Optimal Dispatch Programming of Hydroelectric Power Generation with the use of Genetic Algorithms

Detalhes bibliográficos
Autor(a) principal: Marcelino, Carolina Gil
Data de Publicação: 2013
Outros Autores: Wanner, Elizabeth Fialho, de Almeida, Paulo Eduardo Maciel, Farias, Gray
Tipo de documento: Artigo
Idioma: eng
Título da fonte: INFOCOMP: Jornal de Ciência da Computação
Texto Completo: https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/23
Resumo: The population increase and the growth of buying power of home appliances cause the need of electricity power to increase every year in Brazil. Electric dispatch is defined as the attribution of operational values to each generation unit inside a power plant, given some criteria to be fulfilled. In this context, an optimal dispatch schedule for hydroelectric units in energy plants provides a greater amount of energy to be generated with less consumption of water. This paper presents an optimization solution to solve this problem for an actual plant, using Genetic Algorithms. The underlying mathematical modeling is described in details and practical validation of the proposed approach is performed through simulation experiments. In the case study, results are analysed and compared to the actual system running in a real world plant. Finally, the generality of the proposed approach is discussed and possibilities of its use to solve the same problem to other hydroelectric plants are presented.
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spelling Optimal Dispatch Programming of Hydroelectric Power Generation with the use of Genetic AlgorithmsElectric DispatchOptimizationGenetic AlgorithmsSimulationThe population increase and the growth of buying power of home appliances cause the need of electricity power to increase every year in Brazil. Electric dispatch is defined as the attribution of operational values to each generation unit inside a power plant, given some criteria to be fulfilled. In this context, an optimal dispatch schedule for hydroelectric units in energy plants provides a greater amount of energy to be generated with less consumption of water. This paper presents an optimization solution to solve this problem for an actual plant, using Genetic Algorithms. The underlying mathematical modeling is described in details and practical validation of the proposed approach is performed through simulation experiments. In the case study, results are analysed and compared to the actual system running in a real world plant. Finally, the generality of the proposed approach is discussed and possibilities of its use to solve the same problem to other hydroelectric plants are presented.Editora da UFLA2013-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/23INFOCOMP Journal of Computer Science; Vol. 12 No. 2 (2013): December 2013; 12-221982-33631807-4545reponame:INFOCOMP: Jornal de Ciência da Computaçãoinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/23/10Copyright (c) 2016 INFOCOMP Journal of Computer Scienceinfo:eu-repo/semantics/openAccessMarcelino, Carolina GilWanner, Elizabeth Fialhode Almeida, Paulo Eduardo MacielFarias, Gray2017-07-20T15:41:16Zoai:infocomp.dcc.ufla.br:article/23Revistahttps://infocomp.dcc.ufla.br/index.php/infocompPUBhttps://infocomp.dcc.ufla.br/index.php/infocomp/oaiinfocomp@dcc.ufla.br||apfreire@dcc.ufla.br1982-33631807-4545opendoar:2024-05-21T19:54:11.982571INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv Optimal Dispatch Programming of Hydroelectric Power Generation with the use of Genetic Algorithms
title Optimal Dispatch Programming of Hydroelectric Power Generation with the use of Genetic Algorithms
spellingShingle Optimal Dispatch Programming of Hydroelectric Power Generation with the use of Genetic Algorithms
Marcelino, Carolina Gil
Electric Dispatch
Optimization
Genetic Algorithms
Simulation
title_short Optimal Dispatch Programming of Hydroelectric Power Generation with the use of Genetic Algorithms
title_full Optimal Dispatch Programming of Hydroelectric Power Generation with the use of Genetic Algorithms
title_fullStr Optimal Dispatch Programming of Hydroelectric Power Generation with the use of Genetic Algorithms
title_full_unstemmed Optimal Dispatch Programming of Hydroelectric Power Generation with the use of Genetic Algorithms
title_sort Optimal Dispatch Programming of Hydroelectric Power Generation with the use of Genetic Algorithms
author Marcelino, Carolina Gil
author_facet Marcelino, Carolina Gil
Wanner, Elizabeth Fialho
de Almeida, Paulo Eduardo Maciel
Farias, Gray
author_role author
author2 Wanner, Elizabeth Fialho
de Almeida, Paulo Eduardo Maciel
Farias, Gray
author2_role author
author
author
dc.contributor.author.fl_str_mv Marcelino, Carolina Gil
Wanner, Elizabeth Fialho
de Almeida, Paulo Eduardo Maciel
Farias, Gray
dc.subject.por.fl_str_mv Electric Dispatch
Optimization
Genetic Algorithms
Simulation
topic Electric Dispatch
Optimization
Genetic Algorithms
Simulation
description The population increase and the growth of buying power of home appliances cause the need of electricity power to increase every year in Brazil. Electric dispatch is defined as the attribution of operational values to each generation unit inside a power plant, given some criteria to be fulfilled. In this context, an optimal dispatch schedule for hydroelectric units in energy plants provides a greater amount of energy to be generated with less consumption of water. This paper presents an optimization solution to solve this problem for an actual plant, using Genetic Algorithms. The underlying mathematical modeling is described in details and practical validation of the proposed approach is performed through simulation experiments. In the case study, results are analysed and compared to the actual system running in a real world plant. Finally, the generality of the proposed approach is discussed and possibilities of its use to solve the same problem to other hydroelectric plants are presented.
publishDate 2013
dc.date.none.fl_str_mv 2013-12-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/23
url https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/23
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/23/10
dc.rights.driver.fl_str_mv Copyright (c) 2016 INFOCOMP Journal of Computer Science
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2016 INFOCOMP Journal of Computer Science
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Editora da UFLA
publisher.none.fl_str_mv Editora da UFLA
dc.source.none.fl_str_mv INFOCOMP Journal of Computer Science; Vol. 12 No. 2 (2013): December 2013; 12-22
1982-3363
1807-4545
reponame:INFOCOMP: Jornal de Ciência da Computação
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str INFOCOMP: Jornal de Ciência da Computação
collection INFOCOMP: Jornal de Ciência da Computação
repository.name.fl_str_mv INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv infocomp@dcc.ufla.br||apfreire@dcc.ufla.br
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