Decentralized Charging Coordination of Large-scale Plug-in Electric Vehicles in Power Systems [electronic resource] / by Zhongjing Ma.
By: Ma, Zhongjing [author.].
Contributor(s): SpringerLink (Online service).
Material type: BookPublisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2020Edition: 1st ed. 2020.Description: XXI, 238 p. 89 illus., 1 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9789811376528.Subject(s): Electric power production | Control engineering | Automotive engineering | Game theory | Electrical Power Engineering | Control and Systems Theory | Automotive Engineering | Game TheoryAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 621.31 Online resources: Click here to access onlineIntroduction -- Charging coordination via non-cooperative games -- Decentralized Charging coordination with battery degradation cost -- Charging coordination in capacity-constrained distribution networks -- Charging coordination based on auction games -- V2G coordination method via auction games.
This book focuses on the design of decentralized optimization methods applied to charging strategies for large-scale PEVs in electrical power systems. It studies several classes of charging coordination problems in large-scale PEVs by considering the distinct characteristics of PEV populations and electrical power systems, and subsequently designs decentralized methods based on distinct optimization schemes – such as non-cooperative games, mean-field games, and auction games – to achieve optimal/nearly optimal charging strategies. In closing, several performance aspects of the proposed algorithms, such as their convergence, computational complexity and optimality etc., are rigorously verified and demonstrated in numerical simulations. Given its scope, the book will benefit researchers, engineers, and graduate students in the fields of optimization, game theory, auction games, electrical power systems, etc., and help them design decentralized methods to implement optimal charging strategies in large-scale PEVs.
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