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Multi-Objective Electric Vehicles Scheduling Using Elitist Non-Dominated Sorting Genetic Algorithm

2020Journal article Open access
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dc.contributor.authorMorais, Hugo
dc.contributor.authorSousa, Tiago
dc.contributor.authorCastro, Rui
dc.contributor.authorVale, Zita
dc.date.accessioned2021-09-17T15:18:01Z
dc.date.available2021-09-17T15:18:01Z
dc.date.issued2020
dc.description.abstractThe introduction of electric vehicles (EVs) will have an important impact on global power systems, in particular on distribution networks. Several approaches can be used to schedule the charge and discharge of EVs in coordination with the other distributed energy resources connected on the network operated by the distribution system operator (DSO). The aggregators, as virtual power plants (VPPs), can help the system operator in the management of these distributed resources taking into account the network characteristics. In the present work, an innovative hybrid methodology using deterministic and the elitist nondominated sorting genetic algorithm (NSGA-II) for the EV scheduling problem is proposed. The main goal is to test this method with two conflicting functions (cost and greenhouse gas (GHG) emissions minimization) and performing a comparison with a deterministic approach. The proposed method shows clear advantages in relation to the deterministic method, namely concerning the execution time (takes only 2% of the time) without impacting substantially the obtained results in both objectives (less than 5%).pt_PT
dc.description.sponsorshipThis work was supported by national funds through FCT, Fundação para a Ciência e a Tecnologia, under project UIDB/50021/2020 and from FEDER Funds through COMPETE program and from National Funds (FCT) under projects UIDB/00760/2020 and CENERGETIC (PTDC/EEI-EEE/28983/2017).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/app10227978pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/18422
dc.language.isoengpt_PT
dc.publisherMDPIpt_PT
dc.relation.publisherversionhttps://www.mdpi.com/2076-3417/10/22/7978pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectElectric Vehiclespt_PT
dc.subjectElitist nondominated sorting genetic algorithmpt_PT
dc.subjectMulti-objective optimizationpt_PT
dc.subjectOptimal resource schedulingpt_PT
dc.subjectVirtual power plantspt_PT
dc.titleMulti-Objective Electric Vehicles Scheduling Using Elitist Non-Dominated Sorting Genetic Algorithmpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/157466/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/9471 - RIDTI/150189/PT
oaire.citation.issue22pt_PT
oaire.citation.startPage7978pt_PT
oaire.citation.titleApplied Sciencespt_PT
oaire.citation.volume10pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream9471 - RIDTI
person.familyNameMorais
person.familyNameSousa
person.familyNameCastro
person.familyNameVale
person.givenNameHugo
person.givenNameTiago
person.givenNameRui
person.givenNameZita
person.identifier80878
person.identifier126036
person.identifier632184
person.identifier.ciencia-id2010-D878-271B
person.identifier.ciencia-id5C1D-2997-B7A7
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0001-5906-4744
person.identifier.orcid0000-0002-3704-562X
person.identifier.orcid0000-0002-3108-8880
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridB-9229-2019
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id21834170800
person.identifier.scopus-author-id36549396600
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
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