Publication:
A bi-criteria optimization model to analyze the impacts of electric vehicles on costs and emissions

dc.contributor.coauthorN/A
dc.contributor.departmentN/A
dc.contributor.departmentDepartment of Industrial Engineering
dc.contributor.kuauthorKabatepe, Bora
dc.contributor.kuauthorTürkay, Metin
dc.contributor.kuprofileMaster Student
dc.contributor.kuprofileFaculty Member
dc.contributor.otherDepartment of Industrial Engineering
dc.contributor.schoolcollegeinstituteGraduate School of Sciences and Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.yokidN/A
dc.contributor.yokid24956
dc.date.accessioned2024-11-10T00:09:13Z
dc.date.issued2017
dc.description.abstractElectric vehicles (EV) are emerging as a mobility solution to reduce emissions in the transportation sector. The studies environmental impact analysis of EVs in the literature are based on the average energy mix or pre-defined generation scenarios and construct policy recommendations with a cost minimization objective. However, the environmental performance of EVs depends on the source of the marginal electricity provided to the grid and single objective models do not provide a thorough analysis on the economic and environmental impacts of EVs. In this paper, these gaps are addressed by a four step methodology that analyzes the effects of EVs under different charging and market penetration scenarios. The methodology includes a bi-criteria optimization model representing the electricity market operations. The results from a real-life case analysis show that EVs decrease costs and emissions significantly compared to conventional vehicles.
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.openaccessNO
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuTÜBİTAK
dc.description.sponsorshipSystems Laboratory in Koc University Istanbul
dc.description.sponsorshipIBM Corporation
dc.description.sponsorshipThe Scientific and Technological Research Council of Turkey (TUBITAK) [104M322] The study has been conducted in Systems Laboratory in Koc University Istanbul with the invaluable support of IBM Corporation through IBM SUR Award. The authors would like to acknowledge the funding from The Scientific and Technological Research Council of Turkey (TUBITAK) through grant 104M322. Data provided by Turkish Electricity Transmission Company Limited (TEIAS) has been valuable in the study. Special thanks to Birol Karatay from TEIAS who explained the Turkish electricity market and annotated the data.
dc.description.volume102
dc.identifier.doi10.1016/j.compchemeng.2016.11.026
dc.identifier.eissn1873-4375
dc.identifier.issn0098-1354
dc.identifier.quartileQ2
dc.identifier.scopus2-s2.0-85007433812
dc.identifier.urihttp://dx.doi.org/10.1016/j.compchemeng.2016.11.026
dc.identifier.urihttps://hdl.handle.net/20.500.14288/17070
dc.identifier.wos401885400014
dc.keywordsElectric vehicles
dc.keywordsImpact analysis
dc.keywordsGreenhouse gases
dc.keywordsBi-criteria optimization
dc.languageEnglish
dc.publisherElsevier
dc.sourceComputers and Chemical Engineering
dc.subjectComputer science
dc.subjectInterdisciplinary applications
dc.subjectEngineering
dc.subjectChemical engineering
dc.titleA bi-criteria optimization model to analyze the impacts of electric vehicles on costs and emissions
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.authoridN/A
local.contributor.authorid0000-0003-4769-6714
local.contributor.kuauthorKabatepe, Bora
local.contributor.kuauthorTürkay, Metin
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relation.isOrgUnitOfPublication.latestForDiscoveryd6d00f52-d22d-4653-99e7-863efcd47b4a

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