Grid Optimal Integration of Electrical Vehicles : Examples With Matlab Implementation
Language: English
Published by Springer, 2018
Series: Book 132 of 378 - Studies in Systems, Decision and Control
- Hardcover
- New
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Title
- Grid Optimal Integration of Electrical Vehicles : Examples With Matlab Implementation
- Author
- Ovalle, Andrés; Hably, Ahmad; Bacha, Seddik
- Publisher
- Springer
- Publication year
- 2018
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3319731769
- ISBN 13
- 9783319731766
- Series
- Book 132 of 378: Studies in Systems, Decision and Control
This book is a compilation of recent research on distributed optimization algorithms for the integral load management of plug-in electric vehicle (PEV) fleets and their potential services to the electricity system. It also includes detailed developed Matlab scripts. These algorithms can be implemented and extended to diverse applications where energy management is required (smart buildings, railways systems, task sharing in micro-grids, etc.). The proposed methodologies optimally manage PEV fleets’ charge and discharge schedules by applying classical optimization, game theory, and evolutionary game theory techniques. Taking owner’s requirements into consideration, these approaches provide services like load shifting, load balancing among phases of the system, reactive power supply, and task sharing among PEVs. The book is intended for use in graduate optimization and energy management courses, and readers are encouraged to test and adapt the scripts to their specific applications.
"Synopsis" may belong to another edition of this title.
From the Back Cover
This book is a compilation of recent research on distributed optimization algorithms for the integral load management of plug-in electric vehicle (PEV) fleets and their potential services to the electricity system. It also includes detailed developed Matlab scripts. These algorithms can be implemented and extended to diverse applications where energy management is required (smart buildings, railways systems, task sharing in micro-grids, etc.). The proposed methodologies optimally manage PEV fleets’ charge and discharge schedules by applying classical optimization, game theory, and evolutionary game theory techniques. Taking owner’s requirements into consideration, these approaches provide services like load shifting, load balancing among phases of the system, reactive power supply, and task sharing among PEVs. The book is intended for use in graduate optimization and energy management courses, and readers are encouraged to test and adapt the scripts to their specific applications.
"About the title" may belong to another edition of this title.
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