’VILLE WALDEN
Figure 1. One-line diagram of AREVA T&D system (Area 1 - EAST, Area 2 - WEST, Area 3 – ECAR).
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The following test cases are used to analyze the loss sensitivity in this chapter: Case 1: Case 2:
Case 3:
Case 4: Case 5:
Case 6:
Calculate loss sensitivities using the distributed generation slack and load slack, respectively. All units have AGC on. Calculate loss sensitivities using the distributed generation slack and load slack, respectively. All units have AGC on except the units under station Douglas in Area 1 Calculate loss sensitivities using the distributed generation slack and load slack, respectively. All units have AGC on except the units under station HEARN in Area 1 Calculate loss sensitivities using the distributed generation slack and load slack, respectively. All units have AGC on except the units in Area 2 Calculate loss sensitivities using the distributed generation slack and load slack, respectively. All units have AGC on except the units under station HOLDEN in Area 3 Calculate loss sensitivities for the selected single slack based on the loss factors under the distributed slack.
The simulation results are shown in Table 1–6. All loss sensitivity factors for units and loads are computed. In order to reduce the length of the chapter, only loss sensitivities of generators are listed in Table 1–6, in which column 1 is the name of station and units. Column 2 is the area number that the unit belongs to. Column 3 is the AGC status of the unit. Tables 1–5 are the test results and comparison of loss sensitivity calculation based on the distributed generation reference and distributed load reference, respectively. The loss factors computed from the distributed unit reference are listed in column 4 of Table 1–5. The loss factors computed from the distributed load reference are listed in column 5 of Table 1–5. Generally, the values of loss sensitivities based on the generation reference are different from those based on the load reference, because the distribution of the units is not exactly the same as the distribution of loads in the power system. The loss factors will be close or equal if the units are close to the load locations. This can be observed from Table 1, where all units are on AGC status. For the 60-bus system, each load in area 3 has at least one unit connected, so the loss factors in area 3 are the same for both the distributed generation slack and distributed load slack. It is noted that from Table 1 – 5 that the loss sensitivity factors based on the distributed load slack are the same whether the status of the units is changed or not. But the loss factors based on the distributed generation references are changed since the AGC status of the units are different. Generally, the change of AGC status of the units only affects the loss sensitivities in the same area that these units belong to. It can be seen from Table 2 – 3 that, when AGC status of the units in area 1 changes, only the loss factors in area 1 is affected. The loss factors in the other areas are unchanged. For Table 5, when AGC status of the units in area 3 changes, only the loss factors in area 3 is affected. The loss factors in the other areas are unchanged. But for Table 4, when AGC status of the units in area 2 changes and all units in this area are not on AGC, it means that there is no unit reference in area 2. Then the units with AGC on in the other areas will pick up the
Sensitivity Calculation in Real Time Transmission Network and Energy Markets 1213 mismatch (i.e. area 1 in this case). Thus, the loss factors in area1 and 2 are changed. The loss factors in the other areas are unchanged. Table I. Test Results and Comparison of Loss Sensitivity Calculation (Case 1: All units on AGC)
Station, Generator
Area No.
AGC Unit
DOUGLAS, G2 DOUGLAS, G1 DOUGLAS, CT1 DOUGLAS, CT2 DOUGLAS, ST HEARN, G1 HEARN, G2 LAKEVIEW, G1 BVILLE, 1 WVILLE, 1 CHENAUX, 1 CHEALLS, 1 CHEALLS, 2 HOLDEN, 1 NANTCOKE, 1
1 1 1 1 1 1 1 1 2 2 3 3 3 3 3
YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES
Loss Sensitivity Distributed generation Slack 0.015100 0.012100 0.009900 0.009900 0.009700 -0.016500 -0.016500 -0.018800 -0.001000 0.000700 -0.008900 0.021200 0.021200 0.001000 -0.012200
Loss Sensitivity Distributed load Slack 0.017000 0.014000 0.011800 0.011800 0.011600 -0.014600 -0.014600 -0.017000 -0.004200 -0.002500 -0.008900 0.021200 0.021200 0.001000 -0.012200
Table II. Test Results and Comparison of Loss Sensitivity Calculation (Case 2: All units on AGC except the units under station Douglas in Area 1)
Station, Generator
Area No.
