Publication: A bi-criteria optimization model to analyze the impacts of electric vehicles on costs and emissions
dc.contributor.coauthor | N/A | |
dc.contributor.department | N/A | |
dc.contributor.department | Department of Industrial Engineering | |
dc.contributor.kuauthor | Kabatepe, Bora | |
dc.contributor.kuauthor | Türkay, Metin | |
dc.contributor.kuprofile | Master Student | |
dc.contributor.kuprofile | Faculty Member | |
dc.contributor.other | Department of Industrial Engineering | |
dc.contributor.schoolcollegeinstitute | Graduate School of Sciences and Engineering | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.contributor.yokid | N/A | |
dc.contributor.yokid | 24956 | |
dc.date.accessioned | 2024-11-10T00:09:13Z | |
dc.date.issued | 2017 | |
dc.description.abstract | Electric 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.indexedby | WoS | |
dc.description.indexedby | Scopus | |
dc.description.openaccess | NO | |
dc.description.publisherscope | International | |
dc.description.sponsoredbyTubitakEu | TÜBİTAK | |
dc.description.sponsorship | Systems Laboratory in Koc University Istanbul | |
dc.description.sponsorship | IBM Corporation | |
dc.description.sponsorship | The 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.volume | 102 | |
dc.identifier.doi | 10.1016/j.compchemeng.2016.11.026 | |
dc.identifier.eissn | 1873-4375 | |
dc.identifier.issn | 0098-1354 | |
dc.identifier.quartile | Q2 | |
dc.identifier.scopus | 2-s2.0-85007433812 | |
dc.identifier.uri | http://dx.doi.org/10.1016/j.compchemeng.2016.11.026 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/17070 | |
dc.identifier.wos | 401885400014 | |
dc.keywords | Electric vehicles | |
dc.keywords | Impact analysis | |
dc.keywords | Greenhouse gases | |
dc.keywords | Bi-criteria optimization | |
dc.language | English | |
dc.publisher | Elsevier | |
dc.source | Computers and Chemical Engineering | |
dc.subject | Computer science | |
dc.subject | Interdisciplinary applications | |
dc.subject | Engineering | |
dc.subject | Chemical engineering | |
dc.title | A bi-criteria optimization model to analyze the impacts of electric vehicles on costs and emissions | |
dc.type | Journal Article | |
dspace.entity.type | Publication | |
local.contributor.authorid | N/A | |
local.contributor.authorid | 0000-0003-4769-6714 | |
local.contributor.kuauthor | Kabatepe, Bora | |
local.contributor.kuauthor | Türkay, Metin | |
relation.isOrgUnitOfPublication | d6d00f52-d22d-4653-99e7-863efcd47b4a | |
relation.isOrgUnitOfPublication.latestForDiscovery | d6d00f52-d22d-4653-99e7-863efcd47b4a |