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Summary
Summary
An essential overview of post-deregulation market operations inelectrical power systems
Until recently the U.S. electricity industry was dominated byvertically integrated utilities. It is now evolving into adistributive and competitive market driven by market forces andincreased competition. With electricity amounting to a $200 billionper year market in the United States, the implications of thisrestructuring will naturally affect the rest of the world.
Why is restructuring necessary? What are the components ofrestructuring? How is the new structure different from the oldmonopoly? How are the participants strategizing their options tomaximize their revenues? What are the market risks and how are theyevaluated? How are interchange transactions analyzed and approved?Starting with a background sketch of the industry, this hands-onreference provides insights into the new trends in power systemsoperation and control, and highlights advanced issues in thefield.
Written for both technical and nontechnical professionals involvedin power engineering, finance, and marketing, this must-haveresource discusses:
* Market structure and operation of electric power systems
* Load and price forecasting and arbitrage
* Price-based unit commitment and security constrained unitcommitment
* Market power analysis and game theory applications
* Ancillary services auction market design
* Transmission pricing and congestion
Using real-world case studies, this timely survey offers engineers,consultants, researchers, financial managers, university professorsand students, and other professionals in the industry acomprehensive review of electricity restructuring and how itsradical effects will shape the market.
Author Notes
MOHAMMAD SHAHIDEHPOUR is Professor of Electrical and ComputerEngineering at the Illinois Institute of Technology. He is a Fellowof the IEEE and has served as a consultant for major energycompanies during the last twenty years.
HATIM YAMIN, PhD, is with ABB Energy Information Systems, a globalunit of the energy industry worldwide, and has served as a facultymember in the Power Engineering Department at Yarmouk University inJordan.
ZUYI LI, PhD, is with Global Energy Market Solutions, Inc. and hasbeen affiliated with the Electric Power and Power ElectronicsCenter at the Illinois Institute of Technology.
Reviews 1
Choice Review
Shahidehpour (Illinois Institute of Technology) and colleagues from industry have prepared an excellent work, a successful teaching blend of the physics, economics, and statistics required for professionals to perform in today's electric power markets. Readers will be impressed with the comprehensive approach and clear, readable presentation of material that will be read by professionals with applicable experience in one or maybe two of the key disciplines, but rarely with working skills in all three. The book is highly recommended for use in senior undergraduate- and graduate-level university courses open to engineering, business, and government policy students who have career interests in the electric power industry. The volume will serve well also as a resource in online or distance courses by universities or industry training consultants offering continuous education in the changing complexities of profitable electricity market operation. S. R. Walk Maine Maritime Academy
Table of Contents
Preface | p. XIII |
1 Market Overview in Electric Power Systems | p. 1 |
1.1 Introduction | p. 1 |
1.2 Market Structure and Operation | p. 2 |
