An approach based on neural networks for identification of fault sections in radial distribution systems

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dc.contributor.authorZiolkowski, Valmir
dc.contributor.authorDa Silva, Ivan Nunes
dc.contributor.authorFlauzino, Rogerio Andrade [UNESP]
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:22:02Z
dc.date.available2014-05-27T11:22:02Z
dc.date.issued2006-12-01
dc.description.abstractThe main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.en
dc.description.affiliationUniversity of São Paulo - USP Department of Electrical Engineering, CP 359, São Carlos, SP
dc.description.affiliationSão Paulo State University UNESP Department of Electrical Engineering, CP 473, Bauru, SP
dc.description.affiliationUnespSão Paulo State University UNESP Department of Electrical Engineering, CP 473, Bauru, SP
dc.format.extent25-30
dc.identifierhttp://dx.doi.org/10.1109/ICIT.2006.372351
dc.identifier.citationProceedings of the IEEE International Conference on Industrial Technology, p. 25-30.
dc.identifier.doi10.1109/ICIT.2006.372351
dc.identifier.scopus2-s2.0-51349143502
dc.identifier.urihttp://hdl.handle.net/11449/69237
dc.language.isoeng
dc.relation.ispartofProceedings of the IEEE International Conference on Industrial Technology
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectArtificial intelligence
dc.subjectAutomation
dc.subjectClassification (of information)
dc.subjectComputer networks
dc.subjectElectric fault location
dc.subjectElectric load distribution
dc.subjectElectric power systems
dc.subjectElectric power transmission
dc.subjectElectric tools
dc.subjectElectronic data interchange
dc.subjectFeeding
dc.subjectAutomatic identification
dc.subjectIndustrial technologies
dc.subjectInternational conferences
dc.subjectNeural networks
dc.titleAn approach based on neural networks for identification of fault sections in radial distribution systemsen
dc.typeTrabalho apresentado em evento
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Engenharia, Baurupt

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Artigos - Engenharia Elétrica - FEB