Spatial-temporal simulation to estimate the load demand of battery electric vehicles charging in small residential areas

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dc.contributor.authorMelo, Joel D. [UNESP]
dc.contributor.authorCarreno, Edgar M.
dc.contributor.authorPadilha-Feltrin, Antonio [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionCenter for Engineering and Mathematical Sciences-CECE, University of the State University of West Parana-UNIOESTE
dc.date.accessioned2018-12-11T16:56:15Z
dc.date.available2018-12-11T16:56:15Z
dc.date.issued2014-01-01
dc.description.abstractThis paper presents a spatial-temporal approach for estimating the load demand of battery electric vehicles (BEV) charging in small residential areas. This approach is especially suited for simulating the driving pattern of BEVs in cities without this kind of information. The service zone is divided into several sub-zones; each of these has a probability that represents how likely it is for a BEVs to cross the sub-zone. The driving pattern of BEVs is simulated using a multi-agent framework, which estimates the spatial distribution of these in a city. To determine the hourly charge in each place identified in the spatial area, the model considers the battery charging profile via two charging scenarios. The main contribution of this method is the estimation of BEV charging in feeders or transformers using small-scale simulation. The proposed approach was tested on a real distribution system of a mid-sized city in Brazil. For this specific system, the simulation was able to identify two different levels of agglomerations; when the worst-case scenario with a 20 % penetration is analyzed, an increase in peak demand up to 34.04 % was determined in the most affected part of the distribution system while the rest of the distribution system is almost unaffected. © 2014 Brazilian Society for Automatics - SBA.en
dc.description.affiliationDepartment of Electrical Engineering, University of the State of Sao Paulo-UNESP, Ilha Solteira SP
dc.description.affiliationCenter for Engineering and Mathematical Sciences-CECE, University of the State University of West Parana-UNIOESTE, Iguaçu PR
dc.description.affiliationUnespDepartment of Electrical Engineering, University of the State of Sao Paulo-UNESP, Ilha Solteira SP
dc.format.extent470-480
dc.identifierhttp://dx.doi.org/10.1007/s40313-014-0111-0
dc.identifier.citationJournal of Control, Automation and Electrical Systems, v. 25, n. 4, p. 470-480, 2014.
dc.identifier.doi10.1007/s40313-014-0111-0
dc.identifier.file2-s2.0-84903727807.pdf
dc.identifier.issn2195-3899
dc.identifier.issn2195-3880
dc.identifier.scopus2-s2.0-84903727807
dc.identifier.urihttp://hdl.handle.net/11449/171615
dc.language.isoeng
dc.relation.ispartofJournal of Control, Automation and Electrical Systems
dc.relation.ispartofsjr0,274
dc.relation.ispartofsjr0,274
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectBattery electric vehicle
dc.subjectDistribution planning
dc.subjectLoad estimation
dc.subjectMulti-agent
dc.subjectPercolation theory.
dc.titleSpatial-temporal simulation to estimate the load demand of battery electric vehicles charging in small residential areasen
dc.typeArtigo
unesp.author.lattes3886842168147059[3]
unesp.author.orcid0000-0001-6495-440X[3]

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