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Contents
Preface XIII
CHAPTER
1 Market Overview in Electric Power Systems 1
1.1 Introduction 1
1.2 Market Structure and Operation 2
1.2.1 Objective of Market Operation 2
1.2.2 Electricity Market Models 4
1.2.3 Market Structure 5
1.2.4 Power Market Types 9
1.2.5 Market Power 13
1.2.6 Key Components in Market Operation 14
1.3 Overview of the Book 15
1.3.1 Information Forecasting 15
1.3.2 Unit Commitment in Restructured Markets 17
1.3.3 Arbitrage in Electricity Markets 18
1.3.4 Market Power and Gaming 19
1.3.5 Asset Valuation and Risk Management 19
1.3.6 Ancillary Services Auction 19
1.3.7 Transmission Congestion Management and Pricing 19
2 Short-Term Load Forecasting 21
2.1 Introduction 21
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2.1.1 Applications of Load Forecasting 21
2.1.2 Factors Affecting Load Patterns 22
2.1.3 Load Forecasting Categories 23
2.2 Short-Term Load Forecasting with ANN 25
2.2.1 Introduction to ANN 25
2.2.2 Application of ANN to STLF 29
2.2.3 STLF using MATLAB’S ANN Toolbox 31
2.3 ANN Architecture for STLF 33
2.3.1 Proposed ANN Architecture 33
2.3.2 Seasonal ANN 34
2.3.3 Adaptive Weight 36
2.3.4 Multiple-Day Forecast 37
2.4 Numerical Results 38
2.4.1 Training and Test Data 38
2.4.2 Stopping Criteria for Training Process 42
2.4.3 ANN Models for Comparison 43
2.4.4 Performance of One-Day Forecast 45
2.4.5 Performance of Multiple-Day Forecast 51
2.5 Sensitivity Analysis 53
3 Electricity Price Forecasting 57
3.1 Introduction 57
3.2 Issues of Electricity Pricing and Forecasting 60
3.2.1 Electricity Price Basics 60
3.2.2 Electricity Price Volatility 61
3.2.3 Categorization of Price Forecasting 63
3.2.4 Factors Considered in Price Forecasting 64
3.3 Electricity Price Simulation Module 65
3.3.1 A Sample of Simulation Strategies 66
3.3.2 Simulation Example 67
3.4 Price Forecasting Module based on ANN 69
3.4.1 ANN Factors in Price Forecasting 70
3.4.2 118-Bus System Price Forecasting with ANN 72
3.5 Performance Evaluation of Price Forecasting 77
2.5.1 Possible Models 53
2.5.2 Sensitivity to Input Factors 54
2.5.3 Inclusion of Temperature Implicitly 55
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3.5.1 Alternative Methods 77
3.5.2 Alternative MAPE Definition 78
3.6 Practical Case Studies 81
3.6.1 Impact of Data Pre-Processing 82
3.6.2 Impact of Quantity of Training Vectors 84
3.6.3 Impact of Quantity of Input Factors 86
3.6.4 Impact of Adaptive Forecasting 89
3.6.5 Comparison of ANN Method with Alternative Methods 90
3.7 Price Volatility Analysis Module 91
3.7.1 Price Spikes Analysis 91
3.7.2 Probability Distribution of Electricity Price 105
3.8 Applications of Price Forecasting 111
3.8.1 Application of Point Price Forecast to Making
Generation Schedule 111
3.8.2 Application of Probability Distribution of Price to
Asset Valuation and Risk Analysis 112
3.8.3 Application of Probability Distribution of Price to
Options Valuation 112
3.8.4 Application of Conditional Probability Distribution
of Price on Load to Forward Price Forecasting 112
4 Price-Based Unit Commitment 115
4.1 Introduction 115
4.2 PBUC Formulation 117
4.2.1 System Constraints 118
4.2.2 Unit Constraints 118
4.3 PBUC Solution 119
4.3.1 Solution without Emission or Fuel Constraints 120
4.3.2 Solution with Emission and Fuel Constraints 129
4.4 Discussion on Solution Methodology 134
4.4.1 Energy Purchase 134
4.4.2 Derivation of Steps for Updating Multipliers 134
4.4.3 Optimality Condition 137
4.5 Additional Features of PBUC 139
4.5.1 Different Prices among Buses 139
4.5.2 Variable Fuel Price as a Function of Fuel Consumption 140 4.5.3 Application of Lagrangian Augmentation 141
4.5.4 Bidding Strategy based on PBUC 145
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4.6 Case Studies 150
4.7 Conclusions 160
5 Arbitrage in Electricity Markets 161
5.1 Introduction 161
5.2 Concept of Arbitrage 161
5.2.1 What is Arbitrage 161
5.2.2 Usefulness of Arbitrage 162
5.3 Arbitrage in a Power Market 163
5.3.1 Same-Commodity Arbitrage 163
5.3.2 Cross-Commodity Arbitrage 164
5.3.3 Spark Spread and Arbitrage 164
5.3.4 Applications of Arbitrage Based on PBUC 165
5.4 Arbitrage Examples in Power Market 166
5.4.1 Arbitrage between Energy and Ancillary Service 166
5.4.2 Arbitrage of Bilateral Contract 171
5.4.3 Arbitrage between Gas and Power 174
5.4.4 Arbitrage of Emission Allowance 182
5.4.5 Arbitrage between Steam and Power 186
5.5 Conclusions 188
6 Market Power Analysis Based on Game Theory 191
6.1 Introduction 191
6.2 Game Theory 192
6.2.1 An Instructive Example 192
6.2.2 Game Methods in Power Systems 195
6.3 Power Transactions Game 195
6.3.1 Coalitions among Participants 197
6.3.2 Generation Cost for Participants 198
6.3.3 Participant’s Objective 201
6.4 Nash Bargaining Problem 202
6.4.1 Nash Bargaining Model for Transaction Analysis 203
6.4.2 Two-Participant Problem Analysis 204
6.4.3 Discussion on Optimal Transaction and Its Price 206
4.6.1 Case Study of 5-Unit System 150
4.6.2 Case Study of 36-Unit System 154
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6.4.4 Test Results 207
6.5 Market Competition with Incomplete Information 215
6.5.1 Participants and Bidding Information 215
6.5.2 Basic Probability Distribution of the Game 216
6.5.3 Conditional Probabilities and Expected Payoff 217
6.5.4 Gaming Methodology 218
6.6 Market Competition for Multiple Electricity Products 222
6.6.1 Solution Methodology 222
6.6.2 Study System 223
6.6.3 Gaming Methodology 225
6.7 Conclusions 230
7 Generation Asset Valuation and Risk Analysis 233
7.1 Introduction 233
7.1.1 Asset Valuation 233
7.1.2 Value at Risk (VaR) 234
7.1.3 Application of VaR to Asset Valuation in Power Markets 235 7.2 VaR for Generation Asset Valuation 236
7.2.1 Framework of the VaR Calculation 236
7.2.2 Spot Market Price Simulation 238
7.2.3 A Numerical Example 240
7.2.4 A Practical Example 246
7.2.5 Sensitivity Analysis 258
7.3 Generation Capacity Valuation 267
7.3.1 Framework of VaR Calculation 268
7.3.2 An Example 268
7.3.3 Sensitivity Analysis 270
7.4 Conclusions 273
8 Security-Constrained Unit Commitment 275
8.1 Introduction 275
8.2 SCUC Problem Formulation 276
8.2.1 Discussion on Ramping Constraints 280
8.3 Benders Decomposition Solution of SCUC 285
8.3.1 Benders Decomposition 286
8.3.2 Application of Benders Decomposition to SCUC 287
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8.3.3 Master Problem Formulation 287
8.4 SCUC to Minimize Network Violation 290
8.4.1 Linearization of Network Constraints 290
8.4.2 Subproblem Formulation 293
8.4.3 Benders Cuts Formulation 296
8.4.4 Case Study 296
8.5 SCUC Application to Minimize EUE - Impact of Reliability 303 8.5.1 Subproblem Formulation and Solution 303
8.5.2 Case Study 306
8.6 Conclusions 310
9 Ancillary Services Auction Market Design 311
9.1 Introduction 311
9.2 Ancillary Services for Restructuring 313
9.3 Forward Ancillary Services Auction – Sequential Approach 315 9.3.1 Two Alternatives in Sequential Ancillary Services Auction 317 9.3.2 Ancillary Services Scheduling 318
9.3.3 Design of the Ancillary Services Auction Market 320
9.3.4 Case Study 322
9.3.5 Discussions 334
9.4 Forward Ancillary Services Auction – Simultaneous Approach
334
9.4.1 Design Options for Simultaneous Auction of
Ancillary Services 336
9.4.2 Rational Buyer Auction 338
9.4.3 Marginal Pricing Auction 347
9.4.4 Discussions 354
9.5 Automatic Generation Control (AGC) 354
9.5.1 AGC Functions 354
9.5.2 AGC Response 356
9.5.3 AGC Units Revenue Adequacy 357
9.5.4 AGC Pricing 358
9.5.5 Discussions 366
9.6 Conclusions 367
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10 Transmission Congestion Management and Pricing 369
10.1 Introduction 369
10.2 Transmission Cost Allocation Methods 372
10.2.1 Postage-Stamp Rate Method 372
10.2.2 Contract Path Method 373
10.2.3 MW-Mile Method 373
10.2.4 Unused Transmission Capacity Method 374