DOUGLAS, G2 DOUGLAS, G1 DOUGLAS, CT1 DOUGLAS, CT2 DOUGLAS, ST HEARN, G1 HEARN, G2 LAKEVIEW, G1 BVILLE, 1 WVILLE, 1 CHENAUX, 1 CHEALLS, 1 CHEALLS, 2 HOLDEN, 1 NANTCOKE, 1
1 1 1 1 1 1 1 1 2 2 3 3 3 3 3
AGC Unit NO NO NO NO NO YES YES YES YES YES YES YES YES YES YES
Loss Sensitivity Distributed generation Slack 0.032800 0.029900 0.027800 0.027800 0.027600 0.001500 0.001500 -0.000800 -0.001000 0.000700 -0.008900 0.021200 0.021200 0.001000 -0.012200
Loss Sensitivity Distributed load Slack 0.017000 0.014000 0.011800 0.011800 0.011600 -0.014600 -0.014600 -0.017000 -0.004200 -0.002500 -0.008900 0.021200 0.021200 0.001000 -0.012200
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Jizhong Zhu Table III. Test Results and Comparison of Loss Sensitivity Calculation (Case 3: Only units under HEARN in Area 1 not on AGC)
Station, Generator
Area No.
AGC Unit
DOUGLAS, G2 DOUGLAS, G1 DOUGLAS, CT1 DOUGLAS, CT2 DOUGLAS, ST HEARN, G1 HEARN, G2 LAKEVIEW, G1 BVILLE, 1 WVILLE, 1 CHENAUX, 1 CHEALLS, 1 CHEALLS, 2 HOLDEN, 1 NANTCOKE, 1
1 1 1 1 1 1 1 1 2 2 3 3 3 3 3
YES YES YES YES YES NO NO YES YES YES YES YES YES YES YES
Loss Sensitivity Distributed generation Slack 0.012600 0.009600 0.007400 0.007400 0.007200 -0.019000 -0.019000 -0.021300 -0.001000 0.000700 -0.008900 0.021200 0.021200 0.001000 -0.012200
Loss Sensitivity Distributed load Slack 0.017000 0.014000 0.011800 0.011800 0.011600 -0.014600 -0.014600 -0.017000 -0.004200 -0.002500 -0.008900 0.021200 0.021200 0.001000 -0.012200
Table IV. Test Results and Comparison of Loss Sensitivity Calculation (Case 4: All units on AGC except the units in Area 2)
Station, Generator
Area No.
AGC Unit
DOUGLAS, G2 DOUGLAS, G1 DOUGLAS, CT1 DOUGLAS, CT2 DOUGLAS, ST HEARN, G1 HEARN, G2 LAKEVIEW, G1 BVILLE, 1 WVILLE, 1 CHENAUX, 1 CHEALLS, 1 CHEALLS, 2 HOLDEN, 1 NANTCOKE, 1
1 1 1 1 1 1 1 1 2 2 3 3 3 3 3
YES YES YES YES YES YES YES YES NO NO YES YES YES YES YES
Loss Sensitivity Distributed generation Slack 0.015200 0.012200 0.010000 0.010000 0.009900 -0.016700 -0.016700 -0.019100 -0.021000 -0.019300 -0.008900 0.021200 0.021200 0.001000 -0.012200
Loss Sensitivity Distributed load Slack 0.017000 0.014000 0.011800 0.011800 0.011600 -0.014600 -0.014600 -0.017000 -0.004200 -0.002500 -0.008900 0.021200 0.021200 0.001000 -0.012200
Sensitivity Calculation in Real Time Transmission Network and Energy Markets 1215 Table V. Test Results and Comparison of Loss Sensitivity Calculation (Case 5: All units on AGC except unit 3 under station HOLDEN in Area 3)
Station, Generator DOUGLAS, G2 DOUGLAS, G1 DOUGLAS, CT1 DOUGLAS, CT2 DOUGLAS, ST HEARN, G1 HEARN, G2 LAKEVIEW, G1 BVILLE, 1 WVILLE, 1 CHENAUX, 1 CHEALLS, 1 CHEALLS, 2 HOLDEN, 1 NANTCOKE, 1
Area No. 1 1 1 1 1 1 1 1 2 2 3 3 3 3 3
AGC Unit YES YES YES YES YES YES YES YES YES YES YES YES YES NO YES
Loss Sensitivity Distributed generation Slack 0.015100 0.012100 0.009900 0.009900 0.009700 -0.016500 -0.016500 -0.018800 -0.001000 0.000700 -0.008500 0.021600 0.021600 0.001400 -0.011800
