Multiobjective Optimization Applied to Maintenance Policy for Electrical Networks
Autor(a) principal: | |
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Data de Publicação: | 2007 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://repositorio.inesctec.pt/handle/123456789/1509 |
Resumo: | This paper propose an approach to multi-objective maintenance policy definition for electrical networks. Maximum asset performance is one of the major goals for electric power system managers. To reach this goal, minimal life cycle cost and maintenance optimization becomes crucial, while meeting demands from customers and regulators. This necessitates the determination of the optimal balance between preventive and corrective maintenance in order to obtain the lowest total cost. The approach of this paper is to study the problem of balance between preventive and corrective maintenance as a multiobjective optimization problem, where we have the customer interruptions on one hand and on the other hand the maintenance budget of the network operator. The problem is solved with meta-heuristics developed for the specific problem, as well as with an Evolutionary Particle Swarm Optimization algorithm. The maintenance optimization is applied in a case study to an urban distribution system in Stockholm, Sweden. Despite a general decreased level of maintenance (lower total maintenance cost) a better network performance can be given to the customers. This is achieved by focusing the preventive maintenance on components with a high potential for improvements. Beside this, the paper constitutes a display of the value in introducing more maintenance alternatives for every component and to choose the right level of maintenance for the components with respect to network performance. |
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Multiobjective Optimization Applied to Maintenance Policy for Electrical NetworksThis paper propose an approach to multi-objective maintenance policy definition for electrical networks. Maximum asset performance is one of the major goals for electric power system managers. To reach this goal, minimal life cycle cost and maintenance optimization becomes crucial, while meeting demands from customers and regulators. This necessitates the determination of the optimal balance between preventive and corrective maintenance in order to obtain the lowest total cost. The approach of this paper is to study the problem of balance between preventive and corrective maintenance as a multiobjective optimization problem, where we have the customer interruptions on one hand and on the other hand the maintenance budget of the network operator. The problem is solved with meta-heuristics developed for the specific problem, as well as with an Evolutionary Particle Swarm Optimization algorithm. The maintenance optimization is applied in a case study to an urban distribution system in Stockholm, Sweden. Despite a general decreased level of maintenance (lower total maintenance cost) a better network performance can be given to the customers. This is achieved by focusing the preventive maintenance on components with a high potential for improvements. Beside this, the paper constitutes a display of the value in introducing more maintenance alternatives for every component and to choose the right level of maintenance for the components with respect to network performance.2017-11-16T12:27:27Z2007-01-01T00:00:00Z2007info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/1509engPatrik HilberVladimiro MirandaManuel MatosLina Bertlinginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:34Zoai:repositorio.inesctec.pt:123456789/1509Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:20.246974Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Multiobjective Optimization Applied to Maintenance Policy for Electrical Networks |
title |
Multiobjective Optimization Applied to Maintenance Policy for Electrical Networks |
spellingShingle |
Multiobjective Optimization Applied to Maintenance Policy for Electrical Networks Patrik Hilber |
title_short |
Multiobjective Optimization Applied to Maintenance Policy for Electrical Networks |
title_full |
Multiobjective Optimization Applied to Maintenance Policy for Electrical Networks |
title_fullStr |
Multiobjective Optimization Applied to Maintenance Policy for Electrical Networks |
title_full_unstemmed |
Multiobjective Optimization Applied to Maintenance Policy for Electrical Networks |
title_sort |
Multiobjective Optimization Applied to Maintenance Policy for Electrical Networks |
author |
Patrik Hilber |
author_facet |
Patrik Hilber Vladimiro Miranda Manuel Matos Lina Bertling |
author_role |
author |
author2 |
Vladimiro Miranda Manuel Matos Lina Bertling |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Patrik Hilber Vladimiro Miranda Manuel Matos Lina Bertling |
description |
This paper propose an approach to multi-objective maintenance policy definition for electrical networks. Maximum asset performance is one of the major goals for electric power system managers. To reach this goal, minimal life cycle cost and maintenance optimization becomes crucial, while meeting demands from customers and regulators. This necessitates the determination of the optimal balance between preventive and corrective maintenance in order to obtain the lowest total cost. The approach of this paper is to study the problem of balance between preventive and corrective maintenance as a multiobjective optimization problem, where we have the customer interruptions on one hand and on the other hand the maintenance budget of the network operator. The problem is solved with meta-heuristics developed for the specific problem, as well as with an Evolutionary Particle Swarm Optimization algorithm. The maintenance optimization is applied in a case study to an urban distribution system in Stockholm, Sweden. Despite a general decreased level of maintenance (lower total maintenance cost) a better network performance can be given to the customers. This is achieved by focusing the preventive maintenance on components with a high potential for improvements. Beside this, the paper constitutes a display of the value in introducing more maintenance alternatives for every component and to choose the right level of maintenance for the components with respect to network performance. |
publishDate |
2007 |
dc.date.none.fl_str_mv |
2007-01-01T00:00:00Z 2007 2017-11-16T12:27:27Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.inesctec.pt/handle/123456789/1509 |
url |
http://repositorio.inesctec.pt/handle/123456789/1509 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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