File Download
  Links for fulltext
     (May Require Subscription)
  • Find via Find It@HKUL
Supplementary

Article: Genetic algorithm based cost-emission optimization of unit commitment integrating with gridable vehicles

TitleGenetic algorithm based cost-emission optimization of unit commitment integrating with gridable vehicles
Authors
KeywordsGridable vehicle
Vehicle-to-grid
Unit commitment
Cost-emission optimization
Genetic algorithm
Issue Date2012
PublisherAsian Electric Vehicle Society. The Journal's web site is located at http://www.elec.eng.osaka-cu.ac.jp/aevc/
Citation
Journal of Asian Electric Vehicles, 2012, v. 10 n. 1, p. 1567-1573 How to Cite?
AbstractThis paper first proposes a multilayer framework of vehicle-to-grid (V2G) system based on the concept of gridable vehicles (GVs). GVs can draw and store energy from the power grid as loads, as well as feed energy back to the grid as resources. Then, unit commitment integrating with GVs is analyzed using the proposed framework. The objective is to minimize the total operating cost and emissions of the V2G system by intelligently scheduling the generating units and GVs based on the use of genetic algorithm. The results illustrate that the operating cost and emissions can be reduced and the system reserves can be enhanced by applying V2G.
Persistent Identifierhttp://hdl.handle.net/10722/164051
ISSN

 

DC FieldValueLanguage
dc.contributor.authorWu, Den_US
dc.contributor.authorChau, KTen_US
dc.contributor.authorLiu, Cen_US
dc.contributor.authorGao, Sen_US
dc.date.accessioned2012-09-20T07:55:06Z-
dc.date.available2012-09-20T07:55:06Z-
dc.date.issued2012en_US
dc.identifier.citationJournal of Asian Electric Vehicles, 2012, v. 10 n. 1, p. 1567-1573en_US
dc.identifier.issn1348-3927-
dc.identifier.urihttp://hdl.handle.net/10722/164051-
dc.description.abstractThis paper first proposes a multilayer framework of vehicle-to-grid (V2G) system based on the concept of gridable vehicles (GVs). GVs can draw and store energy from the power grid as loads, as well as feed energy back to the grid as resources. Then, unit commitment integrating with GVs is analyzed using the proposed framework. The objective is to minimize the total operating cost and emissions of the V2G system by intelligently scheduling the generating units and GVs based on the use of genetic algorithm. The results illustrate that the operating cost and emissions can be reduced and the system reserves can be enhanced by applying V2G.-
dc.languageengen_US
dc.publisherAsian Electric Vehicle Society. The Journal's web site is located at http://www.elec.eng.osaka-cu.ac.jp/aevc/-
dc.relation.ispartofJournal of Asian Electric Vehiclesen_US
dc.subjectGridable vehicle-
dc.subjectVehicle-to-grid-
dc.subjectUnit commitment-
dc.subjectCost-emission optimization-
dc.subjectGenetic algorithm-
dc.titleGenetic algorithm based cost-emission optimization of unit commitment integrating with gridable vehiclesen_US
dc.typeArticleen_US
dc.identifier.emailChau, KT: ktchau@eee.hku.hken_US
dc.identifier.emailLiu, C: chhualiu@hku.hken_US
dc.identifier.authorityChau, KT=rp00096en_US
dc.description.naturelink_to_OA_fulltext-
dc.identifier.hkuros208221en_US
dc.identifier.volume10en_US
dc.identifier.issue1en_US
dc.identifier.spage1567en_US
dc.identifier.epage1573en_US
dc.publisher.placeJapan-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats