<br/><p><font color="#800080">Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management </font></p><p><img src="http://ec1.images-amazon.com/images/I/41BEX46K77L.jpg" border="0" alt=""/></p><p>By M. Shahidehpour, H. Yamin, Zuyi Li,</p><p>Publisher:   Wiley-IEEE Press<br/>Number Of Pages:   450<br/>Publication Date:   2002-03-28<br/>Sales Rank:   205818<br/>ISBN / ASIN:   0471443379<br/>EAN:   9780471443377<br/>Binding:   Hardcover<br/>Manufacturer:   Wiley-IEEE Press<br/>Studio:   Wiley-IEEE Press<br/>Average Rating:   4.5<br/>Total Reviews:   3<br/></p><p><br/>--------------------------------------------------------------------------------</p><p><br/>Book Description: </p><p>An essential overview of post-deregulation market operations in electrical power systems</p><p>Until recently the U.S. electricity industry was dominated by vertically integrated utilities. It is now evolving into a distributive and competitive market driven by market forces and increased competition. With electricity amounting to a $200 billion per year market in the United States, the implications of this restructuring will naturally affect the rest of the world.</p><p>Why is restructuring necessary? What are the components of restructuring? How is the new structure different from the old monopoly? How are the participants strategizing their options to maximize their revenues? What are the market risks and how are they evaluated? How are interchange transactions analyzed and approved? Starting with a background sketch of the industry, this hands-on reference provides insights into the new trends in power systems operation and control, and highlights advanced issues in the field.</p><p>Written for both technical and nontechnical professionals involved in power engineering, finance, and marketing, this must-have resource discusses:</p><p>Market structure and operation of electric power systems<br/>Load and price forecasting and arbitrage<br/>Price-based unit commitment and security constrained unit commitment<br/>Market power analysis and game theory applications<br/>Ancillary services auction market design<br/>Transmission pricing and congestion<br/>Using real-world case studies, this timely survey offers engineers, consultants, researchers, financial managers, university professors and students, and other professionals in the industry a comprehensive review of electricity restructuring and how its radical effects will shape the market.</p><p>Contents:<br/>     Preface<br/>     CHAPTER 1 Market Overview in Electric Power Systems<br/>          1.1 Introduction<br/>          1.2 Market Structure and Operation<br/>               1.2.1 Objective of Market Operation<br/>               1.2.2 Electricity Market Models<br/>               1.2.3 Market Structure<br/>               1.2.4 Power Market Types<br/>               1.2.5 Market Power<br/>               1.2.6 Key Components in Market Operation<br/>          1.3 Overview of the Book<br/>               1.3.1 Information Forecasting<br/>               1.3.2 Unit Commitment in Restructured Markets<br/>               1.3.3 Arbitrage in Electricity Markets<br/>               1.3.4 Market Power and Gaming<br/>               1.3.5 Asset Valuation and Risk Management<br/>               1.3.6 Ancillary Services Auction<br/>               1.3.7 Transmission Congestion Management and Pricing<br/>     CHAPTER 2 Short-Term Load Forecasting<br/>          2.1 Introduction<br/>               2.1.1 Applications of Load Forecasting<br/>               2.1.2 Factors Affecting Load Patterns<br/>               2.1.3 Load Forecasting Categories<br/>          2.2 Short-Term Load Forecasting with ANN<br/>               2.2.1 Introduction to ANN<br/>               2.2.2 Application of ANN to STLF<br/>               2.2.3 STLF using MATLAB’S ANN Toolbox<br/>          2.3 ANN Architecture for STLF<br/>               2.3.1 Proposed ANN Architecture<br/>               2.3.2 Seasonal ANN<br/>               2.3.3 Adaptive Weight<br/>               2.3.4 Multiple-Day Forecast<br/>          2.4 Numerical Results<br/>               2.4.1 Training and Test Data<br/>               2.4.2 Stopping Criteria for Training Process<br/>               2.4.3 ANN Models for Comparison<br/>               2.4.4 Performance of One-Day Forecast<br/>               2.4.5 Performance of Multiple-Day Forecast<br/>          2.5 Sensitivity Analysis<br/>               2.5.1 Possible Models<br/>               2.5.2 Sensitivity to Input Factors<br/>               2.5.3 Inclusion of Temperature Implicitly<br/>     CHAPTER 3 Electricity Price Forecasting<br/>          3.1 Introduction<br/>          3.2 Issues of Electricity Pricing and Forecasting<br/>               3.2.1 Electricity Price Basics<br/>               3.2.2 Electricity Price Volatility<br/>               3.2.3 Categorization of Price Forecasting<br/>               3.2.4 Factors Considered in Price Forecasting<br/>          3.3 Electricity Price Simulation Module<br/>               3.3.1 A Sample