Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis

Detalhes bibliográficos
Autor(a) principal: Pinto, Tiago
Data de Publicação: 2013
Outros Autores: Praça, Isabel, Vale, Zita, Morais, Hugo, Sousa, Tiago
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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spelling 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
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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
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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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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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