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Strategic Bidding for Electricity Markets Negotiation Using Support Vector Machines

  • Rafael Pereira
  • Tiago M. Sousa
  • Tiago Pinto
  • Isabel Praça
  • Zita Vale
  • Hugo Morais
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 293)

Abstract

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets environment. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and validated by being included in ALBidS and then compared with the application of an Artificial Neural Network, originating promising results. The proposed approach is tested and validated using real electricity markets data from MIBEL - Iberian market operator.

Keywords

Support Vector Machine Artificial Neural Network Radial Basis Function Mean Absolute Percentage Error Electricity Market 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Rafael Pereira
    • 1
  • Tiago M. Sousa
    • 1
  • Tiago Pinto
    • 1
  • Isabel Praça
    • 1
  • Zita Vale
    • 1
  • Hugo Morais
    • 2
  1. 1.GECAD – Knowledge Engineering and Decision-Support Research CenterInstitute of Engineering – Polytechnic of Porto (ISEP/IPP)PortoPortugal
  2. 2.Automation and Control GroupTechnical University of DenmarkCopenhagenDenmark

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