Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/7323
Título: Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning
Autor: Pinto, Tiago
Vale, Zita
Praça, Isabel
Pires, E.
Lopes, Fernando
Palavras-chave: Adaptive learning
Bilateral contracts
Decision support
Electricity markets
Game theory
Multi-agent simulation
Data: Set-2015
Editora: MDPI
Relatório da Série N.º: Energies;Vol. 8, Issue 9
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 operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.
Peer review: yes
URI: http://hdl.handle.net/10400.22/7323
DOI: 10.3390/en8099817
Versão do Editor: http://www.mdpi.com/1996-1073/8/9/9817/htm
Aparece nas colecções:ISEP – GECAD – Artigos

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