Loss Sensitivity Distributed load Slack 0.017000 0.014000 0.011800 0.011800 0.011600 -0.014600 -0.014600 -0.017000 -0.004200 -0.002500 -0.008900 0.021200 0.021200 0.001000 -0.012200
Table VI. Test Results of Loss Sensitivity Calculation (Distributed Slack vs Single Slack)
Station, Generator
AGC Unit
DOUGLAS, G2 DOUGLAS, G1 DOUGLAS, CT1 DOUGLAS, CT2 DOUGLAS, ST HEARN, G1 HEARN, G2 LAKEVIEW, G1 BVILLE, 1 WVILLE, 1 CHENAUX, 1 CHEALLS, 1 CHEALLS, 2 HOLDEN, 1 NANTCOKE, 1
YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES
Loss Sensitivity Distributed Slack 0.017000 0.014000 0.011800 0.011800 0.011600 -0.014600 -0.014600 -0.017000 -0.004200 -0.002500 -0.008900 0.021200 0.021200 0.001000 -0.012200
Loss Sensitivity Single Slack, HOLDEN 1 0.016016 0.013013 0.010811 0.010811 0.010611 -0.015616 -0.015616 -0.018018 -0.005205 -0.003504 -0.009910 0.020220 0.020220 0.000000 -0.013213
Loss Sensitivity Single Slack, Douglas ST 0.005463 0.002428 0.000202 0.000202 0.000000 -0.026507 -0.026507 -0.028936 -0.015985 -0.014265 -0.020741 0.009713 0.009713 -0.010724 -0.024079
Through the above comparisons, it can be observed that the method of the distributed load references for loss sensitivity calculation is superior to that of the distributed generation
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references in the real time energy markets, since the AGC status of the units are changeable in the real time system. The results of loss sensitivity calculation for a single slack, which are computed from the proposed formula (24), are shown in Table 6. Column 3 in Table 6 is the set of the loss sensitivity coefficients for the distributed slack buses. Column 4 in Table 6 is the set of loss sensitivity factors with a single slack bus at the location of HOLDEN 1. Column 5 in Table 6 is the set of loss sensitivity factors with a single slack bus at the location of Douglas. It is noted that all the loss sensitivities are nonzero if the distributed slack is selected. If the single slack is selected, the loss sensitivity of the slack equals zero. Since the loss sensitivity values based on the distributed slacks from EMS are unchanged as long as the system topology is the same, the loss sensitivities for any market-based single slack can be easily and quickly acquired by use of the loss sensitivity formula (24). Therefore, a large amount of the computations are avoided whenever the loss sensitivities for a marketbased reference are needed in the real time energy markets. Table 7 – 8 are the results of the detected constraint and the corresponding shift factors. The results of one constraint that is branch T525 at Station CHENAUX are listed. Table VII. Example of the Active Constraint (Branch T525 At Station Chenaux) Constraint name Branch T525
Rating (MVA) 1171.4
Actual Flow (MVA) 1542.7
Constraint deviation 371.3
Percent of Violation 131.7
Table VIII. Test Results of SFT (Shift Factors) Calculation for the Active Constraint T525 at Station Chenaux
Station, Generator
Area No.
