Replicator agents for electricity markets

The main focus of this paper is to explore the dynamic behavior of an auction system for an electricity market. In order to cope with this complex problem, agent-based simulation has been previously used, where autonomous agents learn through the results of repeated auctions. In this paper, the replicator equation is introduced as a learning algorithm that can be applicable to agent-based simulation. A repeated electricity auction based on a Japanese power market is simulated with different strategy selection algorithms incorporating mechanisms for learning. The results are compared to show the applicability of the replicator equation