A Genetic Algorithm for Transmission Network Expansion Planning Considering Line Maintenance

Detalhes bibliográficos
Autor(a) principal: Mahdavi, Meisam [UNESP]
Data de Publicação: 2020
Outros Autores: Kheirkhah, Ali Reza [UNESP], MacEdo, Leonardo H. [UNESP], Romero, Ruben [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/CEC48606.2020.9185821
http://hdl.handle.net/11449/228854
Resumo: This paper proposes a decimal codification genetic algorithm to solve the transmission network expansion planning (TNEP) problem considering the economic impact of line maintenance. The goal is to extend the lifespan of the time-worn lines in order to reduce the investment cost in the expansion of the transmission network and to improve the worth of the transmission system. To assess the economic impact of the maintenance on the deterioration of transmission lines and transformers, the sum of years digit method is implemented. The proposed algorithm is evaluated using the IEEE reliability test system, and the assessment of the results shows that by including the effect of line maintenance on the TNEP problem, significant savings can be made in the overall cost of the system.
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spelling A Genetic Algorithm for Transmission Network Expansion Planning Considering Line MaintenanceDecimal codification genetic algorithmlines' degradationmaintenancemixed-integer nonlinear programmingtransmission network expansion planningThis paper proposes a decimal codification genetic algorithm to solve the transmission network expansion planning (TNEP) problem considering the economic impact of line maintenance. The goal is to extend the lifespan of the time-worn lines in order to reduce the investment cost in the expansion of the transmission network and to improve the worth of the transmission system. To assess the economic impact of the maintenance on the deterioration of transmission lines and transformers, the sum of years digit method is implemented. The proposed algorithm is evaluated using the IEEE reliability test system, and the assessment of the results shows that by including the effect of line maintenance on the TNEP problem, significant savings can be made in the overall cost of the system.São Paulo State University Ilha Solteira Department of Electrical Engineering SpSão Paulo State University Ilha Solteira Department of Electrical Engineering SpUniversidade Estadual Paulista (UNESP)Mahdavi, Meisam [UNESP]Kheirkhah, Ali Reza [UNESP]MacEdo, Leonardo H. [UNESP]Romero, Ruben [UNESP]2022-04-29T08:29:01Z2022-04-29T08:29:01Z2020-07-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/CEC48606.2020.91858212020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings.http://hdl.handle.net/11449/22885410.1109/CEC48606.2020.91858212-s2.0-85092023231Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedingsinfo:eu-repo/semantics/openAccess2024-07-04T19:11:39Zoai:repositorio.unesp.br:11449/228854Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:18:24.801229Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A Genetic Algorithm for Transmission Network Expansion Planning Considering Line Maintenance
title A Genetic Algorithm for Transmission Network Expansion Planning Considering Line Maintenance
spellingShingle A Genetic Algorithm for Transmission Network Expansion Planning Considering Line Maintenance
Mahdavi, Meisam [UNESP]
Decimal codification genetic algorithm
lines' degradation
maintenance
mixed-integer nonlinear programming
transmission network expansion planning
title_short A Genetic Algorithm for Transmission Network Expansion Planning Considering Line Maintenance
title_full A Genetic Algorithm for Transmission Network Expansion Planning Considering Line Maintenance
title_fullStr A Genetic Algorithm for Transmission Network Expansion Planning Considering Line Maintenance
title_full_unstemmed A Genetic Algorithm for Transmission Network Expansion Planning Considering Line Maintenance
title_sort A Genetic Algorithm for Transmission Network Expansion Planning Considering Line Maintenance
author Mahdavi, Meisam [UNESP]
author_facet Mahdavi, Meisam [UNESP]
Kheirkhah, Ali Reza [UNESP]
MacEdo, Leonardo H. [UNESP]
Romero, Ruben [UNESP]
author_role author
author2 Kheirkhah, Ali Reza [UNESP]
MacEdo, Leonardo H. [UNESP]
Romero, Ruben [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Mahdavi, Meisam [UNESP]
Kheirkhah, Ali Reza [UNESP]
MacEdo, Leonardo H. [UNESP]
Romero, Ruben [UNESP]
dc.subject.por.fl_str_mv Decimal codification genetic algorithm
lines' degradation
maintenance
mixed-integer nonlinear programming
transmission network expansion planning
topic Decimal codification genetic algorithm
lines' degradation
maintenance
mixed-integer nonlinear programming
transmission network expansion planning
description This paper proposes a decimal codification genetic algorithm to solve the transmission network expansion planning (TNEP) problem considering the economic impact of line maintenance. The goal is to extend the lifespan of the time-worn lines in order to reduce the investment cost in the expansion of the transmission network and to improve the worth of the transmission system. To assess the economic impact of the maintenance on the deterioration of transmission lines and transformers, the sum of years digit method is implemented. The proposed algorithm is evaluated using the IEEE reliability test system, and the assessment of the results shows that by including the effect of line maintenance on the TNEP problem, significant savings can be made in the overall cost of the system.
publishDate 2020
dc.date.none.fl_str_mv 2020-07-01
2022-04-29T08:29:01Z
2022-04-29T08:29:01Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/CEC48606.2020.9185821
2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings.
http://hdl.handle.net/11449/228854
10.1109/CEC48606.2020.9185821
2-s2.0-85092023231
url http://dx.doi.org/10.1109/CEC48606.2020.9185821
http://hdl.handle.net/11449/228854
identifier_str_mv 2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings.
10.1109/CEC48606.2020.9185821
2-s2.0-85092023231
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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