Unit in Serve
DOUGLAS, G2 DOUGLAS, G1 DOUGLAS, CT1 DOUGLAS, CT2 DOUGLAS, ST HEARN, G1 HEARN, G2 LAKEVIEW, G1 BVILLE, 1 WVILLE, 1 CHENAUX, 1 CHEALLS, 1 CHEALLS, 2 HOLDEN, 1 NANTCOKE, 1
1 1 1 1 1 1 1 1 2 2 3 3 3 3 3
YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES
Shift Factors on EMS Reference at Station DOUGLAS 0.000000 0. 000000 0. 000000 0. 000000 0. 000000 0. 000000 0. 000000 0. 000000 -0.013650 -0.024336 0.617887 0.521795 0. 521795 0.304269 0.291815
Shift Factors on Market Reference at Station HOLDEN -0.304269 -0.304269 -0.304269 -0.304269 -0.304269 -0.304269 -0.304269 -0.304269 -0.317919 -0.328605 0.313618 0. 217526 0.217526 0.000000 -0.012454
Sensitivity Calculation in Real Time Transmission Network and Energy Markets 1217 In Table 8, column 1 is the name of station and units. Column 2 is the area number that the unit belongs to. Column 3 is the AGC status of the unit. Column 4 is the set of the shift factors of the constraint T525 with respect to the units for the EMS-based reference at station DOUGLAS. Column 5 is the shift factors of the constraint T525 with respect to the units for the market-based reference at the location of HOLDEN 1. It is noted that all the shift factors are zero for the units in area 1 for the EMS-based reference since the reference is located in area 1 and all units in area 1 are close to the reference unit. If the market-based slack is selected, the shift factors for the market-based reference can be easily obtained from equations (29) and (30). Table 9 shows the major VAR support sites as well as the corresponding benefit factors LBF and VBF for the IEEE-14 bus system. Table IX. Voltage Sensitivity Analysis Results for IEEE 14 Bus Systems VAR support Site Bus 4 Bus 5 Bus 8 Bus 9 Bus 10 Bus 11 Bus 12 Bus 13
LBFi 0.000376 0.000337 0.002309 0.007674 0.002618 0.007407 0.006757 0.008840
VBFi 0.000855 0.000884 0.001775 0.001989 0.002097 0.002175 0.002268 0.002122
CONCLUSION This chapter presents a practical approach to compute the sensitivities in the practical transmission network and energy markets. The analysis and implementation details of the loss sensitivity, voltage sensitivity, generator constraint shift factor, and area based constraint shift factor are discussed. The chapter also comprehensively discusses how to compute and use the sensitivities under the different references such as the market-based reference, and the energy management system based reference, as well as how to convert the sensitivities based on EMS system reference into the ones based on the market system reference. These sensitivities calculations can be used to determine whether the on-line capacity as indicated in the resource plan is located in the right place on the network to serve the forecasted demand. The proposed approach is tested on IEEE 14-bus system and AREVA T&D 60-bus system. The test results show the reported approaches are very fast, useful and efficient for the practical transmission network and energy markets.
REFERENCES [1]
T.E. Dy-Liyacco, “Control Centers Are Here to Stay,” IEEE Computer Applications in Power, Vol.15, No.4, pp18-23, 2002.
