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Initial Solution Heuristic for Portfolio Optimization of Electricity Markets Participation

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Highlights of Practical Applications of Cyber-Physical Multi-Agent Systems (PAAMS 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 722))

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Abstract

Meta-heuristic search methods are used to find near optimal global solutions for difficult optimization problems. These meta-heuristic processes usually require some kind of knowledge to overcome the local optimum locations. One way to achieve diversification is to start the search procedure from a solution already obtained through another method. Since this solution is already validated the algorithm will converge easily to a greater global solution. In this work, several well-known meta-heuristics are used to solve the problem of electricity markets participation portfolio optimization. Their search performance is compared to the performance of a proposed hybrid method (ad-hoc heuristic to generate the initial solution, which is combined with the search method). The addressed problem is the portfolio optimization for energy markets participation, where there are different markets where it is possible to negotiate. In this way the result will be the optimal allocation of electricity in the different markets in order to obtain the maximum return quantified through the objective function.

This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO) and grant agreement No 703689 (project ADAPT); and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013.

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Author information

Authors and Affiliations

  1. GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Institute of Engineering, Polytechnic of Porto (ISEP/IPP), Porto, Portugal

    Ricardo Faia, Tiago Pinto & Zita Vale

  2. BISITE Research Centre, University of Salamanca (US), Salamanca, Spain

    Tiago Pinto

Authors
  1. Ricardo Faia
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  2. Tiago Pinto
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  3. Zita Vale
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Corresponding author

Correspondence to Ricardo Faia .

Editor information

Editors and Affiliations

  1. Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Madrid, Spain

    Javier Bajo

  2. Polytechnic Institute of Porto, Porto, Portugal

    Zita Vale

  3. University of Southern Denmark, Odense, Denmark

    Kasper Hallenborg

  4. University of Porto, Porto, Portugal

    Ana Paula Rocha

  5. Lille University of Science and Technology, Lille, France

    Philippe Mathieu

  6. Poznan University of Technology, Poznan, Poland

    Pawel Pawlewski

  7. Polytechnic University of Valencia, Valencia, Spain

    Elena Del Val

  8. University of Minho, Braga, Portugal

    Paulo Novais

  9. National Laboratory of Energy and Geology, Lisbon, Portugal

    Fernando Lopes

  10. National University of Colombia, Manizales, Caldas, Colombia

    Nestor D. Duque Méndez

  11. Polytechnic University of Valencia, Valencia, Spain

    Vicente Julián

  12. Malmö University, Malmo, Sweden

    Johan Holmgren

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Faia, R., Pinto, T., Vale, Z. (2017). Initial Solution Heuristic for Portfolio Optimization of Electricity Markets Participation. In: Bajo, J., et al. Highlights of Practical Applications of Cyber-Physical Multi-Agent Systems. PAAMS 2017. Communications in Computer and Information Science, vol 722. Springer, Cham. https://doi.org/10.1007/978-3-319-60285-1_11

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  • DOI: https://doi.org/10.1007/978-3-319-60285-1_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60284-4

  • Online ISBN: 978-3-319-60285-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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