Agent-based model of the Italian wholesale electricity market

Mohammad Ali Rastegar, Eric Guerci and Silvano Cincotti
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Mohammad Ali Rastegar: Chercheur indépendant
Silvano Cincotti: DIME - Dipartimento di ingegneria meccanica, energetica, gestionale e dei trasporti - UniGe - Università degli studi di Genova = University of Genoa

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Abstract: This paper proposes an agent-based computational model of the Italian wholesale electricity market. In particular, the aim of the paper is to study how the strategic behavior of the thermal power plants can influence the level of price at a zonal and national level with respect of a typical daily load profile. The model reproduces exactly the market clearing procedure, i.e., day-ahead market (DAM) and the Italian high-voltage transmission network with its zonal subdivision. Furthermore the daily load profile and all installed thermal power plants are realistically considered. Three price cases are studied and compared, i.e., the real situation, a cost based case and a final case where the generation companies learn according to a reinforcement learning algorithm their best strategy. The empirical validation at a national level enables to point out that the model replicate correctly historical data except for some peak-load hours.

Keywords: Electricity markets; agent-based computational economics; multi-agent learning (search for similar items in EconPapers)
Date: 2009-05-27
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Citations: View citations in EconPapers (6)

Published in Energy Market, 2009. EEM 2009. 6th International Conference on the European, May 2009, Leuven, Belgium. pp.1-7, ⟨10.1109/EEM.2009.5207128⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-00871127

DOI: 10.1109/EEM.2009.5207128

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