Maintenance planning in wind farms with allocation of teams using genetic algorithms

Detalhes bibliográficos
Autor(a) principal: Fonseca,I
Data de Publicação: 2014
Outros Autores: Farinha,JT, Fernando Maciel Barbosa
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/123456789/4098
http://dx.doi.org/10.1109/tla.2014.6894001
Resumo: Renewable energy is essential for global sustainability. Wind power has given a great contribution to this energy paradigm. The paper describes a maintenance management system for inshore and offshore wind farms, as well as a method to schedule maintenance using genetic algorithms. Under this subject there exists a sub-problem that concerns with the determination of the cheapest path between two points. The paper compares the performance of three methods: genetic algorithms, Dijkstra's algorithm and ant optimization algorithm to the determination of the cheapest path between different wind parks for maintenance.
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spelling Maintenance planning in wind farms with allocation of teams using genetic algorithmsRenewable energy is essential for global sustainability. Wind power has given a great contribution to this energy paradigm. The paper describes a maintenance management system for inshore and offshore wind farms, as well as a method to schedule maintenance using genetic algorithms. Under this subject there exists a sub-problem that concerns with the determination of the cheapest path between two points. The paper compares the performance of three methods: genetic algorithms, Dijkstra's algorithm and ant optimization algorithm to the determination of the cheapest path between different wind parks for maintenance.2017-12-14T14:45:05Z2014-01-01T00:00:00Z2014info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/4098http://dx.doi.org/10.1109/tla.2014.6894001engFonseca,IFarinha,JTFernando Maciel Barbosainfo: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:RCAAP2023-05-15T10:19:55Zoai:repositorio.inesctec.pt:123456789/4098Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:25.891527Repositório 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 Maintenance planning in wind farms with allocation of teams using genetic algorithms
title Maintenance planning in wind farms with allocation of teams using genetic algorithms
spellingShingle Maintenance planning in wind farms with allocation of teams using genetic algorithms
Fonseca,I
title_short Maintenance planning in wind farms with allocation of teams using genetic algorithms
title_full Maintenance planning in wind farms with allocation of teams using genetic algorithms
title_fullStr Maintenance planning in wind farms with allocation of teams using genetic algorithms
title_full_unstemmed Maintenance planning in wind farms with allocation of teams using genetic algorithms
title_sort Maintenance planning in wind farms with allocation of teams using genetic algorithms
author Fonseca,I
author_facet Fonseca,I
Farinha,JT
Fernando Maciel Barbosa
author_role author
author2 Farinha,JT
Fernando Maciel Barbosa
author2_role author
author
dc.contributor.author.fl_str_mv Fonseca,I
Farinha,JT
Fernando Maciel Barbosa
description Renewable energy is essential for global sustainability. Wind power has given a great contribution to this energy paradigm. The paper describes a maintenance management system for inshore and offshore wind farms, as well as a method to schedule maintenance using genetic algorithms. Under this subject there exists a sub-problem that concerns with the determination of the cheapest path between two points. The paper compares the performance of three methods: genetic algorithms, Dijkstra's algorithm and ant optimization algorithm to the determination of the cheapest path between different wind parks for maintenance.
publishDate 2014
dc.date.none.fl_str_mv 2014-01-01T00:00:00Z
2014
2017-12-14T14:45:05Z
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/123456789/4098
http://dx.doi.org/10.1109/tla.2014.6894001
url http://repositorio.inesctec.pt/handle/123456789/4098
http://dx.doi.org/10.1109/tla.2014.6894001
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
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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