10.2.5 MVA-Mile Method 376
10.2.6 Counter-Flow Method 376
10.2.7 Distribution Factors Method 376
10.2.8 AC Power Flow Method 379
10.2.9 Tracing Methods 379
10.2.10 Comparison of Cost Allocation Methods 386
10.3 Examples for Transmission Cost Allocation Methods 387
10.3.1 Cost Allocation Using Distribution Factors Method 388
10.3.2 Cost Allocation Using Bialek’s Tracing Method 389
10.3.3 Cost Allocation Using Kirschen’s Tracing Method 391
10.3.4 Comparing the Three Cost Allocation Methods 392
10.4 LMP, FTR, and Congestion Management 393
10.4.1 Locational Marginal Price (LMP) 393
10.4.2 LMP Application in Determining Zonal Boundaries 405
10.4.3 Firm Transmission Right (FTR) 408
10.4.4 FTR Auction 412
10.4.5 Zonal Congestion Management 421
10.5 A Comprehensive Transmission Pricing Scheme 431
10.5.1 Outline of the Proposed Transmission Pricing Scheme 432 10.5.2 Prioritization of Transmission Dispatch 434
10.5.3 Calculation of Transmission Usage and Congestion
Charges and FTR Credits 439
10.5.4 Numerical Example 443
10.6 Conclusions 453
APPENDIX A List of Symbols 455
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B Mathematical Derivation 461
B.1 Derivation of Probability Distribution 461
B.2 Lagrangian Augmentation with Inequality Constraints 462
C RTS Load Data 467
D Example Systems Data 469
D.1 5-Unit System 469
D.2 36-Unit System 472
D.3 6-Unit System 476
D.4 Modified IEEE 30-Bus System 477
D.5 118-Bus System 479
E Game Theory Concepts 483
E.1 Equilibrium in Non-Cooperative Games 483
E.2 Characteristics Function 484
E.3 N-Players Cooperative Games 485
E.4 Games with Incomplete Information 486
F Congestion Charges Calculation 489
F.1 Calculations of Congestion Charges using
Contributions of Generators 489
F.2 Calculations of Congestion Charges using
Contributions of Loads 493
References 495
Index 509
Trang 16Preface
During the last five years, Illinois Institute of Technology in Chicago has been offering a master’s degree program in electricity markets which is
a joint venture between the College of Engineering and the School of Business The subject of this book is currently offered as a required course for students majoring in the master of electricity markets
We believe that the subject of this book will be of interest to power engineering faculty and students, consultants, vendors, manufacturers, researchers, designers, and electricity marketer, who will find a detailed discussion of electricity market tools throughout the book with numerous examples We assume that the readers have a fundamental knowledge of power system operation and control
Much of the topics in this book are based on the presumption that there are two major objectives in establishing an electricity market: ensuring a secure operation and facilitating an economical operation Security is the most important aspect of the power system operation be it a regulated operation or a restructured power market In a restructured power system, security could be ensured by utilizing the diverse services available
to the market The economical operation facilitated by the electricity market is believed to help reduce the cost of electricity utilization, which is
a primary motive for restructuring and a way to enhance the security of a power system through its economics To accomplish these objectives, proper market tools must be devised and efficient market strategies must be employed by participants based on power system requirements
The topics covered by this book discuss certain tools and procedures that are utilized by the ISO as well as GENCOs and TRANSCOs These topics include electricity load and price forecasting, security-constrained unit commitment and price-based unit commitment, market power and monitoring, arbitrage in electricity markets, generation asset valuation and risk analysis, auction market design for energy and ancillary services, as well as transmission congestion management and pricing For instance,