Electrical Power Unit Commitment

Lieferzeit: Lieferbar innerhalb 14 Tagen

64,19 

Deterministic and Two-Stage Stochastic Programming Models and Algorithms, SpringerBriefs in Energy

ISBN: 1493967665
ISBN 13: 9781493967667
Autor: Huang, Yuping/Pardalos, Panos M/Zheng, Qipeng P
Verlag: Springer Verlag GmbH
Umfang: viii, 93 S., 8 s/w Illustr., 16 farbige Illustr., 93 p. 24 illus., 16 illus. in color.
Erscheinungsdatum: 13.01.2017
Auflage: 1/2017
Produktform: Kartoniert
Einband: Kartoniert

This volume in the SpringerBriefs in Energy series offers a systematic review of unit commitment (UC) problems in electrical power generation. It updates texts written in the late 1990s and early 2000s by including the fundamentals of both UC and state-of-the-art modeling as well as solution algorithms and highlighting stochastic models and mixed-integer programming techniques.The UC problems are mostly formulated as mixed-integer linear programs, although there are many variants. A number of algorithms have been developed for, or applied to, UC problems, including dynamic programming, Lagrangian relaxation, general mixed-integer programming algorithms, and Benders decomposition. In addition the book discusses the recent trends in solving UC problems, especially stochastic programming models, and advanced techniques to handle large numbers of integer- decision variables due to scenario propagation

Artikelnummer: 9908062 Kategorie:

Beschreibung

This volume in the SpringerBriefs in Energy series offers a systematic review of unit commitment (UC) problems in electrical power generation. It updates texts written in the late 1990s and early 2000s by including the fundamentals of both UC and state-of-the-art modeling as well as solution algorithms and highlighting stochastic models and mixed-integer programming techniques. The UC problems are mostly formulated as mixed-integer linear programs, although there are many variants. A number of algorithms have been developed for, or applied to, UC problems, including dynamic programming, Lagrangian relaxation, general mixed-integer programming algorithms, and Benders decomposition. In addition the book discusses the recent trends in solving UC problems, especially stochastic programming models, and advanced techniques to handle large numbers of integer- decision variables due to scenario propagation

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