Distribution System Reconfiguration with Variable Demands Using the Clonal Selection Algorithm

Detalhes bibliográficos
Autor(a) principal: Frutuoso de Souza, Simone Silva [UNESP]
Data de Publicação: 2015
Outros Autores: Romero, Ruben [UNESP], Correia Pereira, Jorge Manuel, Tome Saraiva, Joao Paulo, IEEE
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/161756
Resumo: This paper describes the application of the clonal selection algorithm to the reconfiguration problem of distribution networks considering non-uniform demand levels. The Clonal Algorithm, CLONALG, is a combinatorial optimization technique inspired in the immunologic bio system and it aims at reproducing the main properties and functions of this system. The reconfiguration problem of distribution networks with non-uniform demand levels is a complex problem that aims at identifying the most adequate radial topology of the network that complies with all technical constraints in every demand level while minimizing the cost of active losses along an extended operation period. This work includes results of the application of the Clonal algorithm to distribution systems with 33, 84 and 136 buses. These results demonstrate the robustness and efficiency of the proposed approach.
id UNSP_96086eab8190fe17e965365f4fd53d3b
oai_identifier_str oai:repositorio.unesp.br:11449/161756
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling Distribution System Reconfiguration with Variable Demands Using the Clonal Selection AlgorithmDistribution System ReconfigurationVariable DemandsClonal Selection AlgorithmArtificial Immune SystemsMixed-Integer Nonlinear Programming ProblemThis paper describes the application of the clonal selection algorithm to the reconfiguration problem of distribution networks considering non-uniform demand levels. The Clonal Algorithm, CLONALG, is a combinatorial optimization technique inspired in the immunologic bio system and it aims at reproducing the main properties and functions of this system. The reconfiguration problem of distribution networks with non-uniform demand levels is a complex problem that aims at identifying the most adequate radial topology of the network that complies with all technical constraints in every demand level while minimizing the cost of active losses along an extended operation period. This work includes results of the application of the Clonal algorithm to distribution systems with 33, 84 and 136 buses. These results demonstrate the robustness and efficiency of the proposed approach.Univ Estadual Paulista, UNESP, Dept Elect Engn, Ilha Solteira, SP, BrazilINESC TEC Porto, Ctr Sistemas Energia CPES, Oporto, PortugalUniv Estadual Paulista, UNESP, Dept Elect Engn, Ilha Solteira, SP, BrazilIeeeUniversidade Estadual Paulista (Unesp)INESC TEC PortoFrutuoso de Souza, Simone Silva [UNESP]Romero, Ruben [UNESP]Correia Pereira, Jorge ManuelTome Saraiva, Joao PauloIEEE2018-11-26T16:48:29Z2018-11-26T16:48:29Z2015-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject62015 18th International Conference On Intelligent System Application To Power Systems (isap). New York: Ieee, 6 p., 2015.http://hdl.handle.net/11449/161756WOS:000380395400034Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2015 18th International Conference On Intelligent System Application To Power Systems (isap)info:eu-repo/semantics/openAccess2024-07-04T19:11:13Zoai:repositorio.unesp.br:11449/161756Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T13:59:23.709472Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Distribution System Reconfiguration with Variable Demands Using the Clonal Selection Algorithm
title Distribution System Reconfiguration with Variable Demands Using the Clonal Selection Algorithm
spellingShingle Distribution System Reconfiguration with Variable Demands Using the Clonal Selection Algorithm
Frutuoso de Souza, Simone Silva [UNESP]
Distribution System Reconfiguration
Variable Demands
Clonal Selection Algorithm
Artificial Immune Systems
Mixed-Integer Nonlinear Programming Problem
title_short Distribution System Reconfiguration with Variable Demands Using the Clonal Selection Algorithm
title_full Distribution System Reconfiguration with Variable Demands Using the Clonal Selection Algorithm
title_fullStr Distribution System Reconfiguration with Variable Demands Using the Clonal Selection Algorithm
title_full_unstemmed Distribution System Reconfiguration with Variable Demands Using the Clonal Selection Algorithm
title_sort Distribution System Reconfiguration with Variable Demands Using the Clonal Selection Algorithm
author Frutuoso de Souza, Simone Silva [UNESP]
author_facet Frutuoso de Souza, Simone Silva [UNESP]
Romero, Ruben [UNESP]
Correia Pereira, Jorge Manuel
Tome Saraiva, Joao Paulo
IEEE
author_role author
author2 Romero, Ruben [UNESP]
Correia Pereira, Jorge Manuel
Tome Saraiva, Joao Paulo
IEEE
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
INESC TEC Porto
dc.contributor.author.fl_str_mv Frutuoso de Souza, Simone Silva [UNESP]
Romero, Ruben [UNESP]
Correia Pereira, Jorge Manuel
Tome Saraiva, Joao Paulo
IEEE
dc.subject.por.fl_str_mv Distribution System Reconfiguration
Variable Demands
Clonal Selection Algorithm
Artificial Immune Systems
Mixed-Integer Nonlinear Programming Problem
topic Distribution System Reconfiguration
Variable Demands
Clonal Selection Algorithm
Artificial Immune Systems
Mixed-Integer Nonlinear Programming Problem
description This paper describes the application of the clonal selection algorithm to the reconfiguration problem of distribution networks considering non-uniform demand levels. The Clonal Algorithm, CLONALG, is a combinatorial optimization technique inspired in the immunologic bio system and it aims at reproducing the main properties and functions of this system. The reconfiguration problem of distribution networks with non-uniform demand levels is a complex problem that aims at identifying the most adequate radial topology of the network that complies with all technical constraints in every demand level while minimizing the cost of active losses along an extended operation period. This work includes results of the application of the Clonal algorithm to distribution systems with 33, 84 and 136 buses. These results demonstrate the robustness and efficiency of the proposed approach.
publishDate 2015
dc.date.none.fl_str_mv 2015-01-01
2018-11-26T16:48:29Z
2018-11-26T16:48:29Z
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 2015 18th International Conference On Intelligent System Application To Power Systems (isap). New York: Ieee, 6 p., 2015.
http://hdl.handle.net/11449/161756
WOS:000380395400034
identifier_str_mv 2015 18th International Conference On Intelligent System Application To Power Systems (isap). New York: Ieee, 6 p., 2015.
WOS:000380395400034
url http://hdl.handle.net/11449/161756
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2015 18th International Conference On Intelligent System Application To Power Systems (isap)
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 6
dc.publisher.none.fl_str_mv Ieee
publisher.none.fl_str_mv Ieee
dc.source.none.fl_str_mv Web of Science
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_ 1808128301515931648

Registros relacionados