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dc.contributor.authorCarreno, E. M.-
dc.contributor.authorPadilha-Feltrin, A.-
dc.contributor.authorLeal, A. G.-
dc.identifier.citationSba: Controle & Automação Sociedade Brasileira de Automatica. Sociedade Brasileira de Automática, v. 21, n. 4, p. 379-388, 2010.-
dc.description.abstractA method for spatial electric load forecasting using elements from evolutionary algorithms is presented. The method uses concepts from knowledge extraction algorithms and linguistic rules' representation to characterize the preferences for land use into a spatial database. The future land use preferences in undeveloped zones in the electrical utility service area are determined using an evolutionary heuristic, which considers a stochastic behavior by crossing over similar rules. The method considers development of new zones and also redevelopment of existing ones. The results are presented in future preference maps. The tests in a real system from a midsized city show a high rate of success when results are compared with information gathered from the utility planning department. The most important features of this method are the need for few data and the simplicity of the algorithm, allowing for future scalability.en
dc.publisherSociedade Brasileira de Automática-
dc.subjectSpatial electric load forecastingen
dc.subjectland useen
dc.subjectknowledge extractionen
dc.subjectdistribution planningen
dc.titleSpatial electric load forecasting using an evolutionary heuristicen
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionELUCID SOLUTIONS-
dc.description.affiliationUNESP Faculdade de Engenharia de Ilha Solteira-
dc.description.affiliationELUCID SOLUTIONS-
dc.description.affiliationUnespUNESP Faculdade de Engenharia de Ilha Solteira-
dc.rights.accessRightsAcesso aberto-
dc.relation.ispartofSba: Controle & Automação Sociedade Brasileira de Automatica-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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