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Strategic bidding in electricity markets: An agent-based simulator with game theory for scenario analysis

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Authors:
  • Pinto, Tiago ;
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    Instituto Politécnico do Porto
  • Praca, Isabel ;
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    Polytechnic Institute of Porto
  • Morais, Hugo ;
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    Orcid logo0000-0001-5906-4744
    Department of Electrical Engineering, Technical University of Denmark
  • Sousa, Tiago M
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    Polytechnic Institute of Porto
DOI:
10.3233/ICA-130438
Abstract:
Electricity markets are complex environments, involving a large number of different entities, with specific charac-teristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to sup-port decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the ac-tion to be performed. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Market are pre-sented and discussed.
Type:
Journal article
Language:
English
Published in:
Integrated Computer-aided Engineering, 2013, Vol 20, Issue 4, p. 335-346
Keywords:
Decision Making; Electricity Markets; Intelligent Agents; Game Theory; Multiagent Systems; Scenario Analysis
Main Research Area:
Science/technology
Publication Status:
Published
Review type:
Peer Review
Submission year:
2013
Scientific Level:
Scientific
ID:
245378082

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