Multiobjective Optimization Applied to Maintenance Policy for Electrical Networks

Detalhes bibliográficos
Autor(a) principal: Patrik Hilber
Data de Publicação: 2007
Outros Autores: Vladimiro Miranda, Manuel Matos, Lina Bertling
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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spelling 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
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