Reconfiguration of Radial Distribution Systems with Variable Demands Using the Clonal Selection Algorithm and the Specialized Genetic Algorithm of Chu-Beasley
Autor(a) principal: | |
---|---|
Data de Publicação: | 2016 |
Outros Autores: | , , |
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/123456789/3921 http://dx.doi.org/10.1007/s40313-016-0268-9 |
Resumo: | This paper presents two new approaches to solve the reconfiguration problem of electrical distribution systems (EDSs) with variable demands, using the CLONALG and the SGACB algorithms. The CLONALG is a combinatorial optimization technique inspired by biological immune systems, which aims at reproducing the main properties and functions of the system. The SGACB is an optimization algorithm inspired by natural selection and the evolution of species. The reconfiguration problem with variable demands is a complex combinatorial problem that aims at identifying the best radial topology for an EDS, while satisfying all technical constraints at every demand level and minimizing the cost of energy losses in a given operation period. Both algorithms were implemented in C++ and test systems with 33, 84, and 136 nodes, as well as a real system with 417 nodes, in order to validate the proposed methods. The obtained results were compared with results available in the literature in order to verify the efficiency of the proposed approaches. |
id |
RCAP_f1251f8da93df2f8ab4107d008f7f5ce |
---|---|
oai_identifier_str |
oai:repositorio.inesctec.pt:123456789/3921 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Reconfiguration of Radial Distribution Systems with Variable Demands Using the Clonal Selection Algorithm and the Specialized Genetic Algorithm of Chu-BeasleyThis paper presents two new approaches to solve the reconfiguration problem of electrical distribution systems (EDSs) with variable demands, using the CLONALG and the SGACB algorithms. The CLONALG is a combinatorial optimization technique inspired by biological immune systems, which aims at reproducing the main properties and functions of the system. The SGACB is an optimization algorithm inspired by natural selection and the evolution of species. The reconfiguration problem with variable demands is a complex combinatorial problem that aims at identifying the best radial topology for an EDS, while satisfying all technical constraints at every demand level and minimizing the cost of energy losses in a given operation period. Both algorithms were implemented in C++ and test systems with 33, 84, and 136 nodes, as well as a real system with 417 nodes, in order to validate the proposed methods. The obtained results were compared with results available in the literature in order to verify the efficiency of the proposed approaches.2017-12-12T15:50:40Z2016-01-01T00:00:00Z2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/3921http://dx.doi.org/10.1007/s40313-016-0268-9engSouza,SSFRomero,RJorge Correia PereiraJoão Tomé Saraivainfo: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:RCAAP2023-05-15T10:19:44Zoai:repositorio.inesctec.pt:123456789/3921Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:09.112163Repositório 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 |
Reconfiguration of Radial Distribution Systems with Variable Demands Using the Clonal Selection Algorithm and the Specialized Genetic Algorithm of Chu-Beasley |
title |
Reconfiguration of Radial Distribution Systems with Variable Demands Using the Clonal Selection Algorithm and the Specialized Genetic Algorithm of Chu-Beasley |
spellingShingle |
Reconfiguration of Radial Distribution Systems with Variable Demands Using the Clonal Selection Algorithm and the Specialized Genetic Algorithm of Chu-Beasley Souza,SSF |
title_short |
Reconfiguration of Radial Distribution Systems with Variable Demands Using the Clonal Selection Algorithm and the Specialized Genetic Algorithm of Chu-Beasley |
title_full |
Reconfiguration of Radial Distribution Systems with Variable Demands Using the Clonal Selection Algorithm and the Specialized Genetic Algorithm of Chu-Beasley |
title_fullStr |
Reconfiguration of Radial Distribution Systems with Variable Demands Using the Clonal Selection Algorithm and the Specialized Genetic Algorithm of Chu-Beasley |
title_full_unstemmed |
Reconfiguration of Radial Distribution Systems with Variable Demands Using the Clonal Selection Algorithm and the Specialized Genetic Algorithm of Chu-Beasley |
title_sort |
Reconfiguration of Radial Distribution Systems with Variable Demands Using the Clonal Selection Algorithm and the Specialized Genetic Algorithm of Chu-Beasley |
author |
Souza,SSF |
author_facet |
Souza,SSF Romero,R Jorge Correia Pereira João Tomé Saraiva |
author_role |
author |
author2 |
Romero,R Jorge Correia Pereira João Tomé Saraiva |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Souza,SSF Romero,R Jorge Correia Pereira João Tomé Saraiva |
description |
This paper presents two new approaches to solve the reconfiguration problem of electrical distribution systems (EDSs) with variable demands, using the CLONALG and the SGACB algorithms. The CLONALG is a combinatorial optimization technique inspired by biological immune systems, which aims at reproducing the main properties and functions of the system. The SGACB is an optimization algorithm inspired by natural selection and the evolution of species. The reconfiguration problem with variable demands is a complex combinatorial problem that aims at identifying the best radial topology for an EDS, while satisfying all technical constraints at every demand level and minimizing the cost of energy losses in a given operation period. Both algorithms were implemented in C++ and test systems with 33, 84, and 136 nodes, as well as a real system with 417 nodes, in order to validate the proposed methods. The obtained results were compared with results available in the literature in order to verify the efficiency of the proposed approaches. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-01-01T00:00:00Z 2016 2017-12-12T15:50:40Z |
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/123456789/3921 http://dx.doi.org/10.1007/s40313-016-0268-9 |
url |
http://repositorio.inesctec.pt/handle/123456789/3921 http://dx.doi.org/10.1007/s40313-016-0268-9 |
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 |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799131598552039424 |