Risk assessment algorithm for power transformer fleets based on condition and strategic importance

Autores
Zaldivar Sanchez, Diego Armando; Romero Quete, Andrés Arturo; Rivera, Sergio R.
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In every electric power system, power transformers (PT) play a critical role. Under ideal circumstances, PT should receive the utmost care to maintain the highest operative condition during their lifetime. Through the years, different approaches have been developed to assess the condition and the inherent risk during the operation of PT. However, most proposed methodologies tend to analyze PT as individuals and not as a fleet. A fleet assessment helps the asset manager make sound decisions regarding the maintenance scheduling for groups of PT with similar conditions. This paper proposes a new methodology to assess the risk of PT fleets, considering the technical condition and the strategic importance of the units. First, the state of the units was evaluated using a health index (HI) with a fuzzy logic algorithm. Then, the strategic importance of each unit was assessed using a weighting technique to obtain the importance index (II). Finally, the analyzed units with similar HI and II were arranged into a set of clusters using the k-means clustering technique. A fleet of 19 PTs was used to validate the proposed method. The obtained results are also provided to demonstrate the viability and feasibility of the assessment model.
Fil: Zaldivar Sanchez, Diego Armando. 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: Romero Quete, Andrés Arturo. 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: Rivera, Sergio R.. Universidad Nacional de Colombia; Colombia
Materia
risk assessment
health index
power transformers
fuzzy logic
importance index
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:11336/179031
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/179031
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Risk assessment algorithm for power transformer fleets based on condition and strategic importanceZaldivar Sanchez, Diego ArmandoRomero Quete, Andrés ArturoRivera, Sergio R.risk assessmenthealth indexpower transformersfuzzy logicimportance indexhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2In every electric power system, power transformers (PT) play a critical role. Under ideal circumstances, PT should receive the utmost care to maintain the highest operative condition during their lifetime. Through the years, different approaches have been developed to assess the condition and the inherent risk during the operation of PT. However, most proposed methodologies tend to analyze PT as individuals and not as a fleet. A fleet assessment helps the asset manager make sound decisions regarding the maintenance scheduling for groups of PT with similar conditions. This paper proposes a new methodology to assess the risk of PT fleets, considering the technical condition and the strategic importance of the units. First, the state of the units was evaluated using a health index (HI) with a fuzzy logic algorithm. Then, the strategic importance of each unit was assessed using a weighting technique to obtain the importance index (II). Finally, the analyzed units with similar HI and II were arranged into a set of clusters using the k-means clustering technique. A fleet of 19 PTs was used to validate the proposed method. The obtained results are also provided to demonstrate the viability and feasibility of the assessment model.Fil: Zaldivar Sanchez, Diego Armando. 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: Romero Quete, Andrés Arturo. 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: Rivera, Sergio R.. Universidad Nacional de Colombia; ColombiaMultidisciplinary Digital Publishing Institute2021-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/179031Zaldivar Sanchez, Diego Armando; Romero Quete, Andrés Arturo; Rivera, Sergio R.; Risk assessment algorithm for power transformer fleets based on condition and strategic importance; Multidisciplinary Digital Publishing Institute; Algorithms; 14; 11; 10-2021; 1-131999-4893CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/1999-4893/14/11/319info:eu-repo/semantics/altIdentifier/doi/10.3390/a14110319info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:44:54Zoai:ri.conicet.gov.ar:11336/179031instacron: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:34982025-09-29 09:44:55.121CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Risk assessment algorithm for power transformer fleets based on condition and strategic importance
title Risk assessment algorithm for power transformer fleets based on condition and strategic importance
spellingShingle Risk assessment algorithm for power transformer fleets based on condition and strategic importance
Zaldivar Sanchez, Diego Armando
risk assessment
health index
power transformers
fuzzy logic
importance index
title_short Risk assessment algorithm for power transformer fleets based on condition and strategic importance
title_full Risk assessment algorithm for power transformer fleets based on condition and strategic importance
title_fullStr Risk assessment algorithm for power transformer fleets based on condition and strategic importance
title_full_unstemmed Risk assessment algorithm for power transformer fleets based on condition and strategic importance
title_sort Risk assessment algorithm for power transformer fleets based on condition and strategic importance
dc.creator.none.fl_str_mv Zaldivar Sanchez, Diego Armando
Romero Quete, Andrés Arturo
Rivera, Sergio R.