1.2.1 Objective of Market Operation | p. 2 |
1.2.2 Electricity Market Models | p. 4 |
1.2.3 Market Structure | p. 5 |
1.2.4 Power Market Types | p. 9 |
1.2.5 Market Power | p. 13 |
1.2.6 Key Components in Market Operation | p. 14 |
1.3 Overview of the Book | p. 15 |
1.3.1 Information Forecasting | p. 15 |
1.3.2 Unit Commitment in Restructured Markets | p. 17 |
1.3.3 Arbitrage in Electricity Markets | p. 18 |
1.3.4 Market Power and Gaming | p. 19 |
1.3.5 Asset Valuation and Risk Management | p. 19 |
1.3.6 Ancillary Services Auction | p. 19 |
1.3.7 Transmission Congestion Management and Pricing | p. 19 |
2 Short-Term Load Forecasting | p. 21 |
2.1 Introduction | p. 21 |
2.1.1 Applications of Load Forecasting | p. 21 |
2.1.2 Factors Affecting Load Patterns | p. 22 |
2.1.3 Load Forecasting Categories | p. 23 |
2.2 Short-Term Load Forecasting with ANN | p. 25 |
2.2.1 Introduction to ANN | p. 25 |
2.2.2 Application of ANN to STLF | p. 29 |
2.2.3 STLF using MATLAB'S ANN Toolbox | p. 31 |
2.3 ANN Architecture for STLF | p. 33 |
2.3.1 Proposed ANN Architecture | p. 33 |
2.3.2 Seasonal ANN | p. 34 |
2.3.3 Adaptive Weight | p. 36 |
2.3.4 Multiple-Day Forecast | p. 37 |
2.4 Numerical Results | p. 38 |
2.4.1 Training and Test Data | p. 38 |
2.4.2 Stopping Criteria for Training Process | p. 42 |
2.4.3 ANN Models for Comparison | p. 43 |
2.4.4 Performance of One-Day Forecast | p. 45 |
2.4.5 Performance of Multiple-Day Forecast | p. 51 |
2.5 Sensitivity Analysis | p. 53 |
2.4.1 Possible Models | p. 53 |
2.4.2 Sensitivity to Input Factors | p. 54 |
2.4.3 Inclusion of Temperature Implicitly | p. 55 |
3 Electricity Price Forecasting | p. 57 |
3.1 Introduction | p. 57 |
3.2 Issues of Electricity Pricing and Forecasting | p. 60 |
3.2.1 Electricity Price Basics | p. 60 |
3.2.2 Electricity Price Volatility | p. 61 |
3.2.3 Categorization of Price Forecasting | p. 63 |
3.2.4 Factors Considered in Price Forecasting | p. 64 |
3.3 Electricity Price Simulation Module | p. 65 |
3.3.1 A Sample of Simulation Strategies | p. 66 |
3.3.2 Simulation Example | p. 67 |
3.4 Price Forecasting Module based on ANN | p. 69 |
3.4.1 ANN Factors in Price Forecasting | p. 70 |
3.4.2 118-Bus System Price Forecasting with ANN | p. 72 |
3.5 Performance Evaluation of Price Forecasting | p. 77 |
3.5.1 Alternative Methods | p. 77 |
3.5.2 Alternative MAPE Definition | p. 78 |
3.6 Practical Case Studies | p. 81 |
3.6.1 Impact of Data Pre-Processing | p. 82 |
3.6.2 Impact of Quantity of Training Vectors | p. 84 |
3.6.3 Impact of Quantity of Input Factors | p. 86 |
3.6.4 Impact of Adaptive Forecasting | p. 89 |
3.6.5 Comparison of ANN Method with Alternative Methods | p. 90 |
3.7 Price Volatility Analysis Module | p. 91 |
3.7.1 Price Spikes Analysis | p. 91 |
3.7.2 Probability Distribution of Electricity Price | p. 105 |
3.8 Applications of Price Forecasting | p. 111 |
3.8.1 Application of Point Price Forecast to Making Generation Schedule | p. 111 |
3.8.2 Application of Probability Distribution of Price to Asset Valuation and Risk Analysis | p. 112 |
3.8.3 Application of Probability Distribution of Price to Options Valuation | p. 112 |
3.8.4 Application of Conditional Probability Distribution of Price on Load to Forward Price Forecasting | p. 112 |
4 Price-Based Unit Commitment | p. 115 |
4.1 Introduction | p. 115 |
4.2 PBUC Formulation | p. 117 |
4.2.1 System Constraints | p. 118 |
4.2.2 Unit Constraints | p. 118 |
4.3 PBUC Solution | p. 119 |
4.3.1 Solution without Emission or Fuel Constraints | p. 120 |
4.3.2 Solution with Emission and Fuel Constraints | p. 129 |
4.4 Discussion on Solution Methodology | p. 134 |
