Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.22/5933 |
Resumo: | Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed. |
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Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysisDecision makingElectricity marketsIntelligent agentsGame theoryMultiagent systemsScenario analysisElectricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.IOS PressRepositório Científico do Instituto Politécnico do PortoPinto, TiagoPraça, IsabelVale, ZitaMorais, HugoSousa, Tiago2015-05-05T16:16:07Z2013-092013-09-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/5933eng10.3233/ICA-130438info: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:RCAAP2023-03-13T12:46:05Zoai:recipp.ipp.pt:10400.22/5933Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:26:33.014616Repositório 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 |
Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis |
title |
Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis |
spellingShingle |
Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis Pinto, Tiago Decision making Electricity markets Intelligent agents Game theory Multiagent systems Scenario analysis |
title_short |
Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis |
title_full |
Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis |
title_fullStr |
Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis |
title_full_unstemmed |
Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis |
title_sort |
Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis |
author |
Pinto, Tiago |
author_facet |
Pinto, Tiago Praça, Isabel Vale, Zita Morais, Hugo Sousa, Tiago |
author_role |
author |
author2 |
Praça, Isabel Vale, Zita Morais, Hugo Sousa, Tiago |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
Pinto, Tiago Praça, Isabel Vale, Zita Morais, Hugo Sousa, Tiago |
dc.subject.por.fl_str_mv |
Decision making Electricity markets Intelligent agents Game theory Multiagent systems Scenario analysis |
topic |
Decision making Electricity markets Intelligent agents Game theory Multiagent systems Scenario analysis |
description |
Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-09 2013-09-01T00:00:00Z 2015-05-05T16:16:07Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.22/5933 |
url |
http://hdl.handle.net/10400.22/5933 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.3233/ICA-130438 |
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.publisher.none.fl_str_mv |
IOS Press |
publisher.none.fl_str_mv |
IOS Press |
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 |
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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) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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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 |
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1799131360331300864 |