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EBOOK
Author Cuevas, Erik,
Title Metaheuristics algorithms in power systems / Erik Cuevas, Emilio Barocio Espejo, Arturo Conde Enriquez.
Imprint Cham : Springer, 2019.

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Author Cuevas, Erik,
Series Studies in Computational Intelligence, 1860-949X ; v. 822.
Studies in computational intelligence ; 822. 1860-949X.
Subject Electric power systems -- Mathematical models.
Engineering.
Artificial intelligence.
Alt Name Barocio Espejo, Emilio,
Conde Enriquez, Arturo,
Description 1 online resource (xii, 221 pages).
Contents Chapter 1. Introduction to metaheuristics methods -- Chapter 2. Metaheuristic schemes for parameter estimation in induction motors -- Chapter 3. Non-conventional overcurrent relays coordination -- Chapter 4. Overcurrent relay coordination, robustness and fast solutions etc.
Summary This book discusses the use of efficient metaheuristic algorithms to solve diverse power system problems, providing an overview of the various aspects of metaheuristic methods to enable readers to gain a comprehensive understanding of the field and of conducting studies on specific metaheuristic algorithms related to power-system applications. By bridging the gap between recent metaheuristic techniques and novel power system methods that benefit from the convenience of metaheuristic methods, it offers power system practitioners who are not metaheuristic computation researchers insights into the techniques, which go beyond simple theoretical tools and have been adapted to solve important problems that commonly arise. On the other hand, members of the metaheuristic computation community learn how power engineering problems can be translated into optimization tasks, and it is also of interest to engineers and application developers. Further, since each chapter can be read independently, the relevant information can be quickly found. Power systems is a multidisciplinary field that addresses the multiple approaches used for design and analysis in areas ranging from signal processing, and electronics to computational intelligence, including the current trend of metaheuristic computation.
ISBN 9783030115937 (electronic bk.)
3030115933 (electronic bk.)
9783030115920 (print)
3030115925
ISBN/ISSN 10.1007/978-3-030-11593-7
OCLC # 1086506745
Additional Format Printed edition: 9783030115920 (OCoLC)1078894165.
Printed edition: 9783030115944.


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