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Article type: Research Article
Authors: Pinto, Tiago | Praça, Isabel | Vale, Zita; * | Morais, Hugo | Sousa, Tiago M.
Affiliations: GECAD – Knowledge Engineering and Decision Support Research Centre – Polytechnic of Porto, Rua Dr. António Bernardino de Almeida, Porto, Portugal
Correspondence: [*] Corresponding author: Zita Vale is with GECAD, Knowledge Engineering and Decision-Support Research Group of the School of Engineering, Polytechnic Institute of Porto (ISEP/IPP), Rua Dr. António Bernardino de Almeida, 431, 4200-072 Porto, Portugal. Tel.: +351 228 340 511; Fax: +351 228 321 159; E-mail: zav@isep.ipp.pt.
Abstract: Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support 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 action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. 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 Electricity Market are presented and discussed.
Keywords: Decision making, electricity markets, intelligent agents, game theory, multiagent systems, scenario analysis
DOI: 10.3233/ICA-130438
Journal: Integrated Computer-Aided Engineering, vol. 20, no. 4, pp. 335-346, 2013
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