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An Ad-Hoc Initial Solution Heuristic for Metaheuristic Optimization of Energy Market Participation Portfolios

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  • Ricardo Faia

    (Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD), Institute of Engineering, Polytechnic of Porto (ISEP/IPP), Rua Dr. António Bernardino de Almeida, 431, 4200-072 Porto, Portugal)

  • Tiago Pinto

    (Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD), Institute of Engineering, Polytechnic of Porto (ISEP/IPP), Rua Dr. António Bernardino de Almeida, 431, 4200-072 Porto, Portugal
    Bioinformatics, Intelligent Systems and Educational Technology (BISITE) Research Centre, University of Salamanca, Calle Espejo, s/n, 37007 Salamanca, Spain)

  • Zita Vale

    (Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD), Institute of Engineering, Polytechnic of Porto (ISEP/IPP), Rua Dr. António Bernardino de Almeida, 431, 4200-072 Porto, Portugal)

  • Juan Manuel Corchado

    (Bioinformatics, Intelligent Systems and Educational Technology (BISITE) Research Centre, University of Salamanca, Calle Espejo, s/n, 37007 Salamanca, Spain)

Abstract

The deregulation of the electricity sector has culminated in the introduction of competitive markets. In addition, the emergence of new forms of electric energy production, namely the production of renewable energy, has brought additional changes in electricity market operation. Renewable energy has significant advantages, but at the cost of an intermittent character. The generation variability adds new challenges for negotiating players, as they have to deal with a new level of uncertainty. In order to assist players in their decisions, decision support tools enabling assisting players in their negotiations are crucial. Artificial intelligence techniques play an important role in this decision support, as they can provide valuable results in rather small execution times, namely regarding the problem of optimizing the electricity markets participation portfolio. This paper proposes a heuristic method that provides an initial solution that allows metaheuristic techniques to improve their results through a good initialization of the optimization process. Results show that by using the proposed heuristic, multiple metaheuristic optimization methods are able to improve their solutions in a faster execution time, thus providing a valuable contribution for players support in energy markets negotiations.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:883-:d:103217
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    References listed on IDEAS

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    1. Sioshansi, Fereidoon P., 2008. "Competitive Electricity Markets: Questions Remain about Design, Implementation, Performance," The Electricity Journal, Elsevier, vol. 21(2), pages 74-87, March.
    2. Bar-Lev, Dan & Katz, Steven, 1976. "A Portfolio Approach to Fossil Fuel Procurement in the Electric Utility Industry," Journal of Finance, American Finance Association, vol. 31(3), pages 933-947, June.
    3. Coelho, Leandro dos Santos, 2008. "A quantum particle swarm optimizer with chaotic mutation operator," Chaos, Solitons & Fractals, Elsevier, vol. 37(5), pages 1409-1418.
    4. Marin Cerjan & Marin Matijaš & Marko Delimar, 2014. "Dynamic Hybrid Model for Short-Term Electricity Price Forecasting," Energies, MDPI, vol. 7(5), pages 1-15, May.
    5. Li, Hongyan & Tesfatsion, Leigh, 2009. "Development of Open Source Software for Power Market Research: The AMES Test Bed," ISU General Staff Papers 200901010800001391, Iowa State University, Department of Economics.
    6. Boris Krey & Peter Zweifel, 2006. "Efficient Electricity Portfolios for Switzerland and the United States," SOI - Working Papers 0602, Socioeconomic Institute - University of Zurich.
    7. 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.
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