A practical method for risk assessment in power transformer fleets
ABSTRACT: A useful tool to support the decision-making process in power transformer management is risk assessment. There are few practical methodologies to assess a Transformer Risk Index (TRI). In addition, such proposals do not consider the latest advances in techniques for transformer health valu...
- Autores:
-
Romero Quete, Andrés Arturo
Gómez Montoya, Héctor David
Molina Castro, Juan David
Moreno Ospina, Germán
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2017
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- eng
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/23204
- Acceso en línea:
- http://hdl.handle.net/10495/23204
- Palabra clave:
- Diagnóstico
Diagnosis
Índice de Riesgo
Risk Index
Sistemas eléctricos
Electrical systems
Evaluación de riesgos
Risk assessment
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/2.5/co/
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| dc.title.spa.fl_str_mv |
A practical method for risk assessment in power transformer fleets |
| dc.title.alternative.spa.fl_str_mv |
Método práctico para la evaluación de riesgo en parques de transformadores de potencia |
| title |
A practical method for risk assessment in power transformer fleets |
| spellingShingle |
A practical method for risk assessment in power transformer fleets Diagnóstico Diagnosis Índice de Riesgo Risk Index Sistemas eléctricos Electrical systems Evaluación de riesgos Risk assessment |
| title_short |
A practical method for risk assessment in power transformer fleets |
| title_full |
A practical method for risk assessment in power transformer fleets |
| title_fullStr |
A practical method for risk assessment in power transformer fleets |
| title_full_unstemmed |
A practical method for risk assessment in power transformer fleets |
| title_sort |
A practical method for risk assessment in power transformer fleets |
| dc.creator.fl_str_mv |
Romero Quete, Andrés Arturo Gómez Montoya, Héctor David Molina Castro, Juan David Moreno Ospina, Germán |
| dc.contributor.author.none.fl_str_mv |
Romero Quete, Andrés Arturo Gómez Montoya, Héctor David Molina Castro, Juan David Moreno Ospina, Germán |
| dc.subject.decs.none.fl_str_mv |
Diagnóstico Diagnosis Índice de Riesgo Risk Index |
| topic |
Diagnóstico Diagnosis Índice de Riesgo Risk Index Sistemas eléctricos Electrical systems Evaluación de riesgos Risk assessment |
| dc.subject.lemb.none.fl_str_mv |
Sistemas eléctricos Electrical systems Evaluación de riesgos Risk assessment |
| description |
ABSTRACT: A useful tool to support the decision-making process in power transformer management is risk assessment. There are few practical methodologies to assess a Transformer Risk Index (TRI). In addition, such proposals do not consider the latest advances in techniques for transformer health valuation, and they also have other drawbacks. This paper proposes a practical method to undertake risk analysis of power transformer fleets, which deal with the stated problem. The proposal appropriately considers the best attributes of the methods reported in literature in order to compute the two components of TRI, i.e., the failure probability factor and the consequence factor. Moreover, this paper contributes to the risk analysis issue by including risk matrices and clustering techniques to support the decision-making process. The presented method was tested on a fleet of fourteen transformers. This approach serves as a practical and reliable tool for asset management in power utilities. |
| publishDate |
2017 |
| dc.date.issued.none.fl_str_mv |
2017 |
| dc.date.accessioned.none.fl_str_mv |
2021-10-15T16:47:35Z |
| dc.date.available.none.fl_str_mv |
2021-10-15T16:47:35Z |
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info:eu-repo/semantics/article |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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https://purl.org/redcol/resource_type/ART |
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Artículo de investigación |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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publishedVersion |
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0012-7353 |
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http://hdl.handle.net/10495/23204 |
| dc.identifier.doi.none.fl_str_mv |
10.15446/dyna.v84n200.54364 |
| dc.identifier.eissn.none.fl_str_mv |
2346-2183 |
| identifier_str_mv |
0012-7353 10.15446/dyna.v84n200.54364 2346-2183 |
| url |
http://hdl.handle.net/10495/23204 |
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eng |
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eng |
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Dyna |
