Overview
- Offers a compilation of recent research on distributed optimization algorithms for the integral load management of plug-in electric vehicle (PEV) fleets
- Proposes distributed optimization algorithms for the integral load management of electric vehicle (EV) fleets and their potential services to the electricity system
- Helps to optimally manage EV fleets charge/discharge schedules by applying game theory and evolutionary game theory techniques
- Benefits researchers working in the field of optimal integration of EVs
- Includes useful material for courses on grid modeling, optimization, and game theory
Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 137)
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Table of contents (5 chapters)
Keywords
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Grid Optimal Integration of Electric Vehicles: Examples with Matlab Implementation
Authors: Andrés Ovalle, Ahmad Hably, Seddik Bacha
Series Title: Studies in Systems, Decision and Control
DOI: https://doi.org/10.1007/978-3-319-73177-3
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2018
Hardcover ISBN: 978-3-319-73176-6Published: 13 February 2018
Softcover ISBN: 978-3-319-89238-2Published: 04 June 2019
eBook ISBN: 978-3-319-73177-3Published: 04 February 2018
Series ISSN: 2198-4182
Series E-ISSN: 2198-4190
Edition Number: 1
Number of Pages: XV, 219
Number of Illustrations: 2 b/w illustrations, 88 illustrations in colour
Topics: Computational Intelligence, Renewable and Green Energy, Renewable and Green Energy, Optimization, Game Theory, Economics, Social and Behav. Sciences