1218 [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15]
[16] [17] [18]
[19] [20]
Jizhong Zhu N. Winser, “FERC's Standard Market Design: the ITC Perspective,” 2002 IEEE PES Summer Meeting, Chicago, IL. July 22 - 26, 2002. A. Ott, “Experience with PJM Market Operation, System Design, and Implementation,” IEEE Trans. on Power Systems, Vol.18, No.2, pp528-534, 2003. D. Kathan, “FERC’s Standard Market Design Proposal,” 2003 ACEEE/CEE National Symposium on Market Transformation, Washington, DC, April 15, 2003. J.Z. Zhu, D. Hwang, and A. Sadjadpour, “The Implementation of Alleviating Overload in Energy Markets,” in Proc. IEEE PES 2007 General Meeting, Tampa, Florida, 2007. L.K. Kirchamayer, Economic Operation of Power Systems, New York: Wiley, 1958. H.W. Dommel, and W.F. Tinney, “Optimal power flow solutions,” IEEE Trans. on PAS, Vol.PAS-87, No.10, pp1866-1876, 1968. M. Ilic, F.D. Galiana, and L. Fink, Power Systems Restructuring: Engineering and Economics. Norwell, MA: Kluwer, 1998. D. Kirschen, R. Allan, and G. Strbac, “Contributions of individual generators to loads and flows,” IEEE Trans. Power Systems, Vol.12, No.1, pp52-60, 1997. F. Schweppe, M. Caramanis, R. Tabors, and R. Bohn, Spot Pricing of Electricity, Norwell, MA: Kluwer, 1988. J. Conejo, F.D. Galiana, and I. Kochar, “Z-Bus loss allocation,” IEEE Trans. Power Systems, Vol.16, No.1, pp105-110, 2001. F.D. Galiana, A.J. Conjeo, and I. Korkar, “Incremental transmission loss allocation under pool dispatch,” IEEE Trans. Power Systems, Vol.17, No.1, pp26-33, 2002. Elgerd, “Electric Energy Systems Theory: An Introduction,” New York: McGraw-Hill, 1982. J.Z. Zhu, D. Hwang, and A. Sadjadpour, “Loss Sensitivity Calculation and Analysis,” in Proc. 2003 IEEE General Meeting, Toronto, July 13-18, 2003. J.Z. Zhu and M.R. Irving, “Combined Active and Reactive Dispatch with Multiple Objectives using an Analytic Hierarchical Process,” IEE Proc. C, Vol.143, No.4, pp344-352, 1996. J.Z. Zhu, and J.A. Momoh, “Optimal VAR pricing and VAR placement using analytic hierarchy process,” Electric Power Systems Research, Vol.48, No.1, pp11-17, 1998. M.O. Mansour, and T.M. Abdel-Rahman, “Non-linear VAR Optimization Using Decomposition and Coordination,” IEEE Trans. PAS, Vol. 103, pp. 246-255, 1984. N.H. Dandachi, M.J. Rawlins, O. Alsac, and B. Stott, “OPF for Reactive Pricing Studies on the NGC System,” IEEE Power Industry Computer Applications Conference, PICA’95, Utah, pp. 11-17, May 1995. Alsac and B. Sttot, “Optimal Power Flow with Steady-State Security,” IEEE Trans., PAS, Vol.93, pp745-751, 1974. J.A. Momoh and J.Z. Zhu, “Improved Interior Point Method for OPF Problems,” IEEE Trans. on Power Systems, Vol.14, No.3, pp1114-1120, 1999.
In: Encyclopedia of Energy Research and Policy Editor: A. L. Zenfora, pp. 1219-1250
ISBN: 978-1-60692-161-6 © 2010 Nova Science Publishers, Inc.
Chapter 38
WIDE-AREA MONITORING AND ANALYSIS OF INTER-AREA OSCILLATIONS USING THE HILBERT-HUANG TRANSFORM* A. R. Messinaa, M. A. Andradeb and E. Barocio c a
The Center for Research and Advanced Studies (Cinvestav), Mexico b The Autonomous University of Nuevo León, Mexico c The University of Guadalajara, Mexico
ABSTRACT Many transient processes in power systems involve phenomena that vary in time and space in complicated ways. Comprehensive monitoring of large-scale power systems by means of properly placed time-synchronized phasor measurement units (PMUs) provides the opportunity to analyze and characterize complex inter-area swing dynamics involving all or most of the power system. Wide-area real-time monitoring may prove invaluable in power system dynamic studies by giving a quick assessment of the damping and frequency content of dominant system modes after critical contingencies. Measured data, however, may exhibit quite different dynamics at each system location or exhibit abrupt changes, dynamic irregularities, or be complicated by nonlinear trends or noise. Traditional Fourier and Prony methods for system identification are unable to resolve the localized nature of these processes and hence provide little useful information concerning the nature of noisy, time-varying oscillatory processes. In this chapter, a new method for analyzing the temporal dynamics of nonlinear and non-stationary inter-area oscillations using a local empirical mode decomposition (EMD) method and the Hilbert transform is presented. Two novel algorithms are developed to address nonlinear and non-stationary issues. The first method is a local implementation of the empirical mode decomposition technique. The second is an algorithm to compute the *
A version of this chapter was also published in Leading-Edge Electric Power Research edited by C.M. O’Sullivan published by Nova Science Publishers, Inc. It was submitted for appropriate modifications in an effort to encourage wider dissemination of research.
