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

Detalhes bibliográficos
Autor(a) principal: Ziolkowski, Valmir
Data de Publicação: 2006
Outros Autores: Silva, Ivan Nunes da, Flauzino, Rogerio Andrade [UNESP], IEEE
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/195878
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 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.
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spelling An approach based on neural networks for identification of fault sections in radial distribution systemsThe 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.Univ Sao Paulo, Dept Elect Engn, CP 359, Sao Carlos, SP, BrazilUNESP, Sao Paulo State Univ, Dept Elect Engn, Bauru, SP, BrazilUNESP, Sao Paulo State Univ, Dept Elect Engn, Bauru, SP, BrazilIeeeUniversidade de São Paulo (USP)Universidade Estadual Paulista (Unesp)Ziolkowski, ValmirSilva, Ivan Nunes daFlauzino, Rogerio Andrade [UNESP]IEEE2020-12-10T18:06:22Z2020-12-10T18:06:22Z2006-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject2078-+2006 Ieee International Conference On Industrial Technology, Vols 1-6. New York: Ieee, p. 2078-+, 2006.http://hdl.handle.net/11449/195878WOS:000248430904005Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2006 Ieee International Conference On Industrial Technology, Vols 1-6info:eu-repo/semantics/openAccess2024-06-28T13:34:35Zoai:repositorio.unesp.br:11449/195878Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T14:55:36.328780Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv An approach based on neural networks for identification of fault sections in radial distribution systems
title An approach based on neural networks for identification of fault sections in radial distribution systems
spellingShingle An approach based on neural networks for identification of fault sections in radial distribution systems
Ziolkowski, Valmir
title_short An approach based on neural networks for identification of fault sections in radial distribution systems
title_full An approach based on neural networks for identification of fault sections in radial distribution systems
title_fullStr An approach based on neural networks for identification of fault sections in radial distribution systems
title_full_unstemmed An approach based on neural networks for identification of fault sections in radial distribution systems
title_sort An approach based on neural networks for identification of fault sections in radial distribution systems
author Ziolkowski, Valmir
author_facet Ziolkowski, Valmir
Silva, Ivan Nunes da
Flauzino, Rogerio Andrade [UNESP]
IEEE
author_role author
author2 Silva, Ivan Nunes da
Flauzino, Rogerio Andrade [UNESP]
IEEE
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade de São Paulo (USP)
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Ziolkowski, Valmir
Silva, Ivan Nunes da
Flauzino, Rogerio Andrade [UNESP]
IEEE
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 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.
publishDate 2006
dc.date.none.fl_str_mv 2006-01-01
2020-12-10T18:06:22Z
2020-12-10T18:06:22Z
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 2006 Ieee International Conference On Industrial Technology, Vols 1-6. New York: Ieee, p. 2078-+, 2006.
http://hdl.handle.net/11449/195878
WOS:000248430904005
identifier_str_mv 2006 Ieee International Conference On Industrial Technology, Vols 1-6. New York: Ieee, p. 2078-+, 2006.
WOS:000248430904005
url http://hdl.handle.net/11449/195878
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2006 Ieee International Conference On Industrial Technology, Vols 1-6
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 2078-+
dc.publisher.none.fl_str_mv Ieee
publisher.none.fl_str_mv Ieee
dc.source.none.fl_str_mv Web of Science
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
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