of Simulation Strategies<br/>               3.3.2 Simulation Example<br/>          3.4 Price Forecasting Module based on ANN<br/>               3.4.1 ANN Factors in Price Forecasting<br/>               3.4.2 118-Bus System Price Forecasting with ANN<br/>          3.5 Performance Evaluation of Price Forecasting<br/>               3.5.1 Alternative Methods<br/>               3.5.2 Alternative MAPE Definition<br/>          3.6 Practical Case Studies<br/>               3.6.1 Impact of Data Pre-Processing<br/>               3.6.2 Impact of Quantity of Training Vectors<br/>               3.6.3 Impact of Quantity of Input Factors<br/>               3.6.4 Impact of Adaptive Forecasting<br/>               3.6.5 Comparison of ANN Method with Alternative Methods<br/>          3.7 Price Volatility Analysis Module<br/>               3.7.1 Price Spikes Analysis<br/>               3.7.2 Probability Distribution of Electricity Price<br/>          3.8 Applications of Price Forecasting<br/>               3.8.1 Application of Point Price Forecast to Making Generation Schedule<br/>               3.8.2 Application of Probability Distribution of Price to Asset Valuation and Risk Analysis<br/>               3.8.3 Application of Probability Distribution of Price to Options Valuation<br/>               3.8.4 Application of Conditional Probability Distribution of Price on Load to Forward Price Forecasting<br/>     CHAPTER 4 Price-Based Unit Commitment<br/>          4.1 Introduction<br/>          4.2 PBUC Formulation<br/>               4.2.1 System Constraints<br/>               4.2.2 Unit Constraints<br/>          4.3 PBUC Solution<br/>               4.3.1 Solution without Emission or Fuel Constraints<br/>               4.3.2 Solution with Emission and Fuel Constraints<br/>          4.4 Discussion on Solution Methodology<br/>               4.4.1 Energy Purchase<br/>               4.4.2 Derivation of Steps for Updating Multipliers<br/>               4.4.3 Optimality Condition<br/>          4.5 Additional Features of PBUC<br/>               4.5.1 Different Prices among Buses<br/>               4.5.2 Variable Fuel Price as a Function of Fuel Consumption<br/>               4.5.3 Application of Lagrangian Augmentation<br/>               4.5.4 Bidding Strategy based on PBUC<br/>          4.6 Case Studies<br/>               4.6.1 Case Study of 5-Unit System<br/>               4.6.2 Case Study of 36-Unit System<br/>          4.7 Conclusions<br/>     CHAPTER 5 Arbitrage in Electricity Markets<br/>          5.1 Introduction<br/>          5.2 Concept of Arbitrage<br/>               5.2.1 What is Arbitrage<br/>               5.2.2 Usefulness of Arbitrage<br/>          5.3 Arbitrage in a Power Market<br/>               5.3.1 Same-Commodity Arbitrage<br/>               5.3.2 Cross-Commodity Arbitrage<br/>               5.3.3 Spark Spread and Arbitrage<br/>               5.3.4 Applications of Arbitrage Based on PBUC<br/>          5.4 Arbitrage Examples in Power Market<br/>               5.4.1 Arbitrage between Energy and Ancillary Service<br/>               5.4.2 Arbitrage of Bilateral Contract<br/>               5.4.3 Arbitrage between Gas and Power<br/>               5.4.4 Arbitrage of Emission Allowance<br/>               5.4.5 Arbitrage between Steam and Power<br/>          5.5 Conclusions<br/>     CHAPTER 6 Market Power Analysis Based on Game Theory<br/>          6.1 Introduction<br/>          6.2 Game Theory<br/>               6.2.1 An Instructive Example<br/>               6.2.2 Game Methods in Power Systems<br/>          6.3 Power Transactions Game<br/>               6.3.1 Coalitions among Participants<br/>               6.3.2 Generation Cost for Participants<br/>               6.3.3 Participant’s Objective<br/>          6.4 Nash Bargaining Problem<br/>               6.4.1 Nash Bargaining Model for Transaction Analysis<br/>               6.4.2 Two-Participant Problem Analysis<br/>               6.4.3 Discussion on Optimal Transaction and Its Price<br/>               6.4.4 Test Results<br/>          6.5 Market Competition with Incomplete Information<br/>               6.5.1 Participants and Bidding Information<br/>               6.5.2 Basic Probability Distribution of the Game<br/>               6.5.3 Conditional Probabilities and Expected Payoff<br/>               6.5.4 Gaming Methodology<br/>          6.6 Market Competition for Multiple Electricity Products<br/>               6.6.1 Solution Methodology<br/>               6.6.2 Study System<br/>               6.6.3 Gaming Methodology<br/>          6.7 Conclusions<br/>     CHAPTER 7 Generation Asset Valuation and Risk Analysis<br/>          7.1 Introduction<br/>               7.1.1 Asset Valuation<br/>               7.1.2 Value at Risk (VaR)<br/>               7.1.3 Application of VaR to Asset Valuation in Power Markets<br/>          7.2 VaR for Generation Asset Valuation<br/>               7.2.1 Framework of the VaR Calculation<br/>               7.2.2 Spot Market Price Simulation<br/>               7.2.3 