Evolutionary multi-move path-relinking for transmission network expansion planning

Detalhes bibliográficos
Autor(a) principal: Rahmani, M. [UNESP]
Data de Publicação: 2010
Outros Autores: Rashidinejad, M., Carreno, E. M., Romero, R. A. [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/PES.2010.5590080
http://hdl.handle.net/11449/72209
Resumo: This paper presents the application of a new metaheuristic algorithm to solve the transmission expansion planning problem. A simple heuristic, using a relaxed network model associated with cost perturbation, is applied to generate a set of high quality initial solutions with different topologies. The population is evolved using a multi-move path-relinking with the objective of finding minimum investment cost for the transmission expansion planning problem employing the DC representation. The algorithm is tested on the southern Brazilian system, obtaining the optimal solution for the system with better performance than similar metaheuristics algorithms applied to the same problem. ©2010 IEEE.
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spelling Evolutionary multi-move path-relinking for transmission network expansion planningConstruction phaseGRASPMulti-move path-relinkingTransmission expansion planningBrazilian systemHigh qualityInitial solutionInvestment costsMeta heuristic algorithmMeta-heuristics algorithmsNetwork modelsOptimal solutionsPath relinkingTransmission network expansion planningAlgorithmsDC power transmissionElectric power transmission networksExpansionTopologyInvestmentsThis paper presents the application of a new metaheuristic algorithm to solve the transmission expansion planning problem. A simple heuristic, using a relaxed network model associated with cost perturbation, is applied to generate a set of high quality initial solutions with different topologies. The population is evolved using a multi-move path-relinking with the objective of finding minimum investment cost for the transmission expansion planning problem employing the DC representation. The algorithm is tested on the southern Brazilian system, obtaining the optimal solution for the system with better performance than similar metaheuristics algorithms applied to the same problem. ©2010 IEEE.Universidade Estadual Paulista Campus Ilha Solteira, SPShahid Bahonar University of Kerman, KermanUniversidade Estadual Paulista Campus Ilha Solteira, SPUniversidade Estadual Paulista (Unesp)Shahid Bahonar University of KermanRahmani, M. [UNESP]Rashidinejad, M.Carreno, E. M.Romero, R. A. [UNESP]2014-05-27T11:25:25Z2014-05-27T11:25:25Z2010-12-06info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/PES.2010.5590080IEEE PES General Meeting, PES 2010.http://hdl.handle.net/11449/7220910.1109/PES.2010.55900802-s2.0-78649561965Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIEEE PES General Meeting, PES 2010info:eu-repo/semantics/openAccess2021-10-23T21:41:23Zoai:repositorio.unesp.br:11449/72209Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T14:31:41.959251Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Evolutionary multi-move path-relinking for transmission network expansion planning
title Evolutionary multi-move path-relinking for transmission network expansion planning
spellingShingle Evolutionary multi-move path-relinking for transmission network expansion planning
Rahmani, M. [UNESP]
Construction phase
GRASP
Multi-move path-relinking
Transmission expansion planning
Brazilian system
High quality
Initial solution
Investment costs
Meta heuristic algorithm
Meta-heuristics algorithms
Network models
Optimal solutions
Path relinking
Transmission network expansion planning
Algorithms
DC power transmission
Electric power transmission networks
Expansion
Topology
Investments
title_short Evolutionary multi-move path-relinking for transmission network expansion planning
title_full Evolutionary multi-move path-relinking for transmission network expansion planning
title_fullStr Evolutionary multi-move path-relinking for transmission network expansion planning
title_full_unstemmed Evolutionary multi-move path-relinking for transmission network expansion planning
title_sort Evolutionary multi-move path-relinking for transmission network expansion planning
author Rahmani, M. [UNESP]
author_facet Rahmani, M. [UNESP]
Rashidinejad, M.
Carreno, E. M.
Romero, R. A. [UNESP]
author_role author
author2 Rashidinejad, M.
Carreno, E. M.
Romero, R. A. [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Shahid Bahonar University of Kerman
dc.contributor.author.fl_str_mv Rahmani, M. [UNESP]
Rashidinejad, M.
Carreno, E. M.
Romero, R. A. [UNESP]
dc.subject.por.fl_str_mv Construction phase
GRASP
Multi-move path-relinking
Transmission expansion planning
Brazilian system
High quality
Initial solution
Investment costs
Meta heuristic algorithm
Meta-heuristics algorithms
Network models
Optimal solutions
Path relinking
Transmission network expansion planning
Algorithms
DC power transmission
Electric power transmission networks
Expansion
Topology
Investments
topic Construction phase
GRASP
Multi-move path-relinking
Transmission expansion planning
Brazilian system
High quality
Initial solution
Investment costs
Meta heuristic algorithm
Meta-heuristics algorithms
Network models
Optimal solutions
Path relinking
Transmission network expansion planning
Algorithms
DC power transmission
Electric power transmission networks
Expansion
Topology
Investments
description This paper presents the application of a new metaheuristic algorithm to solve the transmission expansion planning problem. A simple heuristic, using a relaxed network model associated with cost perturbation, is applied to generate a set of high quality initial solutions with different topologies. The population is evolved using a multi-move path-relinking with the objective of finding minimum investment cost for the transmission expansion planning problem employing the DC representation. The algorithm is tested on the southern Brazilian system, obtaining the optimal solution for the system with better performance than similar metaheuristics algorithms applied to the same problem. ©2010 IEEE.
publishDate 2010
dc.date.none.fl_str_mv 2010-12-06
2014-05-27T11:25:25Z
2014-05-27T11:25:25Z
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/PES.2010.5590080
IEEE PES General Meeting, PES 2010.
http://hdl.handle.net/11449/72209
10.1109/PES.2010.5590080
2-s2.0-78649561965
url http://dx.doi.org/10.1109/PES.2010.5590080
http://hdl.handle.net/11449/72209
identifier_str_mv IEEE PES General Meeting, PES 2010.
10.1109/PES.2010.5590080
2-s2.0-78649561965
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv IEEE PES General Meeting, PES 2010
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
_version_ 1808128373973581824

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