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Energies 2015, 8(9), 9817-9842; doi:10.3390/en8099817

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

1
Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD), Institute of Engineering of the Polytechnic of Porto (ISEP/IPP), Rua Dr. António Bernardino de Almeida, 431, Porto 4200-072, Portugal
2
Universidade de Trás-os-Montes e Alto Douro (UTAD), Quinta de Prados, Vila Real 5000-801, Portugal
3
National Research Institute (LNEG), Estrada do Paco do Lumiar, 22, Lisbon 1649-038, Portugal
*
Author to whom correspondence should be addressed.
Academic Editor: Enrico Sciubba
Received: 20 June 2015 / Revised: 13 August 2015 / Accepted: 29 August 2015 / Published: 9 September 2015
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Abstract

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. View Full-Text
Keywords: adaptive learning; bilateral contracts; decision support; electricity markets; game theory; multi-agent simulation adaptive learning; bilateral contracts; decision support; electricity markets; game theory; multi-agent simulation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Pinto, T.; Vale, Z.; Praça, I.; Pires, E.J.S.; Lopes, F. Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning. Energies 2015, 8, 9817-9842.

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