Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

Detalhes bibliográficos
Autor(a) principal: Pinto,T
Data de Publicação: 2015
Outros Autores: Vale,Z, Praca,I, Eduardo Pires, Lopes,F
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/4897
http://dx.doi.org/10.3390/en8099817
Resumo: This paper presents a decision support methodology for electricity market players' bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method's adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts' negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems' technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players' decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operatorMIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts' negotiations.
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spelling Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive LearningThis paper presents a decision support methodology for electricity market players' bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method's adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts' negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems' technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players' decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operatorMIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts' negotiations.2017-12-22T23:26:07Z2015-01-01T00:00:00Z2015info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/4897http://dx.doi.org/10.3390/en8099817engPinto,TVale,ZPraca,IEduardo PiresLopes,Finfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:04Zoai:repositorio.inesctec.pt:123456789/4897Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:38.687299Repositório 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 Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning
title Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning
spellingShingle Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning
Pinto,T
title_short Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning
title_full Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning
title_fullStr Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning
title_full_unstemmed Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning
title_sort Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning
author Pinto,T
author_facet Pinto,T
Vale,Z
Praca,I
Eduardo Pires
Lopes,F
author_role author
author2 Vale,Z
Praca,I
Eduardo Pires
Lopes,F
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Pinto,T
Vale,Z
Praca,I
Eduardo Pires
Lopes,F
description This paper presents a decision support methodology for electricity market players' bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method's adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts' negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems' technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players' decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operatorMIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts' negotiations.
publishDate 2015
dc.date.none.fl_str_mv 2015-01-01T00:00:00Z
2015
2017-12-22T23:26:07Z
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dc.identifier.uri.fl_str_mv http://repositorio.inesctec.pt/handle/123456789/4897
http://dx.doi.org/10.3390/en8099817
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http://dx.doi.org/10.3390/en8099817
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