The Next Generation of Electric Power Unit Commitment Models
Language: English
Published by Kluwer Academic Publishers, 2001
Series: Book 30 of 323 - International Series in Operations Research & Management Science
- Hardcover
- New
Seller: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
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Condition: New
£ 319.49
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Add to basketItem description from seller
As optimization technology improves, the electric power industry is undergoing radical restructuring, and the role of commitment models is changing. 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. Editor(s): Hobbs, Benjamin F.; Rothkopf, Michael H.; Chao, Hung-Po; O'Neill, Richard P. Series: International Series in Operations Research & Management Science. Num Pages: 328 pages, biography. BIC Classification: KC; KNBL; RNF. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 19. Weight in Grams: 642. . 2001. Hardback. . . . . Books ship from the US and Ireland.
Seller Inventory # V9780792373346
- Title
- The Next Generation of Electric Power Unit Commitment Models
- Author
- . Ed(s): Hobbs, Benjamin F.; Rothkopf, Michael H.; Chao, Hung-Po; O'Neill, Richard P.
- Publisher
- Kluwer Academic Publishers
- Publication year
- 2001
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0792373340
- ISBN 13
- 9780792373346
- Series
- Book 30 of 323: International Series in Operations Research & Management Science
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.
"Synopsis" may belong to another edition of this title.
Kennys Bookstore
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