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A. R. Messina, M. A. Andrade and E. E. Barocio
Hilbert transform using finite impulse response (FIR) filters. By combining these approaches, the method can be used to analyze complex signals for which the conventional assumptions of linearity and stationarity may not apply and can be implemented for on-line estimation of modal damping and frequency using synchronized wide-area measurement systems. The physical mechanism underlying nonlinear time-varying inter-area oscillations is investigated and methods to characterize the observed oscillatory phenomena in terms of physically meaningful modal components are proposed. Emphasis is placed on identifying modal content in the presence of noise and nonlinear trends. Issues concerning the implementation of the method and numerical considerations are also discussed. As specific applications, data obtained from PMU measurements from a real event in the northern systems of the Mexican interconnected system are used to examine the potential usefulness of nonlinear time series analysis techniques to characterize the spatio-temporal characteristics of the observed oscillations and to determine the nature and propagation of the system disturbance. The efficiency and accuracy of the method is demonstrated by comparison to other approaches.
BACKGROUND ON THE HILBERT-HUANG TECHNIQUE Nonlinear, non-stationary behavior plays an important role in a variety of physical processes but it may be hard to identify and quantify. In this section, the combined use of Hilbert spectral analysis and the EMD method to characterize the time evolution of nonlinear, non-stationary processes is discussed.
The Empirical Mode Decomposition Technique The empirical mode decomposition is a time-series analysis method that decomposes a signal, x(t ) , into essentially band-limited components or basis functions, a requirement to get meaningful instantaneous frequencies [1,2], using information from the data itself. The essence of this technique is to identify the basis oscillatory functions by their characteristic time scales and then decompose the signal into a series of temporal modes called intrinsic mode functions (IMFs) given by n
x(t ) =
∑ c (t ) + r (t ), i
(1.1)
i =1
where n is the number of IMF components, and r (t ) is the residue after the n IMF’s have been extracted; the functions ci (t ) are nearly orthogonal and have zero local means. Each IMF is associated with a local, physical time scale and can be amplitude and/or frequency modulated and even non-stationary. The first IMF accounts for the higher frequency oscillations, while each succeeding component accounts for lower average frequencies.
Wide-Area Monitoring and Analysis of Inter-Area Oscillations…
1221
An IMF is defined as a wave in which [1]: (i) in the whole time span of the signal, the number of extremes, namely maxima and minima, and the number of zero crossings must be equal or differ at most by one, and (ii) at any time instant, the mean value of the amplitudes defined by the local maxima and minima, must be zero. In practice, however, only a set of IMFs contain relevant information to system behavior. As a result, we rewrite the basic model in (1.1) in the more useful form [3] p
x(t ) =
n
∑ c (t ) + ∑ c (t ) + r (t ). j
j =1
(1.2)
l
l = p +1
where the terms c j (t ) , j = 1,K , p contain the physical behavior of interest, and the
remaining n − p terms contain uninteresting, non-sinusoidal characteristics.
Given a model of the form (1.2), it is possible to apply Hilbert transform to determine local characteristics of the data. Following the work of Huang et al. [1], the original signal x(t ) can be expressed as the real part of the complex expansion n
x(t ) =
∑ j =1
⎧⎪ c j (t ) + r (t ) = Re ⎨ ⎪⎩
n
∑ j =1
t
A j (t )e ∫0
i ω j ( t ) dt
⎫⎪ ⎬. ⎪⎭
(1.3)
where A j , ω j are the instantaneous amplitude and frequency of the j-th modal component. The IMFs are symmetric, have a unique local frequency, are nearly orthogonal, i.e.
