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The Next Generation of Electric Power Unit Commitment Models

  • Book
  • © 2001

Overview

Editors:
  1. Benjamin F. Hobbs

    1. The Johns Hopkins University, USA

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  2. Michael H. Rothkopf

    1. Rutgers University, USA

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  3. Richard P. O’Neill

    1. Federal Energy Regulatory Commission, USA

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  4. Hung-po Chao

    1. Electric Power Research Institute, USA

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Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 36)

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Table of contents (16 chapters)

  1. Front Matter

    Pages i-vii
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  2. The Evolving Context for Unit Commitment Decisions

    1. Why this Book? New Capabilities and New Needs for Unit Commitment Modeling

      • Benjamin F. Hobbs, William R. Stewart Jr., Robert E. Bixby, Michael H. Rothkopf, Richard P. O’Neill, Hung-po Chao
      Pages 1-14

    2. Regulatory Evolution, Market Design and Unit Commitment

      • Richard P. O’Neill, Udi Helman, Paul M. Sotkiewicz, Michael H. Rothkopf, William R. Stewart Jr.
      Pages 15-37

    3. Development of an Electric Energy Market Simulator

      • Atif Debs, Charles Hansen, Yu-Chi Wu
      Pages 39-52

  3. New Features in Unit Commitment Models

    1. Auctions with Explicit Demand-Side Bidding in Competitive Electricity Markets

      • A. Borghetti, G. Gross, C. A. Nucci
      Pages 53-74

    2. Thermal Unit Commitment with a Nonlinear AC Power Flow Network Model

      • Carlos E. Murillo-Sánchez, Robert J. Thomas
      Pages 75-92

    3. Optimal Self-Commitment under Uncertain Energy and Reserve Prices

      • R. Rajaraman, L. Kirsch, F. L. Alvarado, C. Clark
      Pages 93-116

    4. A Stochastic Model for a Price-Based Unit Commitment Problem and Its Application to Short-Term Generation Asset Valuation

      • Chung-Li Tseng
      Pages 117-138

    5. Probabilistic Unit Commitment under a Deregulated Market

      • Jorge Valenzuela, Mainak Mazumdar
      Pages 139-152

  5. Decentralized Decision Making

    1. Strategic Unit Commitment for Generation in Deregulated Electricity Markets

      • A. Baíllo, M. Ventosa, A. Ramos, M. Rivier, A. Canseco
      Pages 227-248

    2. Optimization-Based Bidding Strategies for Deregulated Electric Power Markets

      • Xiaohong Guan, Ernan Ni, Peter B. Luh, Yu-Chi Ho
      Pages 249-270

    3. Decentralized Nodal-Price Self-Dispatch and Unit Commitment

      • Francisco D. Galiana, Alexis L. Motto, Antonio J. Conejo, Maurice Huneault
      Pages 271-292

    4. Decentralized Unit Commitment in Competitive Energy Markets

      • Jinghai Xu, Richard D. Christie
      Pages 293-313

  6. Back Matter

    Pages 317-319
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Keywords

About this book

Over the years, the electric power industry has been using optimization methods to help them solve the unit commitment problem. The result has been savings of tens and perhaps hundreds of millions of dollars in fuel costs. Things are changing, however. Optimization technology is improving, and the industry is undergoing radical restructuring. Consequently, the role of commitment models is changing, and the value of the improved solutions that better algorithms might yield is increasing. The dual purpose of this book is to explore the technology and needs of the next generation of computer models for aiding unit commitment decisions.
Because of the unit commitment problem's size and complexity and because of the large economic benefits that could result from its improved solution, considerable attention has been devoted to algorithm development in the book. More systematic procedures based on a variety of widely researched algorithms have been proposed and tested. These techniques have included dynamic programming, branch-and-bound mixed integer programming (MIP), linear and network programming approaches, and Benders decomposition methods, among others. Recently, metaheuristic methods have been tested, such as genetic programming and simulated annealing, along with expert systems and neural networks. Because electric markets are changing rapidly, how UC models are solved and what purposes they serve need reconsideration. Hence, the book brings together people who understand the problem and people who know what improvements in algorithms are really possible. The two-fold result in The Next Generation of Electric Power Unit Commitment Models is an assessment of industry needs and new formulations and computational approaches that promise to make unit commitment models more responsive to those needs.

Editors and Affiliations

  • The Johns Hopkins University, USA

    Benjamin F. Hobbs

  • Rutgers University, USA

    Michael H. Rothkopf

  • Federal Energy Regulatory Commission, USA

    Richard P. O’Neill

  • Electric Power Research Institute, USA

    Hung-po Chao

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