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dc.contributor.authorMelo, J. D. [UNESP]
dc.contributor.authorPadilha-Feltrin, A. [UNESP]
dc.contributor.authorCarreno, E. M.
dc.date.accessioned2018-12-11T17:25:09Z
dc.date.available2018-12-11T17:25:09Z
dc.date.issued2014-01-01
dc.identifierhttp://dx.doi.org/10.1109/PESGM.2014.6939848
dc.identifier.citationIEEE Power and Energy Society General Meeting, v. 2014-October, n. October, 2014.
dc.identifier.issn1944-9933
dc.identifier.issn1944-9925
dc.identifier.urihttp://hdl.handle.net/11449/177374
dc.description.abstractThe magnitude and geographic location of electricity demand in the planning horizon are vital pieces of information for power distribution companies in planning future network expansion and operation. Such information is often obtained through spatial load forecasting. Several methods have been developed using different data sources as inputs, depending on their availability; however, many of the advanced spatial load forecasting methods have not yet been widely used because of the size, variety, and availability of the data required. This paper presents a review of the different spatial load forecasting techniques developed in the last 10 years, focusing particularly on the evolution of the required input data, as well as some insights on how current and future technologies could be used to improve spatial load forecasting practices.en
dc.language.isoeng
dc.relation.ispartofIEEE Power and Energy Society General Meeting
dc.sourceScopus
dc.subjectExpansion planning of distribution system
dc.subjectgeographic information system
dc.subjectpower distribution system
dc.subjectspatial load forecasting
dc.titleData issues in spatial electric load forecastingen
dc.typeTrabalho apresentado em evento
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionCenter for Engineering and Mathematical Sciences, West Parana State University, UNIOESTE
dc.description.affiliationDept. Electrical Engineering, University of the State of Sao Paulo, UNESP
dc.description.affiliationCenter for Engineering and Mathematical Sciences, West Parana State University, UNIOESTE
dc.description.affiliationUnespDept. Electrical Engineering, University of the State of Sao Paulo, UNESP
dc.identifier.doi10.1109/PESGM.2014.6939848
dc.rights.accessRightsAcesso aberto
dc.identifier.scopus2-s2.0-84931003497
unesp.author.lattes3886842168147059[2]
unesp.author.orcid0000-0001-6495-440X[2]
dc.relation.ispartofsjr0,328
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