IMFi , IMFj ≈ 0 , for i ≠ j and form a complete basis; the sum of the IMFs equals the original series. Although the HHT technique can be efficiently used to characterize nonlinear, nonstationary oscillations several problems persist: (i) The IMFs are a mix of amplitude and frequency modulated signals. Extracting from these components the underlying dynamics is not easy (ii) Although experience suggest that the extracted IMFs usually represent recognizable physical characteristics of the data, the results are not supported by an underlying physical theory, (iii) Further, some IMFs may have no practical significance in the study of complex multi-component signals. This makes the analysis and interpretation of complex phenomena a difficult task. These basis functions are then processed through Hilbert analysis to obtain magnitude, phase and damping information as a function of time.
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A. R. Messina, M. A. Andrade and E. E. Barocio
The Sifting Process The basic method adopted to extract the IMFs consists of three steps [1,3]: a) Starting with the original signal, x(t ) , set hi (t ) = x(t ) , and extract the local minima and local maxima from hi (t ) , b) Interpolate the local minima and local maxima with a cubic spline to form upper and lower envelopes respectively, and c) Obtain the mean of the envelopes, mi (t ) , and subtract it from hi (t ) to determine a new function hi +1 (t ) = hi (t ) − mi (t ) . The three-step procedure is repeated until
hi +1 (t ) satisfies the criteria of an IMF and then c j (t ) = hi +1 (t ) . This procedure is known as the sifting process. Although this method does not always guarantee a perfect instantaneous frequency over all conditions, the resulting instantaneous frequency is still consistent with the physics of the system under study. As pointed out in [3], an inherent aspect of the EMD is that each IMF represents a simple oscillatory mode as a counterpart of the simple harmonic function. Unlike other approaches, the decomposition of the original signal into intrinsic mode functions uses a direct, and adaptive method, which does not assume any basis. This makes it particularly attractive for the study of general signals. Once the original signal has been decomposed into set of intrinsic mode functions, the Hilbert transform can be applied to the IMF components to construct the energy-timefrequency distribution designated as the Hilbert spectrum. The following sections give a brief review of the Hilbert transform and describe the adaptation of proposed method to produce physically meaningful representations of nonlinear, and non-stationary data.
BACKGROUND: THE ANALYTIC SIGNAL OF GABOR The Hilbert Transform For a given real signal, u (t ) , its Hilbert transform is defined as
v (t ) = −
1
π
P
u (η ) 1 dη = π −∞ η − t
∫
∞
u (η ) dη , −∞ t − η
∫
∞
(1.4)
where P indicates that the Cauchy principal value of the integral is taken as the transform is an improper integral [2]. In a similar way, the Hilbert inverse transform is given by
u (t ) =
1
π
P
v(η ) 1 dη = − P π −∞ η − t
∫
∞
v(η ) . −∞ t − η
∫
∞
(1.5)
Wide-Area Monitoring and Analysis of Inter-Area Oscillations…
1223
These expressions can be written in a more convenient way in the form of convolutions as
1 , πt 1 u (t ) = −v(t ) ∗ . πt v(t ) = u (t ) ∗
(1.6) (1.7)
As shown in (1.6), the Hilbert transform returns a signal v (t ) with the same power as the original u (t ) but phase-shifted at each frequency by −π / 2 . Instead of evaluating the integral in (1.4), it is more practical to obtain the representation in the Gabor domain to take advantage of the analytical properties of the Frequency spectrum [4].
The Analytic Signal The complex helical signal whose imaginary part is the Hilbert transform of the real signal,
ψ (t ) = u (t ) + jv(t ),
(1.8)
is known as the analytic signal [4], where the real part, u (t ) , is the data itself and the imaginary part is given by the Hilbert transform of the signal in (1.4). The term analytic function is used in the sense of a complex function Ψ ( z ) of the complex variable
z = t + jτ . In what follows, we briefly review existing techniques for computing the Hilbert transform, and propose a technique for its local calculation based on finite impulse response (FIR) filters.
