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

Author

Listed:
  • Tiago Pinto

    (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
    Universidade de Trás-os-Montes e Alto Douro (UTAD), Quinta de Prados, Vila Real 5000-801, Portugal)

  • Zita Vale

    (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)

  • Isabel Praça

    (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)

  • E. J. Solteiro Pires

    (Universidade de Trás-os-Montes e Alto Douro (UTAD), Quinta de Prados, Vila Real 5000-801, Portugal)

  • Fernando Lopes

    (National Research Institute (LNEG), Estrada do Paco do Lumiar, 22, Lisbon 1649-038, Portugal)

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.

Suggested Citation

  • Tiago Pinto & Zita Vale & Isabel Praça & E. J. Solteiro Pires & Fernando Lopes, 2015. "Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning," Energies, MDPI, vol. 8(9), pages 1-26, September.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:9:p:9817-9842:d:55448
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    References listed on IDEAS

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    Cited by:

    1. Tiago Pinto & Mohammad Ali Fotouhi Ghazvini & Joao Soares & Ricardo Faia & Juan Manuel Corchado & Rui Castro & Zita Vale, 2018. "Decision Support for Negotiations among Microgrids Using a Multiagent Architecture," Energies, MDPI, vol. 11(10), pages 1-20, September.
    2. Ricardo Faia & Tiago Pinto & Zita Vale & Juan Manuel Corchado, 2017. "An Ad-Hoc Initial Solution Heuristic for Metaheuristic Optimization of Energy Market Participation Portfolios," Energies, MDPI, vol. 10(7), pages 1-18, June.
    3. Mihai Daniel Roman & Diana Mihaela Stanculescu, 2021. "An Analysis of Countries’ Bargaining Power Derived from the Natural Gas Transportation System Using a Cooperative Game Theory Model," Energies, MDPI, vol. 14(12), pages 1-13, June.
    4. Byung-Yun Son & Eul-Bum Lee, 2019. "Using Text Mining to Estimate Schedule Delay Risk of 13 Offshore Oil and Gas EPC Case Studies During the Bidding Process," Energies, MDPI, vol. 12(10), pages 1-25, May.
    5. Pablo Benalcazar & Jacek Kamiński & Karol Stós, 2022. "An Integrated Approach to Long-Term Fuel Supply Planning in Combined Heat and Power Systems," Energies, MDPI, vol. 15(22), pages 1-22, November.
    6. Mahendra Piraveenan, 2019. "Applications of Game Theory in Project Management: A Structured Review and Analysis," Mathematics, MDPI, vol. 7(9), pages 1-31, September.

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