Operation planning of hydro stations using genetic algorithms considering their impact on the electricity market prices
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , |
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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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 |
institution |
RCAAP |
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 |
repository.mail.fl_str_mv |
|
_version_ |
1799136207824748544 |