Modern Optimisation Techniques in Power Systems by Yong-Hua SongModern Optimisation Techniques in Power Systems by Yong-Hua Song

Modern Optimisation Techniques in Power Systems

EditorYong-Hua Song

Paperback | December 5, 2010

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Under an ever-increasingly competitive/deregulated environment, power utilities need efficient and effective tools to ensure that electrical energy of the desired quality can be provided at the lowest cost. These usually form highly constrained optimisation problems. Modern Optimisation Techniques in Power Systems is the first book to offer a comprehensive cover of major modern optimisation methods applied to power systems, including: simulated annealing, tabu search, genetic algorithms, neural networks, fuzzy programming, Lagrangian relaxation, interior point methods, ant colony search and hybrid techniques. Various applications and case studies are presented to demonstrate the potential and procedures of applying such techniques in solving complex power system optimisation problems. Written by top international experts in this field, this book will be a useful reference for professional engineers and managers involved in the optimisation of power system operation. It will also be of interest to postgraduates and researchers.
Title:Modern Optimisation Techniques in Power SystemsFormat:PaperbackDimensions:286 pages, 9.61 × 6.69 × 0.04 inPublished:December 5, 2010Publisher:Springer NetherlandsLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:904815216X

ISBN - 13:9789048152162

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Table of Contents

Preface. Contributors. 1. Introduction; Y.H. Song. 2. Simulated annealing applications; K. Nara. 3. Tabu search application in fault section estimation and state identification of unobserved protective relays in power system; F. Wen, C.S. Chang. 4. Genetic algorithms for scheduling generation and maintenance in power systems; C.J. Aldridge, et al. 5. Transmission network planning using genetic algorithms; M.R. Irving, et al. 6. Artificial neural networks for generation scheduling; M.P. Walsh, M.J. O'Malley. 7. Decision making in a deregulated power environment based on fuzzy sets; S.M. Shahidehpour, M.I. Alomoush. 8. Lagrangian relaxation applications to electric power operations and planning problems; A.J. Conejo, et al. 9. Inter point methods and applications in power systems; K. Xie, Y.H. Song. 10. Ant colony search, advanced engineered-conditioning genetic algorithms and fuzzy logic controlled genetic algorithms: economic dispatch problems; Y.H. Song, et al. 11. Industrial applications of artificial intelligence techniques; A.O. Ekwue.