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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/116571
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dc.contributor.authorLeao, Fabio Bertequini-
dc.contributor.authorPereira, Rodrigo A. F.-
dc.contributor.authorMantovani, Jose R. S.-
dc.date.accessioned2015-03-18T15:53:31Z-
dc.date.accessioned2016-10-25T20:25:06Z-
dc.date.available2015-03-18T15:53:31Z-
dc.date.available2016-10-25T20:25:06Z-
dc.date.issued2014-12-01-
dc.identifierhttp://dx.doi.org/10.1016/j.ijepes.2014.06.052-
dc.identifier.citationInternational Journal Of Electrical Power & Energy Systems. Oxford: Elsevier Sci Ltd, v. 63, p. 787-805, 2014.-
dc.identifier.issn0142-0615-
dc.identifier.urihttp://hdl.handle.net/11449/116571-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/116571-
dc.description.abstractThis paper presents a novel mathematical model for fast fault section estimation in a Distribution Control Center (DCC). The mathematical model is divided into two parts, namely: (1) a protection system operations model based on operator's heuristic knowledge of the protection system performance and (2) an optimization Unconstrained Binary Programming (UBP) model based on parsimonious covering theory. In order to solve the UBP model, an Adaptive Genetic Algorithm (AGA) using crossing over and mutation rates that are automatically tuned in each generation is proposed. An Alarm Probabilistic Generator Algorithm (APGA) is developed and a real four-interconnected distribution substation system is used to test exhaustively the approach. Results show that the proposed methodology is capable of performing fault section estimation in a very fast and reliable manner. Furthermore, the proposed methodology is a powerful real-time fault diagnosis tool for application in future Distribution Control Centers. (C) 2014 Elsevier Ltd. All rights reserved.en
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
dc.format.extent787-805-
dc.language.isoeng-
dc.publisherElsevier B.V.-
dc.sourceWeb of Science-
dc.subjectDistribution control centersen
dc.subjectFault section estimationen
dc.subjectFault diagnosisen
dc.subjectProtective relayingen
dc.subjectDigital protectionen
dc.subjectGenetic algorithmen
dc.titleFast fault section estimation in distribution control centers using adaptive genetic algorithmen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationSao Paulo State Univ UNESP, Dept Elect Engn, Res Grp Elect Power Syst Planning, BR-15385000 Ilha Solteira, Brazil-
dc.description.affiliationUnespSao Paulo State Univ UNESP, Dept Elect Engn, Res Grp Elect Power Syst Planning, BR-15385000 Ilha Solteira, Brazil-
dc.description.sponsorshipIdFAPESP: 06/02569-7-
dc.description.sponsorshipIdCNPq: 305371-2012-6-
dc.identifier.doi10.1016/j.ijepes.2014.06.052-
dc.identifier.wosWOS:000341336700085-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofInternational Journal Of Electrical Power & Energy Systems-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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