Operation planning of hydro stations using genetic algorithms considering their impact on the electricity market prices

Detalhes bibliográficos
Autor(a) principal: Carlos A. Guerreiro
Data de Publicação: 2014
Outros Autores: João Tomé Saraiva, J. C. Sousa, V. T. Mendes
Tipo de documento: Livro
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://repositorio-aberto.up.pt/handle/10216/74448
Resumo: With the advent of restructuring, generation companies have to plan the operation of their stations in order to maximize their profits. This is very relevant for companies having a large share of hydro stations, and even more if these stations have pumping capacity. This paper describes a model to plan the operation of a set of hydro stations eventually installed in cascade and admitting that some of them are pumping stations. Once a first set of operation orders is obtained using a Genetic Algorithm, their generation/load values are included in the expected market selling/buying curves and the hourly prices are updated. These prices are then used to refine the operation orders originating an iterative process so that hydro stations are price makers. The paper includes results for a hydro system in order to illustrate the application of the developed approach.
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spelling Operation planning of hydro stations using genetic algorithms considering their impact on the electricity market pricesEngenharia electrotécnica, Engenharia electrotécnica, electrónica e informáticaElectrical engineering, Electrical engineering, Electronic engineering, Information engineeringWith the advent of restructuring, generation companies have to plan the operation of their stations in order to maximize their profits. This is very relevant for companies having a large share of hydro stations, and even more if these stations have pumping capacity. This paper describes a model to plan the operation of a set of hydro stations eventually installed in cascade and admitting that some of them are pumping stations. Once a first set of operation orders is obtained using a Genetic Algorithm, their generation/load values are included in the expected market selling/buying curves and the hourly prices are updated. These prices are then used to refine the operation orders originating an iterative process so that hydro stations are price makers. The paper includes results for a hydro system in order to illustrate the application of the developed approach.20142014-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://repositorio-aberto.up.pt/handle/10216/74448eng10.1109/EEM.2014.6861210Carlos A. GuerreiroJoão Tomé SaraivaJ. C. SousaV. T. Mendesinfo: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:RCAAP2023-11-29T15:41:16Zoai:repositorio-aberto.up.pt:10216/74448Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:29:43.091516Repositório 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 Operation planning of hydro stations using genetic algorithms considering their impact on the electricity market prices
title Operation planning of hydro stations using genetic algorithms considering their impact on the electricity market prices
spellingShingle Operation planning of hydro stations using genetic algorithms considering their impact on the electricity market prices
Carlos A. Guerreiro
Engenharia electrotécnica, Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electrical engineering, Electronic engineering, Information engineering
title_short Operation planning of hydro stations using genetic algorithms considering their impact on the electricity market prices
title_full Operation planning of hydro stations using genetic algorithms considering their impact on the electricity market prices
title_fullStr Operation planning of hydro stations using genetic algorithms considering their impact on the electricity market prices
title_full_unstemmed Operation planning of hydro stations using genetic algorithms considering their impact on the electricity market prices
title_sort Operation planning of hydro stations using genetic algorithms considering their impact on the electricity market prices
author Carlos A. Guerreiro
author_facet Carlos A. Guerreiro
João Tomé Saraiva
J. C. Sousa
V. T. Mendes
author_role author
author2 João Tomé Saraiva
J. C. Sousa
V. T. Mendes
author2_role author
author
author
dc.contributor.author.fl_str_mv Carlos A. Guerreiro
João Tomé Saraiva
J. C. Sousa
V. T. Mendes
dc.subject.por.fl_str_mv Engenharia electrotécnica, Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electrical engineering, Electronic engineering, Information engineering
topic Engenharia electrotécnica, Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electrical engineering, Electronic engineering, Information engineering
description With the advent of restructuring, generation companies have to plan the operation of their stations in order to maximize their profits. This is very relevant for companies having a large share of hydro stations, and even more if these stations have pumping capacity. This paper describes a model to plan the operation of a set of hydro stations eventually installed in cascade and admitting that some of them are pumping stations. Once a first set of operation orders is obtained using a Genetic Algorithm, their generation/load values are included in the expected market selling/buying curves and the hourly prices are updated. These prices are then used to refine the operation orders originating an iterative process so that hydro stations are price makers. The paper includes results for a hydro system in order to illustrate the application of the developed approach.
publishDate 2014
dc.date.none.fl_str_mv 2014
2014-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/book
format book
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://repositorio-aberto.up.pt/handle/10216/74448
url https://repositorio-aberto.up.pt/handle/10216/74448
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1109/EEM.2014.6861210
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
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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
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