Abstract
In this paper an agent-based approach characterizing auction-style electricity spot market dynamics is proposed. This method captures the learning and decisionmaking of rational agents which cannot be modeled using a supply-demand equilibrium approach. Because the auctions are repeated, an agent improves its decisions through time or through adaptive learning. Furthermore, instead of elaborately searching for an optimal bidding strategy for each agent, some sensible and practical bidding strategies are assigned to the agents. This strategic behavior depends highly on information available to the agents before a bidding decision is made. The model mainly focuses on understanding the role of learning by the generators and, accordingly, on their strategic bidding behavior in the market.
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