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Electric Vehicles’ User Charging Behaviour Simulator for a Smart City

dc.contributor.authorCanizes, Bruno
dc.contributor.authorSoares, João
dc.contributor.authorCosta, Ângelo
dc.contributor.authorPinto, Tiago
dc.contributor.authorLezama, Fernando
dc.contributor.authorNovais, Paulo
dc.contributor.authorVale, Zita
dc.date.accessioned2019-11-22T14:36:57Z
dc.date.available2019-11-22T14:36:57Z
dc.date.issued2019
dc.description.abstractThe increase of variable renewable energy generation has brought several new challenges to power and energy systems. Solutions based on storage systems and consumption flexibility are being proposed to balance the variability from generation sources that depend directly on environmental conditions. The widespread use of electric vehicles is seen as a resource that includes both distributed storage capabilities and the potential for consumption (charging) flexibility. However, to take advantage of the full potential of electric vehicles’ flexibility, it is essential that proper incentives are provided and that the management is performed with the variation of generation. This paper presents a research study on the impact of the variation of the electricity prices on the behavior of electric vehicle’s users. This study compared the benefits when using the variable and fixed charging prices. The variable prices are determined based on the calculation of distribution locational marginal pricing, which are recalculated and adapted continuously accordingly to the users’ trips and behavior. A travel simulation tool was developed for simulating real environments taking into account the behavior of real users. Results show that variable-rate of electricity prices demonstrate to be more advantageous to the users, enabling them to reduce charging costs while contributing to the required flexibility for the system.pt_PT
dc.description.sponsorshipThis work has received funding from FEDER Funds through COMPETE program, from National Funds through FCT projects UID/EEA/00760/2019 and UID/CEC/00319/2019 and PTDC/EEI-EEE/28983/2017-CENERGETIC. Bruno Canizes is supported by FCT Funds through SFRH/BD/110678/2015 PhD scholarship. Angelo Costa is supported by the FCT Post-Doc Grant SFRH/BPD/102696/2014.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/en12081470pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/14932
dc.language.isoengpt_PT
dc.publisherMDPIpt_PT
dc.relationPTDC/EEI-EEE/28983/2017-CENERGETICpt_PT
dc.relationResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
dc.relationALGORITMI Research Centre
dc.relation.publisherversionhttps://www.mdpi.com/1996-1073/12/8/1470pt_PT
dc.subjectElectric charging behaviourpt_PT
dc.subjectElectric mobilitypt_PT
dc.subjectEnergy pricespt_PT
dc.subjectEVspt_PT
dc.subjectTravel simulatorpt_PT
dc.titleElectric Vehicles’ User Charging Behaviour Simulator for a Smart Citypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
oaire.awardTitleALGORITMI Research Centre
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FEEA%2F00760%2F2019/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FCEC%2F00319%2F2019/PT
oaire.citation.issue8pt_PT
oaire.citation.startPage1470pt_PT
oaire.citation.titleEnergiespt_PT
oaire.citation.volume12pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
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person.familyNameSoares
person.familyNameCosta
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person.familyNameLezama
person.familyNameVale
person.givenNameBruno
person.givenNameJoão
person.givenNameÂngelo
person.givenNameTiago
person.givenNameFernando
person.givenNameZita
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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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