Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach

Detalhes bibliográficos
Autor(a) principal: João Tomé Saraiva
Data de Publicação: 2016
Outros Autores: José Carlos Sousa
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/10216/84384
Resumo: The restructuring of power systems with the introduction of electricity markets and decentralized structures increased the number of participating entities. This is particularly true in generation and retailing which are now provided under competition. Accordingly, it is important to develop models to simulate the behavior of these agents and to optimize their participation in electricity markets. Among them, it is essential to adequately model generation agents namely in countries having a large share of hydro stations. This paper describes an agent-based approach to model the day-ahead electricity market having a particular emphasis on hydro generation. Apart from the characterization of the agents, the paper details the introduction of the Q-Learning algorithm in the model as a way to enhance the performance of generation agents. This paper also presents some preliminary results taking the Portuguese generation system as an example.
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spelling Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approachEngenharia electrotécnica, Engenharia electrotécnica, electrónica e informáticaElectrical engineering, Electrical engineering, Electronic engineering, Information engineeringThe restructuring of power systems with the introduction of electricity markets and decentralized structures increased the number of participating entities. This is particularly true in generation and retailing which are now provided under competition. Accordingly, it is important to develop models to simulate the behavior of these agents and to optimize their participation in electricity markets. Among them, it is essential to adequately model generation agents namely in countries having a large share of hydro stations. This paper describes an agent-based approach to model the day-ahead electricity market having a particular emphasis on hydro generation. Apart from the characterization of the agents, the paper details the introduction of the Q-Learning algorithm in the model as a way to enhance the performance of generation agents. This paper also presents some preliminary results taking the Portuguese generation system as an example.2016-06-062016-06-06T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://repositorio-aberto.up.pt/handle/10216/84384eng10.1109/EEM.2016.7521334João Tomé SaraivaJosé Carlos Sousainfo: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:RCAAP2023-11-29T12:36:31Zoai:repositorio-aberto.up.pt:10216/84384Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:23:25.003456Repositório 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 Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach
title Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach
spellingShingle Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach
João Tomé Saraiva
Engenharia electrotécnica, Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electrical engineering, Electronic engineering, Information engineering
title_short Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach
title_full Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach
title_fullStr Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach
title_full_unstemmed Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach
title_sort Simulation of the operation of hydro plants in an electricity market using agent based models - Introducing a Q Learning approach
author João Tomé Saraiva
author_facet João Tomé Saraiva
José Carlos Sousa
author_role author
author2 José Carlos Sousa
author2_role author
dc.contributor.author.fl_str_mv João Tomé Saraiva
José Carlos Sousa
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 The restructuring of power systems with the introduction of electricity markets and decentralized structures increased the number of participating entities. This is particularly true in generation and retailing which are now provided under competition. Accordingly, it is important to develop models to simulate the behavior of these agents and to optimize their participation in electricity markets. Among them, it is essential to adequately model generation agents namely in countries having a large share of hydro stations. This paper describes an agent-based approach to model the day-ahead electricity market having a particular emphasis on hydro generation. Apart from the characterization of the agents, the paper details the introduction of the Q-Learning algorithm in the model as a way to enhance the performance of generation agents. This paper also presents some preliminary results taking the Portuguese generation system as an example.
publishDate 2016
dc.date.none.fl_str_mv 2016-06-06
2016-06-06T00:00:00Z
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/10216/84384
url https://repositorio-aberto.up.pt/handle/10216/84384
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1109/EEM.2016.7521334
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
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