4.4.1 Energy Purchase | p. 134 |
4.4.2 Derivation of Steps for Updating Multipliers | p. 134 |
4.4.3 Optimality Condition | p. 137 |
4.5 Additional Features of PBUC | p. 139 |
4.5.1 Different Prices among Buses | p. 139 |
4.5.2 Variable Fuel Price as a Function of Fuel Consumption | p. 140 |
4.5.3 Application of Lagrangian Augmentation | p. 141 |
4.5.4 Bidding Strategy based on PBUC | p. 145 |
4.6 Case Studies | p. 150 |
4.5.1 Case Study of 5-Unit System | p. 150 |
4.5.2 Case Study of 36-Unit System | p. 154 |
4.7 Conclusions | p. 160 |
5 Arbitrage in Electricity Markets | p. 161 |
5.1 Introduction | p. 161 |
5.2 Concept of Arbitrage | p. 161 |
5.2.1 What is Arbitrage | p. 161 |
5.2.2 Usefulness of Arbitrage | p. 162 |
5.3 Arbitrage in a Power Market | p. 163 |
5.3.1 Same-Commodity Arbitrage | p. 163 |
5.3.2 Cross-Commodity Arbitrage | p. 164 |
5.3.3 Spark Spread and Arbitrage | p. 164 |
5.3.4 Applications of Arbitrage Based on PBUC | p. 165 |
5.4 Arbitrage Examples in Power Market | p. 166 |
5.4.1 Arbitrage between Energy and Ancillary Service | p. 166 |
5.4.2 Arbitrage of Bilateral Contract | p. 171 |
5.4.3 Arbitrage between Gas and Power | p. 174 |
5.4.4 Arbitrage of Emission Allowance | p. 182 |
5.4.5 Arbitrage between Steam and Power | p. 186 |
5.5 Conclusions | p. 188 |
6 Market Power Analysis Based on Game Theory | p. 191 |
6.1 Introduction | p. 191 |
6.2 Game Theory | p. 192 |
6.2.1 An Instructive Example | p. 192 |
6.2.2 Game Methods in Power Systems | p. 195 |
6.3 Power Transactions Game | p. 195 |
6.3.1 Coalitions among Participants | p. 197 |
6.3.2 Generation Cost for Participants | p. 198 |
6.3.3 Participant's Objective | p. 201 |
6.4 Nash Bargaining Problem | p. 202 |
6.4.1 Nash Bargaining Model for Transaction Analysis | p. 203 |
6.4.2 Two-Participant Problem Analysis | p. 204 |
6.4.3 Discussion on Optimal Transaction and Its Price | p. 206 |
6.4.4 Test Results | p. 207 |
6.5 Market Competition with Incomplete Information | p. 215 |
6.5.1 Participants and Bidding Information | p. 215 |
6.5.2 Basic Probability Distribution of the Game | p. 216 |
6.5.3 Conditional Probabilities and Expected Payoff | p. 217 |
6.5.4 Gaming Methodology | p. 218 |
6.6 Market Competition for Multiple Electricity Products | p. 222 |
6.6.1 Solution Methodology | p. 222 |
6.6.2 Study System | p. 223 |
6.6.3 Gaming Methodology | p. 225 |
6.7 Conclusions | p. 230 |
7 Generation Asset Valuation and Risk Analysis | p. 233 |
7.1 Introduction | p. 233 |
7.1.1 Asset Valuation | p. 233 |
7.1.2 Value at Risk (VaR) | p. 234 |
7.1.3 Application of VaR to Asset Valuation in Power Markets | p. 235 |
7.2 VaR for Generation Asset Valuation | p. 236 |
7.2.1 Framework of the VaR Calculation | p. 236 |
7.2.2 Spot Market Price Simulation | p. 238 |
7.2.3 A Numerical Example | p. 240 |
7.2.4 A Practical Example | p. 246 |
7.2.5 Sensitivity Analysis | p. 258 |
7.3 Generation Capacity Valuation | p. 267 |
7.3.1 Framework of VaR Calculation | p. 268 |
7.3.2 An Example | p. 268 |
7.3.3 Sensitivity Analysis | p. 270 |
7.4 Conclusions | p. 273 |
8 Security-Constrained Unit Commitment | p. 275 |
8.1 Introduction | p. 275 |
8.2 SCUC Problem Formulation | p. 276 |
8.2.1 Discussion on Ramping Constraints | p. 280 |
8.3 Benders Decomposition Solution of SCUC | p. 285 |
8.3.1 Benders Decomposition | p. 286 |
8.3.2 Application of Benders Decomposition to SCUC | p. 287 |
8.3.3 Master Problem Formulation | p. 287 |
8.4 SCUC to Minimize Network Violation | p. 290 |
8.4.1 Linearization of Network Constraints | p. 290 |
8.4.2 Subproblem Formulation | p. 293 |
