株式会社極東書店トップ商品一覧Probabilistic Reliability Analysis of Power Systems: A Student's Introduction. 2020 ed.

商品詳細

Probabilistic Reliability Analysis of Power Systems: A Student's Introduction. 2020 ed.

Probabilistic Reliability Analysis of Power Systems: A Student's Introduction. 2020 ed.

・ISBN 978-3-030-43497-7 hard EUR 99.99

¥26,726.- (税込) (※)価格はご注文時の参考価格となります。
納品価格につきましては書籍の入荷時点で確定となります。
版元の原価改定、外国為替の変動等により異なる場合がございますので、予めご了承下さい。

お気に入り
著者・編者Tuinema, Bart W. / Rueda Torres, Jose L. / Stefanov, Alexandru I. / Gonzalez-Longatt, Francisco M. / van der Meijden, Mart A. M. M.,
出版社 (Springer Nature Switzerland AG, SZ)
出版年月2020
ページ数334 pp.
言語ENG
ニュース番号<A02-65266>

解説

This textbook provides an introduction to probabilistic reliability analysis of power systems. It discusses a range of probabilistic methods used in reliability modelling of power system components, small systems and large systems. It also presents the benefits of probabilistic methods for modelling renewable energy sources. The textbook describes real-life studies, discussing practical examples and providing interesting problems, teaching students the methods in a thorough and hands-on way.

The textbook has chapters dedicated to reliability models for components (reliability functions, component life cycle, two-state Markov model, stress-strength model), small systems (reliability networks, Markov models, fault/event tree analysis) and large systems (generation adequacy, state enumeration, Monte-Carlo simulation). Moreover, it contains chapters about probabilistic optimal power flow, the reliability of underground cables and cyber-physical power systems.

After reading this book, engineering students will be able to apply various methods to model the reliability of power system components, smaller and larger systems. The textbook will be accessible to power engineering students, as well as students from mathematics, computer science, physics, mechanical engineering, policy & management, and will allow them to apply reliability analysis methods to their own areas of expertise.