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Joint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 Emissions

2021Artigo científico Acesso aberto
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dc.contributor.authorLima, Tayenne Dias de
dc.contributor.authorFranco, John F.
dc.contributor.authorLezama, Fernando
dc.contributor.authorSoares, João
dc.contributor.authorVale, Zita
dc.date.accessioned2023-03-14T09:45:09Z
dc.date.available2023-03-14T09:45:09Z
dc.date.issued2021
dc.description.abstractIn the coming years, several transformations in the transport sector are expected, associated with the increase in electric vehicles (EVs). These changes directly impact electrical distribution systems (EDSs), introducing new challenges in their planning and operation. One way to assist in the desired integration of this technology is to allocate EV charging stations (EVCSs). Efforts have been made towards the development of EVCSs, with the ability to recharge the vehicle at a similar time than conventional vehicle filling stations. Besides, EVs can bring environmental benefits by reducing greenhouse gas emissions. However, depending on the energy matrix of the country in which the EVs fleet circulates, there may be indirect emissions of polluting gases. Therefore, the development of this technology must be combined with the growth of renewable generation. Thus, this proposal aims to develop a mathematical model that includes EVs integration in the distribution system. To this end, a mixed-integer linear programming (MILP) model is proposed to solve the allocation problem of EVCSs including renewable energy sources. The model addresses the environmental impact and uncertainties associated with demand (conventional and EVs) and renewable generation. Moreover, an EV charging forecast method is proposed, subject to the uncertainties related to the driver's behavior, the energy required by these vehicles, and the state of charge of the EVs. The proposed model was implemented in the AMPL modelling language and solved via the commercial solver CPLEX. Tests with a 24-node system allow evaluating the proposed method applicationpt_PT
dc.description.sponsorshipThe work was supported from FEDER funds through the Operational Programme for Competitiveness and Internationalization (COMPETE2020), under Project POCI-01-0145-FEDER-028983; by National Funds through the FCT Portuguese Foundation for Science and Technology, under Projects PTDC/EEI-EEE/28983/2017(CENERGETIC), CEECIND/02814/2017, and UIDB/000760/2020. This Brazillian team was supported by the Brazilian institutions Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001, CNPq (process 313047/2017–0) and São Paulo Research Foundation (FAPESP), grants 2015/21972–6, 2017/02831–8, 2018/23617–7, and 20018/08008–4 (CENERGETIC research project).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1186/s42162-021-00157-5pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/22466
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerOpenpt_PT
dc.relationPOCI-01-0145-FEDER-028983pt_PT
dc.relationNot Available
dc.relation.publisherversionhttps://energyinformatics.springeropen.com/articles/10.1186/s42162-021-00157-5pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectAllocation of electric vehicle charging stationspt_PT
dc.subjectElectric vehicle charging stationspt_PT
dc.subjectEV charging forecast methodpt_PT
dc.subjectRenewable energy sourcespt_PT
dc.titleJoint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 Emissionspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleNot Available
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/9471 - RIDTI/PTDC%2FEEI-EEE%2F28983%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/CEEC IND 2017/CEECIND%2F02814%2F2017%2FCP1417%2FCT0002/PT
oaire.citation.issueS2pt_PT
oaire.citation.titleEnergy Informaticspt_PT
oaire.citation.volume4pt_PT
oaire.fundingStream9471 - RIDTI
oaire.fundingStreamCEEC IND 2017
person.familyNameLezama
person.familyNameSoares
person.familyNameVale
person.givenNameFernando
person.givenNameJoão
person.givenNameZita
person.identifier1043580
person.identifier632184
person.identifier.ciencia-idE31F-56D6-1E0F
person.identifier.ciencia-id1612-8EA8-D0E8
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0001-8638-8373
person.identifier.orcid0000-0002-4172-4502
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-6945-2017
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id36810077500
person.identifier.scopus-author-id35436109600
person.identifier.scopus-author-id7004115775
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication6a55317b-92c2-404f-8542-c7a73061cc9b
relation.isAuthorOfPublication9ece308b-6d79-4cec-af91-f2278dcc47eb
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