8.4.3 Benders Cuts Formulation | p. 296 |
8.4.4 Case Study | p. 296 |
8.5 SCUC Application to Minimize EUE - Impact of Reliability | p. 303 |
8.5.1 Subproblem Formulation and Solution | p. 303 |
8.5.2 Case Study | p. 306 |
8.6 Conclusions | p. 310 |
9 Ancillary Services Auction Market Design | p. 311 |
9.1 Introduction | p. 311 |
9.2 Ancillary Services for Restructuring | p. 313 |
9.3 Forward Ancillary Services Auction--Sequential Approach | p. 315 |
9.3.1 Two Alternatives in Sequential Ancillary Services Auction | p. 317 |
9.3.2 Ancillary Services Scheduling | p. 318 |
9.3.3 Design of the Ancillary Services Auction Market | p. 320 |
9.3.4 Case Study | p. 322 |
9.3.5 Discussions | p. 334 |
9.4 Forward Ancillary Services Auction--Simultaneous Approach | p. 334 |
9.4.1 Design Options for Simultaneous Auction of Ancillary Services | p. 336 |
9.4.2 Rational Buyer Auction | p. 338 |
9.4.3 Marginal Pricing Auction | p. 347 |
9.4.4 Discussions | p. 354 |
9.5 Automatic Generation Control (AGC) | p. 354 |
9.5.1 AGC Functions | p. 354 |
9.5.2 AGC Response | p. 356 |
9.5.3 AGC Units Revenue Adequacy | p. 357 |
9.5.4 AGC Pricing | p. 358 |
9.5.5 Discussions | p. 366 |
9.6 Conclusions | p. 367 |
10 Transmission Congestion Management and Pricing | p. 369 |
10.1 Introduction | p. 369 |
10.2 Transmission Cost Allocation Methods | p. 372 |
10.2.1 Postage-Stamp Rate Method | p. 372 |
10.2.2 Contract Path Method | p. 373 |
10.2.3 MW-Mile Method | p. 373 |
10.2.4 Unused Transmission Capacity Method | p. 374 |
10.2.5 MVA-Mile Method | p. 376 |
10.2.6 Counter-Flow Method | p. 376 |
10.2.7 Distribution Factors Method | p. 376 |
10.2.8 AC Power Flow Method | p. 379 |
10.2.9 Tracing Methods | p. 379 |
10.2.10 Comparison of Cost Allocation Methods | p. 386 |
10.3 Examples for Transmission Cost Allocation Methods | p. 387 |
10.3.1 Cost Allocation Using Distribution Factors Method | p. 388 |
10.3.2 Cost Allocation Using Bialek's Tracing Method | p. 389 |
10.3.3 Cost Allocation Using Kirschen's Tracing Method | p. 391 |
10.3.4 Comparing the Three Cost Allocation Methods | p. 392 |
10.4 LMP, FTR, and Congestion Management | p. 393 |
10.4.1 Locational Marginal Price (LMP) | p. 393 |
10.4.2 LMP Application in Determining Zonal Boundaries | p. 405 |
10.4.3 Firm Transmission Right (FTR) | p. 408 |
10.4.4 FTR Auction | p. 412 |
10.4.5 Zonal Congestion Management | p. 421 |
10.5 A Comprehensive Transmission Pricing Scheme | p. 431 |
10.5.1 Outline of the Proposed Transmission Pricing Scheme | p. 432 |
10.5.2 Prioritization of Transmission Dispatch | p. 434 |
10.5.3 Calculation of Transmission Usage and Congestion Charges and FTR Credits | p. 439 |
10.5.4 Numerical Example | p. 443 |
10.6 Conclusions | p. 453 |
Appendix | |
A List of Symbols | p. 455 |
B Mathematical Derivation | p. 461 |
B.1 Derivation of Probability Distribution | p. 461 |
B.2 Lagrangian Augmentation with Inequality Constraints | p. 462 |
C RTS Load Data | p. 467 |
D Example Systems Data | p. 469 |
D.1 5-Unit System | p. 469 |
D.2 36-Unit System | p. 472 |
D.3 6-Unit System | p. 476 |
D.4 Modified IEEE 30-Bus System | p. 477 |
D.5 118-Bus System | p. 479 |
E Game Theory Concepts | p. 483 |
E.1 Equilibrium in Non-Cooperative Games | p. 483 |
E.2 Characteristics Function | p. 484 |
E.3 N-Players Cooperative Games | p. 485 |
E.4 Games with Incomplete Information | p. 486 |
F Congestion Charges Calculation | p. 489 |
F.1 Calculations of Congestion Charges using Contributions of Generators | p. 489 |
F.2 Calculations of Congestion Charges using Contributions of Loads | p. 493 |
References | p. 495 |
Index | p. 509 |