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- handle: 10670/1.2b74we
- halshs: halshs-00871077
- doi: 10.1007/978-3-642-02956-1_5
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info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-642-02956-1_5
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Electricity markets agent-based computational economics uniform auction discriminatory auctionCiter ce document
Eric Guerci et al., « Operator's bidding strategies in the liberalized Italian power market », HAL-SHS : économie et finance, ID : 10.1007/978-3-642-02956-1_5
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This paper studies the Italian wholesale electricity market by means of a realistic agent-based computational model of the day-ahead market session, of the thermal-power production pool and of the Italian high-voltage transmission network. The aim of the paper is twofold. Firstly, it studies how the strategic behavior of the thermal power plants can influence the level of price at a national level. Secondly, it performs an empirical validation of the computational model over a period of one month which enables to assess the validity of the proposed model. In particular, three scenarios are studied and compared, i.e., the historical performance, a marginal cost based case and a strategic case where generation companies learn according to a reinforcement learning algorithm their best strategy. Results show that the strategic model reproduces real price dynamic during low- and medium- demand periods, whereas during peak-hours the strategic model tends to underestimate historical performances.