Power Transformer Condition Assessment Using DGA and FRA

Autores
Gonzales Arispe, Jimmy Cesar; Mombello, Enrique Esteban
Año de publicación
2016
Idioma
español castellano
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Power transformer condition assessment is a very complex task but also of high priority for power system reliability. Several diagnosis techniques have been published, specifically; insulation system condition assessment (paper and oil) using Dissolve Gas Analysis (DGA), and to assess winding and core condition, using Frequency Response Analysis (FRA). Results of these different techniques represent complementary or corroborative information of the final transformer condition. Therefore, unification of both techniques information helps to assess accurately transformer condition, which is very important in transformers management field and its failure risk estimation. In this paper, a novel method for DGA and FRA results unification is proposed, which is based on fuzzy sets application in failures detection and interpretation stages.
Fil: Gonzales Arispe, Jimmy Cesar. 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: Mombello, Enrique Esteban. 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
Materia
Dissolve Gas Analysis
Frequency Response Analysis
Fuzzy Sets
Power Transformer
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/61246
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Power Transformer Condition Assessment Using DGA and FRAGonzales Arispe, Jimmy CesarMombello, Enrique EstebanDissolve Gas AnalysisFrequency Response AnalysisFuzzy SetsPower Transformerhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2Power transformer condition assessment is a very complex task but also of high priority for power system reliability. Several diagnosis techniques have been published, specifically; insulation system condition assessment (paper and oil) using Dissolve Gas Analysis (DGA), and to assess winding and core condition, using Frequency Response Analysis (FRA). Results of these different techniques represent complementary or corroborative information of the final transformer condition. Therefore, unification of both techniques information helps to assess accurately transformer condition, which is very important in transformers management field and its failure risk estimation. In this paper, a novel method for DGA and FRA results unification is proposed, which is based on fuzzy sets application in failures detection and interpretation stages.Fil: Gonzales Arispe, Jimmy Cesar. 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: Mombello, Enrique Esteban. 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; ArgentinaInstitute of Electrical and Electronics Engineers2016-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/61246Gonzales Arispe, Jimmy Cesar; Mombello, Enrique Esteban; Power Transformer Condition Assessment Using DGA and FRA; Institute of Electrical and Electronics Engineers; IEEE Latin America Transactions; 14; 11; 11-2016; 4527-45331548-0992CONICET DigitalCONICETspainfo:eu-repo/semantics/altIdentifier/doi/10.1109/TLA.2016.7795824info:eu-repo/semantics/altIdentifier/url/https://ieeexplore.ieee.org/document/7795824info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:30:32Zoai:ri.conicet.gov.ar:11336/61246instacron: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:34982025-10-15 14:30:32.373CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Power Transformer Condition Assessment Using DGA and FRA
title Power Transformer Condition Assessment Using DGA and FRA
spellingShingle Power Transformer Condition Assessment Using DGA and FRA
Gonzales Arispe, Jimmy Cesar
Dissolve Gas Analysis
Frequency Response Analysis
Fuzzy Sets
Power Transformer
title_short Power Transformer Condition Assessment Using DGA and FRA
title_full Power Transformer Condition Assessment Using DGA and FRA
title_fullStr Power Transformer Condition Assessment Using DGA and FRA
title_full_unstemmed Power Transformer Condition Assessment Using DGA and FRA
title_sort Power Transformer Condition Assessment Using DGA and FRA
dc.creator.none.fl_str_mv Gonzales Arispe, Jimmy Cesar
Mombello, Enrique Esteban
author Gonzales Arispe, Jimmy Cesar
author_facet Gonzales Arispe, Jimmy Cesar
Mombello, Enrique Esteban
author_role author
author2 Mombello, Enrique Esteban
author2_role author
dc.subject.none.fl_str_mv Dissolve Gas Analysis
Frequency Response Analysis
Fuzzy Sets
Power Transformer
topic Dissolve Gas Analysis
Frequency Response Analysis
Fuzzy Sets
Power Transformer
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Power transformer condition assessment is a very complex task but also of high priority for power system reliability. Several diagnosis techniques have been published, specifically; insulation system condition assessment (paper and oil) using Dissolve Gas Analysis (DGA), and to assess winding and core condition, using Frequency Response Analysis (FRA). Results of these different techniques represent complementary or corroborative information of the final transformer condition. Therefore, unification of both techniques information helps to assess accurately transformer condition, which is very important in transformers management field and its failure risk estimation. In this paper, a novel method for DGA and FRA results unification is proposed, which is based on fuzzy sets application in failures detection and interpretation stages.
Fil: Gonzales Arispe, Jimmy Cesar. 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: Mombello, Enrique Esteban. 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
description Power transformer condition assessment is a very complex task but also of high priority for power system reliability. Several diagnosis techniques have been published, specifically; insulation system condition assessment (paper and oil) using Dissolve Gas Analysis (DGA), and to assess winding and core condition, using Frequency Response Analysis (FRA). Results of these different techniques represent complementary or corroborative information of the final transformer condition. Therefore, unification of both techniques information helps to assess accurately transformer condition, which is very important in transformers management field and its failure risk estimation. In this paper, a novel method for DGA and FRA results unification is proposed, which is based on fuzzy sets application in failures detection and interpretation stages.
publishDate 2016
dc.date.none.fl_str_mv 2016-11
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/11336/61246
Gonzales Arispe, Jimmy Cesar; Mombello, Enrique Esteban; Power Transformer Condition Assessment Using DGA and FRA; Institute of Electrical and Electronics Engineers; IEEE Latin America Transactions; 14; 11; 11-2016; 4527-4533
1548-0992
CONICET Digital
CONICET
url http://hdl.handle.net/11336/61246
identifier_str_mv Gonzales Arispe, Jimmy Cesar; Mombello, Enrique Esteban; Power Transformer Condition Assessment Using DGA and FRA; Institute of Electrical and Electronics Engineers; IEEE Latin America Transactions; 14; 11; 11-2016; 4527-4533
1548-0992
CONICET Digital
CONICET
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1109/TLA.2016.7795824
info:eu-repo/semantics/altIdentifier/url/https://ieeexplore.ieee.org/document/7795824
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
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
_version_ 1846082783181537280
score 13.22299

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