Fault identification in distribution lines using intelligent systems and statistical methods

Detalhes bibliográficos
Autor(a) principal: Ziolkowski, Valmir
Data de Publicação: 2006
Outros Autores: Da Silva, Ivan Nunes, Flauzino, Rogerio [UNESP], Ulson, Jose Alfredo Covolan [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/MELCON.2006.1653297
http://hdl.handle.net/11449/69247
Resumo: The 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 distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder. © 2006 IEEE.
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spelling Fault identification in distribution lines using intelligent systems and statistical methodsElectric linesElectric power distributionIntelligent systemsNeural networksStatistical methodsDistribution linesFault identificationElectric fault currentsThe 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 distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder. © 2006 IEEE.ELEKTRO Electricity Company, Rua Ary Antenor de Souza, 321, Campinas, SPUniversity of São Paulo - USP Department of Electrical Engineering, CP 359, São Carlos, SPSão Paulo State University - UNESP Department of Electrical Engineering, CP 473, Bauru, SPSão Paulo State University - UNESP Department of Electrical Engineering, CP 473, Bauru, SPELEKTRO Electricity CompanyUniversidade de São Paulo (USP)Universidade Estadual Paulista (Unesp)Ziolkowski, ValmirDa Silva, Ivan NunesFlauzino, Rogerio [UNESP]Ulson, Jose Alfredo Covolan [UNESP]2014-05-27T11:22:03Z2014-05-27T11:22:03Z2006-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1122-1125http://dx.doi.org/10.1109/MELCON.2006.1653297Proceedings of the Mediterranean Electrotechnical Conference - MELECON, v. 2006, p. 1122-1125.http://hdl.handle.net/11449/6924710.1109/MELCON.2006.16532972-s2.0-340471395844517057121462258Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of the Mediterranean Electrotechnical Conference - MELECONinfo:eu-repo/semantics/openAccess2024-06-28T13:34:43Zoai:repositorio.unesp.br:11449/69247Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:07:18.945224Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Fault identification in distribution lines using intelligent systems and statistical methods
title Fault identification in distribution lines using intelligent systems and statistical methods
spellingShingle Fault identification in distribution lines using intelligent systems and statistical methods
Ziolkowski, Valmir
Electric lines
Electric power distribution
Intelligent systems
Neural networks
Statistical methods
Distribution lines
Fault identification
Electric fault currents
title_short Fault identification in distribution lines using intelligent systems and statistical methods
title_full Fault identification in distribution lines using intelligent systems and statistical methods
title_fullStr Fault identification in distribution lines using intelligent systems and statistical methods
title_full_unstemmed Fault identification in distribution lines using intelligent systems and statistical methods
title_sort Fault identification in distribution lines using intelligent systems and statistical methods
author Ziolkowski, Valmir
author_facet Ziolkowski, Valmir
Da Silva, Ivan Nunes
Flauzino, Rogerio [UNESP]
Ulson, Jose Alfredo Covolan [UNESP]
author_role author
author2 Da Silva, Ivan Nunes
Flauzino, Rogerio [UNESP]
Ulson, Jose Alfredo Covolan [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv ELEKTRO Electricity Company
Universidade de São Paulo (USP)
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Ziolkowski, Valmir
Da Silva, Ivan Nunes
Flauzino, Rogerio [UNESP]
Ulson, Jose Alfredo Covolan [UNESP]
dc.subject.por.fl_str_mv Electric lines
Electric power distribution
Intelligent systems
Neural networks
Statistical methods
Distribution lines
Fault identification
Electric fault currents
topic Electric lines
Electric power distribution
Intelligent systems
Neural networks
Statistical methods
Distribution lines
Fault identification
Electric fault currents
description The 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 distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder. © 2006 IEEE.
publishDate 2006
dc.date.none.fl_str_mv 2006-12-01
2014-05-27T11:22:03Z
2014-05-27T11:22:03Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/MELCON.2006.1653297
Proceedings of the Mediterranean Electrotechnical Conference - MELECON, v. 2006, p. 1122-1125.
http://hdl.handle.net/11449/69247
10.1109/MELCON.2006.1653297
2-s2.0-34047139584
4517057121462258
url http://dx.doi.org/10.1109/MELCON.2006.1653297
http://hdl.handle.net/11449/69247
identifier_str_mv Proceedings of the Mediterranean Electrotechnical Conference - MELECON, v. 2006, p. 1122-1125.
10.1109/MELCON.2006.1653297
2-s2.0-34047139584
4517057121462258
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Proceedings of the Mediterranean Electrotechnical Conference - MELECON
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1122-1125
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808129394004197376

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