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info:eu-repo/semantics/openAccess |
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http://creativecommons.org/licenses/by-nc-nd/2.5/co/ |
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https://creativecommons.org/licenses/by-nc-nd/4.0/ |
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openAccess |
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| dc.publisher.spa.fl_str_mv |
Universidad Nacional de Colombia, Facultad de Minas, Centro de Publicaciones |
| dc.publisher.group.spa.fl_str_mv |
Grupo de Manejo Eficiente de la Energía (GIMEL) |
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Medellín, Colombia |
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Universidad de Antioquia |
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Romero Quete, Andrés ArturoGómez Montoya, Héctor DavidMolina Castro, Juan DavidMoreno Ospina, Germán2021-10-15T16:47:35Z2021-10-15T16:47:35Z20170012-7353http://hdl.handle.net/10495/2320410.15446/dyna.v84n200.543642346-2183ABSTRACT: A useful tool to support the decision-making process in power transformer management is risk assessment. There are few practical methodologies to assess a Transformer Risk Index (TRI). In addition, such proposals do not consider the latest advances in techniques for transformer health valuation, and they also have other drawbacks. This paper proposes a practical method to undertake risk analysis of power transformer fleets, which deal with the stated problem. The proposal appropriately considers the best attributes of the methods reported in literature in order to compute the two components of TRI, i.e., the failure probability factor and the consequence factor. Moreover, this paper contributes to the risk analysis issue by including risk matrices and clustering techniques to support the decision-making process. The presented method was tested on a fleet of fourteen transformers. This approach serves as a practical and reliable tool for asset management in power utilities.RESUMEN: La evaluación de riesgo es una herramienta útil para apoyar el proceso de toma de decisiones para la gestión de transformadores de potencia. Existen pocas metodologías prácticas para evaluar un índice de riesgo del transformador (TRI). Además, tales propuestas no tienen en cuenta los últimos avances en técnicas para la valoración de la salud del transformador, entre otros inconvenientes. En este artículo se propone un método práctico para el análisis de riesgo en flotas de transformadores de potencia, el cual plantea soluciones a los problemas mencionados. La propuesta incluye los mejores atributos de los métodos reportados en la literatura, con el fin de calcular los dos componentes del TRI, es decir, el factor de probabilidad de falla y el factor consecuencias de la falla. Por otra parte, este trabajo contribuye con el análisis de riesgos mediante la inclusión de matrices de riesgo y técnicas de agrupamiento que permiten apoyar de manera robusta el proceso de toma de decisiones. El método presentado es probado en una flota de catorce transformadores. Este enfoque sirve como una herramienta práctica y fiable para la gestión de los activos de las empresas eléctricas.COL00104778application/pdfengUniversidad Nacional de Colombia, Facultad de Minas, Centro de PublicacionesGrupo de Manejo Eficiente de la Energía (GIMEL)Medellín, Colombiainfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_2df8fbb1https://purl.org/redcol/resource_type/ARTArtículo de investigaciónhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/2.5/co/http://purl.org/coar/access_right/c_abf2https://creativecommons.org/licenses/by-nc-nd/4.0/A practical method for risk assessment in power transformer fleetsMétodo práctico para la evaluación de riesgo en parques de transformadores de potenciaDiagnósticoDiagnosisÍndice de RiesgoRisk IndexSistemas eléctricosElectrical systemsEvaluación de riesgosRisk assessmentDynaDyna111884200ORIGINALRomeroAndres_2017_MethodRiskAssessment.pdfRomeroAndres_2017_MethodRiskAssessment.pdfArtículo de investigaciónapplication/pdf463043http://bibliotecadigital.udea.edu.co/bitstream/10495/23204/1/RomeroAndres_2017_MethodRiskAssessment.pdf88ccf5a7329682070eb2ab7c784b56d3MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8823http://bibliotecadigital.udea.edu.co/bitstream/10495/23204/2/license_rdfb88b088d9957e670ce3b3fbe2eedbc13MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://bibliotecadigital.udea.edu.co/bitstream/10495/23204/3/license.txt8a4605be74aa9ea9d79846c1fba20a33MD5310495/23204oai:bibliotecadigital.udea.edu.co:10495/232042021-10-15 11:47:35.756Repositorio Institucional Universidad de Antioquiaandres.perez@udea.edu.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 |