Optimal Dispatch Programming of Hydroelectric Power Generation with the use of Genetic Algorithms
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , , |
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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INFOCOMP: Jornal de Ciência da Computação |
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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 |
_version_ |
1799874739970244608 |