@inproceedings{4049a82c154a445898fcb71e3b1aeed4,
title = "Optimal V2G scheduling of electric vehicles and unit commitment using chemical reaction optimization",
abstract = "An electric vehicle (EV) may be used as energy storage which allows the bi-directional electricity flow between the vehicle's battery and the electric power grid. In order to flatten the load profile of the electricity system, EV scheduling has become a hot research topic in recent years. In this paper, we propose a new formulation of the joint scheduling of EV and Unit Commitment (UC), called EVUC. Our formulation considers the characteristics of EVs while optimizing the system total running cost. We employ Chemical Reaction Optimization (CRO), a general-purpose optimization algorithm to solve this problem and the simulation results on a widely used set of instances indicate that CRO can effectively optimize this problem.",
keywords = "chemical reaction optimization, Electric vehicle, metaheuristic, power system, smart grid, unit commitment, vehicle-to-grid",
author = "Yu, {James J.Q.} and Li, {Victor O.K.} and Lam, {Albert Y.S.}",
note = "Copyright: Copyright 2013 Elsevier B.V., All rights reserved.; 2013 IEEE Congress on Evolutionary Computation, CEC 2013 ; Conference date: 20-06-2013 Through 23-06-2013",
year = "2013",
doi = "10.1109/CEC.2013.6557596",
language = "English",
isbn = "9781479904549",
series = "2013 IEEE Congress on Evolutionary Computation, CEC 2013",
pages = "392--399",
booktitle = "2013 IEEE Congress on Evolutionary Computation, CEC 2013",
}