IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i7p883-d103217.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/7/883/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/10/7/883/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Westner, Günther & Madlener, Reinhard, 2011. "Development of cogeneration in Germany: A mean-variance portfolio analysis of individual technology’s prospects in view of the new regulatory framework," Energy, Elsevier, vol. 36(8), pages 5301-5313.
    2. repec:ers:journl:v:xv:y:2012:i:sie:p:3-30 is not listed on IDEAS
    3. Ruangpattana, Suriya & Preckel, Paul V. & Gotham, Douglas J. & Muthuraman, Kumar & Velástegui, Marco & Morin, Thomas L. & Uhan, Nelson A., 2012. "Diversification of fuel costs accounting for load variation," Energy Policy, Elsevier, vol. 42(C), pages 400-408.
    4. de-Llano Paz, Fernando & Antelo, Susana Iglesias & Calvo Silvosa, Anxo & Soares, Isabel, 2014. "The technological and environmental efficiency of the EU-27 power mix: An evaluation based on MPT," Energy, Elsevier, vol. 69(C), pages 67-81.
    5. Madlener, Reinhard & Glensk, Barbara & Weber, Veronika, 2011. "Fuzzy Portfolio Optimization of Onshore Wind Power Plants," FCN Working Papers 10/2011, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Jul 2014.
    6. Zhu, Lei & Fan, Ying, 2010. "Optimization of China's generating portfolio and policy implications based on portfolio theory," Energy, Elsevier, vol. 35(3), pages 1391-1402.
    7. deLlano-Paz, Fernando & Calvo-Silvosa, Anxo & Iglesias Antelo, Susana & Soares, Isabel, 2015. "The European low-carbon mix for 2030: The role of renewable energy sources in an environmentally and socially efficient approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 49-61.
    8. Marrero, Gustavo A. & Puch, Luis A. & Ramos-Real, Francisco J., 2015. "Mean-variance portfolio methods for energy policy risk management," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 246-264.
    9. Delarue, Erik & De Jonghe, Cedric & Belmans, Ronnie & D'haeseleer, William, 2011. "Applying portfolio theory to the electricity sector: Energy versus power," Energy Economics, Elsevier, vol. 33(1), pages 12-23, January.
    10. Madlener, Reinhard & Wenk, Christioph, 2008. "Efficient Investment Portfolios for the Swiss Electricity Supply Sector," FCN Working Papers 2/2008, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    11. Roques, Fabien A. & Newbery, David M. & Nuttall, William J., 2008. "Fuel mix diversification incentives in liberalized electricity markets: A Mean-Variance Portfolio theory approach," Energy Economics, Elsevier, vol. 30(4), pages 1831-1849, July.
    12. Locatelli, Giorgio & Mancini, Mauro, 2011. "Large and small baseload power plants: Drivers to define the optimal portfolios," Energy Policy, Elsevier, vol. 39(12), pages 7762-7775.
    13. Pérez Odeh, Rodrigo & Watts, David & Flores, Yarela, 2018. "Planning in a changing environment: Applications of portfolio optimisation to deal with risk in the electricity sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3808-3823.
    14. Gotham, Douglas & Muthuraman, Kumar & Preckel, Paul & Rardin, Ronald & Ruangpattana, Suriya, 2009. "A load factor based mean-variance analysis for fuel diversification," Energy Economics, Elsevier, vol. 31(2), pages 249-256, March.
    15. Fernando de Llano Paz & Anxo Calvo Silvosa & Martín Portos García, 2012. "The Problem of Determining the Energy Mix: from the Portfolio Theory to the Reality of Energy Planning in the Spanish Case," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 3-30.
    16. 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.
    17. Zhang, Mingming & Tang, Yamei & Liu, Liyun & Zhou, Dequn, 2022. "Optimal investment portfolio strategies for power enterprises under multi-policy scenarios of renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    18. deLlano-Paz, Fernando & Calvo-Silvosa, Anxo & Antelo, Susana Iglesias & Soares, Isabel, 2017. "Energy planning and modern portfolio theory: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 636-651.
    19. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    20. Christos N. Dimitriadis & Evangelos G. Tsimopoulos & Michael C. Georgiadis, 2021. "A Review on the Complementarity Modelling in Competitive Electricity Markets," Energies, MDPI, vol. 14(21), pages 1-27, November.
    21. Allan, Grant & Eromenko, Igor & McGregor, Peter & Swales, Kim, 2011. "The regional electricity generation mix in Scotland: A portfolio selection approach incorporating marine technologies," Energy Policy, Elsevier, vol. 39(1), pages 6-22, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:883-:d:103217. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.