author Zaldivar Sanchez, Diego Armando
author_facet Zaldivar Sanchez, Diego Armando
Romero Quete, Andrés Arturo
Rivera, Sergio R.
author_role author
author2 Romero Quete, Andrés Arturo
Rivera, Sergio R.
author2_role author
author
dc.subject.none.fl_str_mv risk assessment
health index
power transformers
fuzzy logic
importance index
topic risk assessment
health index
power transformers
fuzzy logic
importance index
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv In every electric power system, power transformers (PT) play a critical role. Under ideal circumstances, PT should receive the utmost care to maintain the highest operative condition during their lifetime. Through the years, different approaches have been developed to assess the condition and the inherent risk during the operation of PT. However, most proposed methodologies tend to analyze PT as individuals and not as a fleet. A fleet assessment helps the asset manager make sound decisions regarding the maintenance scheduling for groups of PT with similar conditions. This paper proposes a new methodology to assess the risk of PT fleets, considering the technical condition and the strategic importance of the units. First, the state of the units was evaluated using a health index (HI) with a fuzzy logic algorithm. Then, the strategic importance of each unit was assessed using a weighting technique to obtain the importance index (II). Finally, the analyzed units with similar HI and II were arranged into a set of clusters using the k-means clustering technique. A fleet of 19 PTs was used to validate the proposed method. The obtained results are also provided to demonstrate the viability and feasibility of the assessment model.
Fil: Zaldivar Sanchez, Diego Armando. 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: Romero Quete, Andrés Arturo. 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: Rivera, Sergio R.. Universidad Nacional de Colombia; Colombia
description In every electric power system, power transformers (PT) play a critical role. Under ideal circumstances, PT should receive the utmost care to maintain the highest operative condition during their lifetime. Through the years, different approaches have been developed to assess the condition and the inherent risk during the operation of PT. However, most proposed methodologies tend to analyze PT as individuals and not as a fleet. A fleet assessment helps the asset manager make sound decisions regarding the maintenance scheduling for groups of PT with similar conditions. This paper proposes a new methodology to assess the risk of PT fleets, considering the technical condition and the strategic importance of the units. First, the state of the units was evaluated using a health index (HI) with a fuzzy logic algorithm. Then, the strategic importance of each unit was assessed using a weighting technique to obtain the importance index (II). Finally, the analyzed units with similar HI and II were arranged into a set of clusters using the k-means clustering technique. A fleet of 19 PTs was used to validate the proposed method. The obtained results are also provided to demonstrate the viability and feasibility of the assessment model.
publishDate 2021
dc.date.none.fl_str_mv 2021-10
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/11336/179031
Zaldivar Sanchez, Diego Armando; Romero Quete, Andrés Arturo; Rivera, Sergio R.; Risk assessment algorithm for power transformer fleets based on condition and strategic importance; Multidisciplinary Digital Publishing Institute; Algorithms; 14; 11; 10-2021; 1-13
1999-4893
CONICET Digital
CONICET
url http://hdl.handle.net/11336/179031
identifier_str_mv Zaldivar Sanchez, Diego Armando; Romero Quete, Andrés Arturo; Rivera, Sergio R.; Risk assessment algorithm for power transformer fleets based on condition and strategic importance; Multidisciplinary Digital Publishing Institute; Algorithms; 14; 11; 10-2021; 1-13
1999-4893
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/1999-4893/14/11/319
info:eu-repo/semantics/altIdentifier/doi/10.3390/a14110319
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 Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
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 13.070432

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