A novel approach to arcing faults characterization using multivariable analysis and support vector machine

Autores
Morales Garcia, John Armando; Muñoz, Eduardo; Orduña, Eduardo Agustín; Idarraga Ospina, Gina Maria
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Based on the Institute of Electrical and Electronics Engineers (IEEE) Standard C37.104-2012 Power Systems Relaying Committee report, topics related to auto-reclosing in transmission lines have been considered as an imperative benefit for electric power systems. An important issue in reclosing, when performed correctly, is identifying the fault type, i.e., permanent or temporary, which keeps the faulted transmission line in service as long as possible. In this paper, a multivariable analysis was used to classify signals as permanent and temporary faults. Thus, by using a simple convolution process among the mother functions called eigenvectors and the fault signals from a single end, a dimensionality reduction was determined. In this manner, the feature classifier based on the support vector machine was used for acceptably classifying fault types. The algorithm was tested in different fault scenarios that considered several distances along the transmission line and representation of first and second arcs simulated in the alternative transients program ATP software. Therefore, the main contribution of the analysis performed in this paper is to propose a novel algorithm to discriminate permanent and temporary faults based on the behavior of the faulted phase voltage after single-phase opening of the circuit breakers. Several simulations let the authors conclude that the proposed algorithm is effective and reliable.
Fil: Morales Garcia, John Armando. Universidad Politecnica Salesiana; Ecuador. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentina
Fil: Muñoz, Eduardo. Universidad Politecnica Salesiana; Ecuador
Fil: Orduña, Eduardo Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentina
Fil: Idarraga Ospina, Gina Maria. Universidad Autónoma de Nuevo León; México
Materia
ARCING FAULT IDENTIFICATION
AUTORECLOSURE
RELAY
TRANSIENT ANALYSIS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/124804
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A novel approach to arcing faults characterization using multivariable analysis and support vector machineMorales Garcia, John ArmandoMuñoz, EduardoOrduña, Eduardo AgustínIdarraga Ospina, Gina MariaARCING FAULT IDENTIFICATIONAUTORECLOSURERELAYTRANSIENT ANALYSIShttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2Based on the Institute of Electrical and Electronics Engineers (IEEE) Standard C37.104-2012 Power Systems Relaying Committee report, topics related to auto-reclosing in transmission lines have been considered as an imperative benefit for electric power systems. An important issue in reclosing, when performed correctly, is identifying the fault type, i.e., permanent or temporary, which keeps the faulted transmission line in service as long as possible. In this paper, a multivariable analysis was used to classify signals as permanent and temporary faults. Thus, by using a simple convolution process among the mother functions called eigenvectors and the fault signals from a single end, a dimensionality reduction was determined. In this manner, the feature classifier based on the support vector machine was used for acceptably classifying fault types. The algorithm was tested in different fault scenarios that considered several distances along the transmission line and representation of first and second arcs simulated in the alternative transients program ATP software. Therefore, the main contribution of the analysis performed in this paper is to propose a novel algorithm to discriminate permanent and temporary faults based on the behavior of the faulted phase voltage after single-phase opening of the circuit breakers. Several simulations let the authors conclude that the proposed algorithm is effective and reliable.Fil: Morales Garcia, John Armando. Universidad Politecnica Salesiana; Ecuador. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Muñoz, Eduardo. Universidad Politecnica Salesiana; EcuadorFil: Orduña, Eduardo Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Idarraga Ospina, Gina Maria. Universidad Autónoma de Nuevo León; MéxicoMDPI2019-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/124804Morales Garcia, John Armando; Muñoz, Eduardo; Orduña, Eduardo Agustín; Idarraga Ospina, Gina Maria; A novel approach to arcing faults characterization using multivariable analysis and support vector machine; MDPI; Energies; 12; 11; 6-2019; 1-211996-1073CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/1996-1073/12/11/2126info:eu-repo/semantics/altIdentifier/doi/10.3390/en12112126info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:25:53Zoai:ri.conicet.gov.ar:11336/124804instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:25:53.885CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A novel approach to arcing faults characterization using multivariable analysis and support vector machine
title A novel approach to arcing faults characterization using multivariable analysis and support vector machine
spellingShingle A novel approach to arcing faults characterization using multivariable analysis and support vector machine
Morales Garcia, John Armando
ARCING FAULT IDENTIFICATION
AUTORECLOSURE
RELAY
