Coevolutionary Genetic Algorithm Based on the Augmented Lagrangian Function for Solving the Economic Dispatch Problem
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/TLA.2015.7387232 http://hdl.handle.net/11449/177912 |
Resumo: | This paper proposes a coevolutionary augmented Lagrangian method (AGCE) for solving the classic economic dispatch problem. This problem becomes non-convex and non-differentiable if valve-point loadings effects are considered in the cost curves of thermal units. In such cases, the evolutionary approaches have proven to be efficient for solving the primal economic dispatch problem; however, the great majority of these methods are not capable of solving the associated dual problem. Furthermore, the solutions obtained by these methods cannot be evaluated concerning their optimality. The AGCE works in the primal-dual subspaces and is able to calculate both primal and dual optimal values. For such a purpose, AGCE processes, in parallel, the evolution of two distinct groups of individuals, associated with primal and dual variables, respectively. The 'clouds' of primal and dual points become iteratively denser, and converge to the saddle points associated with the problem, even in the presence of non-differentiability points. Therefore, AGCE makes possible the evaluation of optimality of its solution points. In the results, the AGCE is compared with a traditional interior point method and with a genetic algorithm that works only in the primal subspace. |
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Repositório Institucional da UNESP |
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Coevolutionary Genetic Algorithm Based on the Augmented Lagrangian Function for Solving the Economic Dispatch Problemaugmented Lagrangian methodeconomic dispatchevolutionary computationGenetic algorithmsThis paper proposes a coevolutionary augmented Lagrangian method (AGCE) for solving the classic economic dispatch problem. This problem becomes non-convex and non-differentiable if valve-point loadings effects are considered in the cost curves of thermal units. In such cases, the evolutionary approaches have proven to be efficient for solving the primal economic dispatch problem; however, the great majority of these methods are not capable of solving the associated dual problem. Furthermore, the solutions obtained by these methods cannot be evaluated concerning their optimality. The AGCE works in the primal-dual subspaces and is able to calculate both primal and dual optimal values. For such a purpose, AGCE processes, in parallel, the evolution of two distinct groups of individuals, associated with primal and dual variables, respectively. The 'clouds' of primal and dual points become iteratively denser, and converge to the saddle points associated with the problem, even in the presence of non-differentiability points. Therefore, AGCE makes possible the evaluation of optimality of its solution points. In the results, the AGCE is compared with a traditional interior point method and with a genetic algorithm that works only in the primal subspace.Unesp-Univ Estadual Paulista Departamento de Engenharia EléctricaUnesp-Univ Estadual Paulista Departamento de Engenharia EléctricaUniversidade Estadual Paulista (Unesp)Nepomuceno, Leonardo [UNESP]Cassia Baptista, Edmea [UNESP]Roberto Balbo, Antonio [UNESP]Martins Soler, Edilaine [UNESP]2018-12-11T17:27:39Z2018-12-11T17:27:39Z2015-10-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article3277-3286application/pdfhttp://dx.doi.org/10.1109/TLA.2015.7387232IEEE Latin America Transactions, v. 13, n. 10, p. 3277-3286, 2015.1548-0992http://hdl.handle.net/11449/17791210.1109/TLA.2015.73872322-s2.0-849619280562-s2.0-84961928056.pdf2013445187247691Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporIEEE Latin America Transactions0,253info:eu-repo/semantics/openAccess2023-12-10T06:23:48Zoai:repositorio.unesp.br:11449/177912Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-12-10T06:23:48Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Coevolutionary Genetic Algorithm Based on the Augmented Lagrangian Function for Solving the Economic Dispatch Problem |
title |
Coevolutionary Genetic Algorithm Based on the Augmented Lagrangian Function for Solving the Economic Dispatch Problem |
spellingShingle |
Coevolutionary Genetic Algorithm Based on the Augmented Lagrangian Function for Solving the Economic Dispatch Problem Nepomuceno, Leonardo [UNESP] augmented Lagrangian method economic dispatch evolutionary computation Genetic algorithms |
title_short |
Coevolutionary Genetic Algorithm Based on the Augmented Lagrangian Function for Solving the Economic Dispatch Problem |
title_full |
Coevolutionary Genetic Algorithm Based on the Augmented Lagrangian Function for Solving the Economic Dispatch Problem |
title_fullStr |
Coevolutionary Genetic Algorithm Based on the Augmented Lagrangian Function for Solving the Economic Dispatch Problem |
title_full_unstemmed |
Coevolutionary Genetic Algorithm Based on the Augmented Lagrangian Function for Solving the Economic Dispatch Problem |
title_sort |
Coevolutionary Genetic Algorithm Based on the Augmented Lagrangian Function for Solving the Economic Dispatch Problem |
author |
Nepomuceno, Leonardo [UNESP] |
author_facet |
Nepomuceno, Leonardo [UNESP] Cassia Baptista, Edmea [UNESP] Roberto Balbo, Antonio [UNESP] Martins Soler, Edilaine [UNESP] |
author_role |
author |
author2 |
Cassia Baptista, Edmea [UNESP] Roberto Balbo, Antonio [UNESP] Martins Soler, Edilaine [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Nepomuceno, Leonardo [UNESP] Cassia Baptista, Edmea [UNESP] Roberto Balbo, Antonio [UNESP] Martins Soler, Edilaine [UNESP] |
dc.subject.por.fl_str_mv |
augmented Lagrangian method economic dispatch evolutionary computation Genetic algorithms |
topic |
augmented Lagrangian method economic dispatch evolutionary computation Genetic algorithms |
description |
This paper proposes a coevolutionary augmented Lagrangian method (AGCE) for solving the classic economic dispatch problem. This problem becomes non-convex and non-differentiable if valve-point loadings effects are considered in the cost curves of thermal units. In such cases, the evolutionary approaches have proven to be efficient for solving the primal economic dispatch problem; however, the great majority of these methods are not capable of solving the associated dual problem. Furthermore, the solutions obtained by these methods cannot be evaluated concerning their optimality. The AGCE works in the primal-dual subspaces and is able to calculate both primal and dual optimal values. For such a purpose, AGCE processes, in parallel, the evolution of two distinct groups of individuals, associated with primal and dual variables, respectively. The 'clouds' of primal and dual points become iteratively denser, and converge to the saddle points associated with the problem, even in the presence of non-differentiability points. Therefore, AGCE makes possible the evaluation of optimality of its solution points. In the results, the AGCE is compared with a traditional interior point method and with a genetic algorithm that works only in the primal subspace. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-10-01 2018-12-11T17:27:39Z 2018-12-11T17:27:39Z |
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://dx.doi.org/10.1109/TLA.2015.7387232 IEEE Latin America Transactions, v. 13, n. 10, p. 3277-3286, 2015. 1548-0992 http://hdl.handle.net/11449/177912 10.1109/TLA.2015.7387232 2-s2.0-84961928056 2-s2.0-84961928056.pdf 2013445187247691 |
url |
http://dx.doi.org/10.1109/TLA.2015.7387232 http://hdl.handle.net/11449/177912 |
identifier_str_mv |
IEEE Latin America Transactions, v. 13, n. 10, p. 3277-3286, 2015. 1548-0992 10.1109/TLA.2015.7387232 2-s2.0-84961928056 2-s2.0-84961928056.pdf 2013445187247691 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
IEEE Latin America Transactions 0,253 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
3277-3286 application/pdf |
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_ |
1803046889585639424 |