CONTINUOUS-TIME ESTIMATION OF THE HILBERT TRANSFORM Existing approaches to the numerical calculation of the Hilbert transform are based on the computation of the analytic signal using the Fourier transform. Details of this technique are given in [5], but a brief outline is provided here. Fourier-based techniques have a global character since they span the whole data range and hence, are not well adapted for characterization of local signal attributes. This limits its application to off-line studies requiring the full data set. Essentially, the practical implementation of the Hilbert transform using these approaches can be achieved by using the following steps [5]:
1224 • •
A. R. Messina, M. A. Andrade and E. E. Barocio Perform a Fourier transform of the data, and set all the Fourier coefficients with negative frequency to zero. Multiply the results by two, and perform and inverse Fourier transform. The result is the complex-valued Hilbert transform.
A major problem with this approach is that the Hilbert transform is a step function in frequency. This behavior can cause undesirable Gibbs’ phenomena resulting in ripples in the Hilbert spectrum at the end of the data set. This, in turn, creates errors in the instantaneous frequencies and amplitudes calculated from the affected regions. In the succeeding sections, a brief description of the method is discussed, followed by the mechanics of deriving the numerical approximations. First, some drawbacks and limitations of the existing frameworks for computation of the Fourier-based Hilbert transform are presented and the alternative algorithms are outlined. A new technique for the local computation of the Hilbert transform and the associated analytic signal is then introduced.
The Continuous-Time Hilbert Transform The analytic signal ψ (t ) associated with the signal x(t ) , is defined by
ψ (t ) = x(t ) + xh (t ).
(1.9)
Taking the Fourier transform of (1.9) with respect to f , gives [5]
⎧2 X ( f ), ⎪ Ψ ( f ) = ⎨ X (0), ⎪ 0, ⎩
for f > 0 for f = 0, for f < 0
where
X( f ) =
∫
∞
x(t )e− j 2π ft dt
−∞
is the Fourier transform of x(t ) . Since x(t ) is real, it is possible to show that its Fourier ∗
transform is complex conjugated and symmetric, i.e. X (− f ) = X ( f ) [2]. Based on these relationships, the analytic signal can be obtained, in continuous time, using the fast Fourier transform as follows: 1. Obtain the N-point FFT of the real signal x(t ) . Compute the Hilbert transform using the expression above. 2. Obtain the Fourier transform of the analytic signal as
Wide-Area Monitoring and Analysis of Inter-Area Oscillations…
⎧ X [0], ⎪ 2 X [m], ⎪ Ψ[m] = ⎨ N ⎪ X [ 2 ], ⎩⎪0,
for m = 0 for 1 ≤ m ≤ for m = N2 for
N 2
N 2
−1
1225
.
+1 ≤ m ≤ N −1
(1.10)
Compute the analytic signal in continuous-time using the N-point FFT inverse of (1.10). While the underlying idea is straightforward, this approach has some drawbacks that make it not too reliable. A further limitation is that it is necessary to use the whole of the signal to obtain instantaneous characteristics. In a variation to existing approaches a new algorithm for the local implementation of the Hilbert transform is proposed that circumvents these limitations and enables to track the temporal evolution of arbitrary signals, on an on-line basis.
REAL-TIME IMPLEMENTATION OF THE HILBERT TRANSFORM Transient signals encountered in power systems and other applications are inherently non-stationary. This section explores approaches to extending Hilbert spectral techniques to analyze the local properties of general non-stationary signals. In this formulation, the Hilbert transform is developed using finite impulse response (FIR) filters whose frequency response is an approximation to the response of an ideal Hilbert transformer. Since the method is based on local information, this technique is well-suited for real-time applications.
The Discrete-Time Hilbert Transform jω
The linear time-invariant discrete-time system whose frequency response H (e ) is given by [6,7]
⎧− j, H (e jω ) = ⎨ ⎩ j,
0 ≤ω