A Numerical Example<br/>               7.2.4 A Practical Example<br/>               7.2.5 Sensitivity Analysis<br/>          7.3 Generation Capacity Valuation<br/>               7.3.1 Framework of VaR Calculation<br/>               7.3.2 An Example<br/>               7.3.3 Sensitivity Analysis<br/>          7.4 Conclusions<br/>     CHAPTER 8 Security-Constrained Unit Commitment<br/>          8.1 Introduction<br/>          8.2 SCUC Problem Formulation<br/>               8.2.1 Discussion on Ramping Constraints<br/>          8.3 Benders Decomposition Solution of SCUC<br/>               8.3.1 Benders Decomposition<br/>               8.3.2 Application of Benders Decomposition to SCUC<br/>               8.3.3 Master Problem Formulation<br/>          8.4 SCUC to Minimize Network Violation<br/>               8.4.1 Linearization of Network Constraints<br/>               8.4.2 Subproblem Formulation<br/>               8.4.3 Benders Cuts Formulation<br/>               8.4.4 Case Study<br/>          8.5 SCUC Application to Minimize EUE - Impact of Reliability<br/>               8.5.1 Subproblem Formulation and Solution<br/>               8.5.2 Case Study<br/>          8.6 Conclusions<br/>     CHAPTER 9 Ancillary Services Auction Market Design<br/>          9.1 Introduction<br/>          9.2 Ancillary Services for Restructuring<br/>          9.3 Forward Ancillary Services Auction – Sequential Approach<br/>               9.3.1 Two Alternatives in Sequential Ancillary Services Auction<br/>               9.3.2 Ancillary Services Scheduling<br/>               9.3.3 Design of the Ancillary Services Auction Market<br/>               9.3.4 Case Study<br/>               9.3.5 Discussions<br/>          9.4 Forward Ancillary Services Auction – Simultaneous Approach<br/>               9.4.1 Design Options for Simultaneous Auction of Ancillary Services<br/>               9.4.2 Rational Buyer Auction<br/>               9.4.3 Marginal Pricing Auction<br/>               9.4.4 Discussions<br/>          9.5 Automatic Generation Control (AGC)<br/>               9.5.1 AGC Functions<br/>               9.5.2 AGC Response<br/>               9.5.3 AGC Units Revenue Adequacy<br/>               9.5.4 AGC Pricing<br/>               9.5.5 Discussions<br/>          9.6 Conclusions<br/>     CHAPTER 10 Transmission Congestion Management and Pricing<br/>          10.1 Introduction<br/>          10.2 Transmission Cost Allocation Methods<br/>               10.2.1 Postage-Stamp Rate Method<br/>               10.2.2 Contract Path Method<br/>               10.2.3 MW-Mile Method<br/>               10.2.4 Unused Transmission Capacity Method<br/>               10.2.5 MVA-Mile Method<br/>               10.2.6 Counter-Flow Method<br/>               10.2.7 Distribution Factors Method<br/>               10.2.8 AC Power Flow Method<br/>               10.2.9 Tracing Methods<br/>               10.2.10 Comparison of Cost Allocation Methods<br/>          10.3 Examples for Transmission Cost Allocation Methods<br/>               10.3.1 Cost Allocation Using Distribution Factors Method<br/>               10.3.2 Cost Allocation Using Bialek’s Tracing Method<br/>               10.3.3 Cost Allocation Using Kirschen’s Tracing Method<br/>               10.3.4 Comparing the Three Cost Allocation Methods<br/>          10.4 LMP, FTR, and Congestion Management<br/>               10.4.1 Locational Marginal Price (LMP)<br/>               10.4.2 LMP Application in Determining Zonal Boundaries<br/>               10.4.3 Firm Transmission Right (FTR)<br/>               10.4.4 FTR Auction<br/>               10.4.5 Zonal Congestion Management<br/>          10.5 A Comprehensive Transmission Pricing Scheme<br/>               10.5.1 Outline of the Proposed Transmission Pricing Scheme<br/>               10.5.2 Prioritization of Transmission Dispatch<br/>               10.5.3 Calculation of Transmission Usage and Congestion Charges and FTR Credits<br/>               10.5.4 Numerical Example<br/>          10.6 Conclusions<br/>     APPENDIX A List of Symbols<br/>     APPENDIX B Mathematical Derivation<br/>          B.1 Derivation of Probability Distribution<br/>          B.2 Lagrangian Augmentation with Inequality Constraints<br/>     APPENDIX C RTS Load Data<br/>     APPENDIX D Example Systems Data<br/>          D.1 5-Unit System<br/>          D.2 36-Unit System<br/>          D.3 6-Unit System<br/>          D.4 Modified IEEE 30-Bus System<br/>          D.5 118-Bus System<br/>     APPENDIX E Game Theory Concepts<br/>          E.1 Equilibrium in Non-Cooperative Games<br/>          E.2 Characteristics Function<br/>          E.3 N-Players Cooperative Games<br/>          E.4 Games with Incomplete Information<br/>     APPENDIX F Congestion Charges Calculation<br/>          F.1 Calculations of Congestion Charges using Contributions of Generators<br/>          F.2 Calculations of Congestion Charges using Contributions of Loads<br/>     References<br/>     Index</p>

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