TRANSIENT ANALYSIS
title_short A novel approach to arcing faults characterization using multivariable analysis and support vector machine
title_full A novel approach to arcing faults characterization using multivariable analysis and support vector machine
title_fullStr A novel approach to arcing faults characterization using multivariable analysis and support vector machine
title_full_unstemmed A novel approach to arcing faults characterization using multivariable analysis and support vector machine
title_sort A novel approach to arcing faults characterization using multivariable analysis and support vector machine
dc.creator.none.fl_str_mv Morales Garcia, John Armando
Muñoz, Eduardo
Orduña, Eduardo Agustín
Idarraga Ospina, Gina Maria
author Morales Garcia, John Armando
author_facet Morales Garcia, John Armando
Muñoz, Eduardo
Orduña, Eduardo Agustín
Idarraga Ospina, Gina Maria
author_role author
author2 Muñoz, Eduardo
Orduña, Eduardo Agustín
Idarraga Ospina, Gina Maria
author2_role author
author
author
dc.subject.none.fl_str_mv ARCING FAULT IDENTIFICATION
AUTORECLOSURE
RELAY
TRANSIENT ANALYSIS
topic ARCING FAULT IDENTIFICATION
AUTORECLOSURE
RELAY
TRANSIENT ANALYSIS
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Based on the Institute of Electrical and Electronics Engineers (IEEE) Standard C37.104-2012 Power Systems Relaying Committee report, topics related to auto-reclosing in transmission lines have been considered as an imperative benefit for electric power systems. An important issue in reclosing, when performed correctly, is identifying the fault type, i.e., permanent or temporary, which keeps the faulted transmission line in service as long as possible. In this paper, a multivariable analysis was used to classify signals as permanent and temporary faults. Thus, by using a simple convolution process among the mother functions called eigenvectors and the fault signals from a single end, a dimensionality reduction was determined. In this manner, the feature classifier based on the support vector machine was used for acceptably classifying fault types. The algorithm was tested in different fault scenarios that considered several distances along the transmission line and representation of first and second arcs simulated in the alternative transients program ATP software. Therefore, the main contribution of the analysis performed in this paper is to propose a novel algorithm to discriminate permanent and temporary faults based on the behavior of the faulted phase voltage after single-phase opening of the circuit breakers. Several simulations let the authors conclude that the proposed algorithm is effective and reliable.
Fil: Morales Garcia, John Armando. Universidad Politecnica Salesiana; Ecuador. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentina
Fil: Muñoz, Eduardo. Universidad Politecnica Salesiana; Ecuador
Fil: Orduña, Eduardo Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentina
Fil: Idarraga Ospina, Gina Maria. Universidad Autónoma de Nuevo León; México
description Based on the Institute of Electrical and Electronics Engineers (IEEE) Standard C37.104-2012 Power Systems Relaying Committee report, topics related to auto-reclosing in transmission lines have been considered as an imperative benefit for electric power systems. An important issue in reclosing, when performed correctly, is identifying the fault type, i.e., permanent or temporary, which keeps the faulted transmission line in service as long as possible. In this paper, a multivariable analysis was used to classify signals as permanent and temporary faults. Thus, by using a simple convolution process among the mother functions called eigenvectors and the fault signals from a single end, a dimensionality reduction was determined. In this manner, the feature classifier based on the support vector machine was used for acceptably classifying fault types. The algorithm was tested in different fault scenarios that considered several distances along the transmission line and representation of first and second arcs simulated in the alternative transients program ATP software. Therefore, the main contribution of the analysis performed in this paper is to propose a novel algorithm to discriminate permanent and temporary faults based on the behavior of the faulted phase voltage after single-phase opening of the circuit breakers. Several simulations let the authors conclude that the proposed algorithm is effective and reliable.
publishDate 2019
dc.date.none.fl_str_mv 2019-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/124804
Morales Garcia, John Armando; Muñoz, Eduardo; Orduña, Eduardo Agustín; Idarraga Ospina, Gina Maria; A novel approach to arcing faults characterization using multivariable analysis and support vector machine; MDPI; Energies; 12; 11; 6-2019; 1-21
1996-1073
CONICET Digital
CONICET
url http://hdl.handle.net/11336/124804
identifier_str_mv Morales Garcia, John Armando; Muñoz, Eduardo; Orduña, Eduardo Agustín; Idarraga Ospina, Gina Maria; A novel approach to arcing faults characterization using multivariable analysis and support vector machine; MDPI; Energies; 12; 11; 6-2019; 1-21
1996-1073
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/1996-1073/12/11/2126
info:eu-repo/semantics/altIdentifier/doi/10.3390/en12112126
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.982451

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