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© 2008

New Computational Methods in Power System Reliability

  • David Elmakias
  • Comprehensive up-to-date presentation of novel tools for power system reliability analysis and optimization and to present examples of applications

Book
  • 6.1k Downloads

Part of the Studies in Computational Intelligence book series (SCI, volume 111)

About this book

Introduction

Power system reliability is in the focus of intensive study due to its critical role in providing energy supply to the modern society. This book is not aimed at providing the overview of the state of the art in power system reliability. On the contrary, it describes application of some new specific techniques: universal generating function method and its combination with Monte Carlo simulation and with random processes methods, Semi-Markov and Markov reward models and genetic algorithm. The book can be considered as complementary to power system reliability textbooks. It is suitable for different types of readers. It primarily addresses practising reliability engineers and researchers who have an interest in reliability and performability analysis of power systems. It can also be used as a textbook for senior undergraduate or graduate courses in electrical engineering.

Keywords

Distribution Networks Markov Power System Reliability Power Systems algorithm algorithms electrical engineering genetic algorithms simulation transformation

Editors and affiliations

  • David Elmakias

There are no affiliations available

Bibliographic information

  • Book Title New Computational Methods in Power System Reliability
  • Editors David Elmakias
  • Series Title Studies in Computational Intelligence
  • DOI https://doi.org/10.1007/978-3-540-77812-7
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-3-540-77810-3
  • Softcover ISBN 978-3-642-09657-0
  • eBook ISBN 978-3-540-77812-7
  • Series ISSN 1860-949X
  • Series E-ISSN 1860-9503
  • Edition Number 1
  • Number of Pages XIV, 404
  • Number of Illustrations 119 b/w illustrations, 0 illustrations in colour
  • Topics Mathematical and Computational Engineering
    Artificial Intelligence
  • Buy this book on publisher's site
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