Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system

This paper presents a multi-objective teaching learning algorithm based on decomposition for solving the optimal reactive power dispatch problem (ORPD). The effectiveness and performance of the proposed algorithm are compared with respect to a multi-objective evolutionary algorithm based on decompos...

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Autores:
Medina, Miguel A
Ramirez, Juan M
Coello, Carlos A
Das, Swagatam
Tipo de recurso:
Article of journal
Fecha de publicación:
2014
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/72529
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/72529
http://bdigital.unal.edu.co/37002/
Palabra clave:
Multi-objective evolutionary algorithm based on decomposition (MOEA/D)
Multi-objective Teaching-learning algorithm
Optimal reactive power dispatch.
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
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spelling Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Medina, Miguel Aee1b70fa-8ef0-4241-abf2-78fca4977937300Ramirez, Juan M2aa672b9-0960-4785-a9c2-0b89c2bcc612300Coello, Carlos Af5fea921-c949-4467-ad46-6fa573965ff6300Das, Swagatam799a1151-71dc-41d5-b0ec-dde94190c0703002019-07-03T15:17:00Z2019-07-03T15:17:00Z2014-06-25https://repositorio.unal.edu.co/handle/unal/72529http://bdigital.unal.edu.co/37002/This paper presents a multi-objective teaching learning algorithm based on decomposition for solving the optimal reactive power dispatch problem (ORPD). The effectiveness and performance of the proposed algorithm are compared with respect to a multi-objective evolutionary algorithm based on decomposition (MOEA/D) and the NSGA-II. A benchmark power system model is used to test the algorithms’ performance. The results of the power losses reduction as well as the performance metrics indicate that the proposed algorithm is a reliable choice for solving the problem.application/pdfspaUniversidad Nacional de Colombia Sede Medellínhttp://revistas.unal.edu.co/index.php/dyna/article/view/38309Universidad Nacional de Colombia Revistas electrónicas UN DynaDynaDYNA; Vol. 81, núm. 185 (2014); 196-203 Dyna; Vol. 81, núm. 185 (2014); 196-203 2346-2183 0012-7353Medina, Miguel A and Ramirez, Juan M and Coello, Carlos A and Das, Swagatam (2014) Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system. DYNA; Vol. 81, núm. 185 (2014); 196-203 Dyna; Vol. 81, núm. 185 (2014); 196-203 2346-2183 0012-7353 .Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test systemArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTMulti-objective evolutionary algorithm based on decomposition (MOEA/D)Multi-objective Teaching-learning algorithmOptimal reactive power dispatch.ORIGINAL38309-207933-1-PB.pdfapplication/pdf545482https://repositorio.unal.edu.co/bitstream/unal/72529/1/38309-207933-1-PB.pdfc96d0e06f25f94d46420d14a3c3fe870MD5138309-170429-1-SP.docapplication/msword29696https://repositorio.unal.edu.co/bitstream/unal/72529/2/38309-170429-1-SP.doca42a1d4afb89e2922fb838ac32a88f71MD52THUMBNAIL38309-207933-1-PB.pdf.jpg38309-207933-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg9693https://repositorio.unal.edu.co/bitstream/unal/72529/3/38309-207933-1-PB.pdf.jpg7a6d02d7eea73c4fded9972b0fca30abMD53unal/72529oai:repositorio.unal.edu.co:unal/725292024-06-16 23:12:00.029Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co
dc.title.spa.fl_str_mv Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system
title Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system
spellingShingle Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system
Multi-objective evolutionary algorithm based on decomposition (MOEA/D)
Multi-objective Teaching-learning algorithm
Optimal reactive power dispatch.
title_short Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system
title_full Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system
title_fullStr Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system
title_full_unstemmed Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system
title_sort Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system
dc.creator.fl_str_mv Medina, Miguel A
Ramirez, Juan M
Coello, Carlos A
Das, Swagatam
dc.contributor.author.spa.fl_str_mv Medina, Miguel A
Ramirez, Juan M
Coello, Carlos A
Das, Swagatam
dc.subject.proposal.spa.fl_str_mv Multi-objective evolutionary algorithm based on decomposition (MOEA/D)
Multi-objective Teaching-learning algorithm
Optimal reactive power dispatch.
topic Multi-objective evolutionary algorithm based on decomposition (MOEA/D)
Multi-objective Teaching-learning algorithm
Optimal reactive power dispatch.
description This paper presents a multi-objective teaching learning algorithm based on decomposition for solving the optimal reactive power dispatch problem (ORPD). The effectiveness and performance of the proposed algorithm are compared with respect to a multi-objective evolutionary algorithm based on decomposition (MOEA/D) and the NSGA-II. A benchmark power system model is used to test the algorithms’ performance. The results of the power losses reduction as well as the performance metrics indicate that the proposed algorithm is a reliable choice for solving the problem.
publishDate 2014
dc.date.issued.spa.fl_str_mv 2014-06-25
dc.date.accessioned.spa.fl_str_mv 2019-07-03T15:17:00Z
dc.date.available.spa.fl_str_mv 2019-07-03T15:17:00Z
dc.type.spa.fl_str_mv Artículo de revista
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
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format http://purl.org/coar/resource_type/c_6501
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dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/72529
dc.identifier.eprints.spa.fl_str_mv http://bdigital.unal.edu.co/37002/
url https://repositorio.unal.edu.co/handle/unal/72529
http://bdigital.unal.edu.co/37002/
dc.language.iso.spa.fl_str_mv spa
language spa
dc.relation.spa.fl_str_mv http://revistas.unal.edu.co/index.php/dyna/article/view/38309
dc.relation.ispartof.spa.fl_str_mv Universidad Nacional de Colombia Revistas electrónicas UN Dyna
Dyna
dc.relation.ispartofseries.none.fl_str_mv DYNA; Vol. 81, núm. 185 (2014); 196-203 Dyna; Vol. 81, núm. 185 (2014); 196-203 2346-2183 0012-7353
dc.relation.references.spa.fl_str_mv Medina, Miguel A and Ramirez, Juan M and Coello, Carlos A and Das, Swagatam (2014) Use of a multi-objective teaching-learning algorithm for reduction of power losses in a power test system. DYNA; Vol. 81, núm. 185 (2014); 196-203 Dyna; Vol. 81, núm. 185 (2014); 196-203 2346-2183 0012-7353 .
dc.rights.spa.fl_str_mv Derechos reservados - Universidad Nacional de Colombia
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv Atribución-NoComercial 4.0 Internacional
dc.rights.uri.spa.fl_str_mv http://creativecommons.org/licenses/by-nc/4.0/
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv Atribución-NoComercial 4.0 Internacional
Derechos reservados - Universidad Nacional de Colombia
http://creativecommons.org/licenses/by-nc/4.0/
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad Nacional de Colombia Sede Medellín
institution Universidad Nacional de Colombia
bitstream.url.fl_str_mv https://repositorio.unal.edu.co/bitstream/unal/72529/1/38309-207933-1-PB.pdf
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