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Conference Paper: Optimal V2G scheduling of electric vehicles and unit commitment using chemical reaction optimization

TitleOptimal V2G scheduling of electric vehicles and unit commitment using chemical reaction optimization
Authors
KeywordsChemical reaction optimization
Electric vehicle
Metaheuristic
Power system
Smart grid
Unit commitmen
Vehicle-to-grid
Issue Date2013
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000284
Citation
The 2013 IEEE Congress on Evolutionary Computation (CEC), Cancun, Mexico, 20-23 June 2013. In Conference Proceedings, 2013, p. 392-399 How to Cite?
AbstractAn 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. © 2013 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/191608
ISBN

 

DC FieldValueLanguage
dc.contributor.authorYu, JJQen_US
dc.contributor.authorLi, VOKen_US
dc.contributor.authorLam, AYSen_US
dc.date.accessioned2013-10-15T07:14:37Z-
dc.date.available2013-10-15T07:14:37Z-
dc.date.issued2013en_US
dc.identifier.citationThe 2013 IEEE Congress on Evolutionary Computation (CEC), Cancun, Mexico, 20-23 June 2013. In Conference Proceedings, 2013, p. 392-399en_US
dc.identifier.isbn978-1-4799-0454-9-
dc.identifier.urihttp://hdl.handle.net/10722/191608-
dc.description.abstractAn 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. © 2013 IEEE.-
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000284-
dc.relation.ispartofCongress on Evolutionary Computation Proceedingsen_US
dc.rightsCongress on Evolutionary Computation Proceedings. Copyright © IEEE.-
dc.rights©2013 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectChemical reaction optimization-
dc.subjectElectric vehicle-
dc.subjectMetaheuristic-
dc.subjectPower system-
dc.subjectSmart grid-
dc.subjectUnit commitmen-
dc.subjectVehicle-to-grid-
dc.titleOptimal V2G scheduling of electric vehicles and unit commitment using chemical reaction optimizationen_US
dc.typeConference_Paperen_US
dc.identifier.emailYu, JJQ: jqyu@eee.hku.hken_US
dc.identifier.emailLi, VOK: vli@eee.hku.hk-
dc.identifier.emailLam, AYS: albertlam@ieee.org-
dc.identifier.authorityLi, VOK=rp00150en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/CEC.2013.6557596-
dc.identifier.scopuseid_2-s2.0-84881579379-
dc.identifier.hkuros225542en_US
dc.identifier.hkuros261763-
dc.identifier.spage392-
dc.identifier.epage399-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 131106 ; sml 160908 merged-

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