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The Impacts of Battery Electric Vehicles on the Power Grid: A Monte Carlo Method Approach

2021Journal article Open access
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dc.contributor.authorNogueira, Teresa
dc.contributor.authorMagano, José
dc.contributor.authorSousa, Ezequiel
dc.contributor.authorAlves, Gustavo R.
dc.date.accessioned2022-05-02T13:31:08Z
dc.date.available2022-05-02T13:31:08Z
dc.date.issued2021
dc.description.abstractBalancing energy demand and supply will become an even greater challenge considering the ongoing transition from traditional fuel to electric vehicles (EV). The management of this task will heavily depend on the pace of the adoption of light-duty EVs. Electric vehicles have seen their market share increase worldwide; the same is happening in Portugal, partly because the government has kept incentives for consumers to purchase EVs, despite the COVID-19 pandemic. The consequent shift to EVs entails various challenges for the distribution network, including coping with the expected growing demand for power. This article addresses this concern by presenting a case study of an area comprising 20 municipalities in Northern Portugal, for which battery electric vehicles (BEV) sales and their impact on distribution networks are estimated within the 2030 horizon. The power required from the grid is estimated under three BEV sales growth deterministic scenarios based on a daily consumption rate resulting from the combination of long- and short-distance routes. A Monte Carlo computational simulation is run to account for uncertainty under severe EV sales growth. The analysis is carried out considering three popular BEV models in Portugal, namely the Nissan Leaf, Tesla Model 3, and Renault Zoe. Their impacts on the available power of the distribution network are calculated for peak and off-peak hours. The results suggest that the current power grid capacity will not cope with demand increases as early as 2026. The modeling approach could be replicated in other regions with adjusted parameters.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/en14238102pt_PT
dc.identifier.issn1996-1073
dc.identifier.urihttp://hdl.handle.net/10400.22/20426
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationCenter for Innovation in Industrial Engineering and Technology
dc.relation.publisherversionhttps://www.mdpi.com/1996-1073/14/23/8102pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectBEVpt_PT
dc.subjectPHEVpt_PT
dc.subjectElectric vehiclespt_PT
dc.subjectEV salespt_PT
dc.subjectEnergy demandpt_PT
dc.subjectDistribution gridpt_PT
dc.subjectPower impactpt_PT
dc.titleThe Impacts of Battery Electric Vehicles on the Power Grid: A Monte Carlo Method Approachpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCenter for Innovation in Industrial Engineering and Technology
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04730%2F2020/PT
oaire.citation.issue23pt_PT
oaire.citation.startPage8102pt_PT
oaire.citation.titleEnergiespt_PT
oaire.citation.volume14pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameNogueira
person.familyNameSousa
person.familyNameAlves
person.givenNameTeresa
person.givenNameEzequiel
person.givenNameGustavo
person.identifier447885
person.identifier150015
person.identifier.ciencia-idFA1A-23A9-9DA3
person.identifier.ciencia-id4210-4DF2-5206
person.identifier.orcid0000-0001-9904-7527
person.identifier.orcid0000-0003-4046-5876
person.identifier.orcid0000-0002-1244-8502
person.identifier.ridQ-6796-2016
person.identifier.ridI-7876-2014
person.identifier.scopus-author-id24802401000
person.identifier.scopus-author-id7006053908
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublicationca6f043e-777a-40d2-a243-6a6d48ca23b9
relation.isAuthorOfPublication01800568-7eaf-41d9-b78d-cf64f7c7381d
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