A co-evolutionary approach to modelling the behaviour of participants in competitive electricity markets

The behaviour of participants in electricity markets is complex and is more appropriately studied as an economic game rather than as an optimisation problem. In this paper, a co-evolutionary approach has been developed to study the dynamic behaviour of participants over many trading intervals. Each market participant is represented by a trading agent. The bidding strategy of each agent is modelled as a set of bidding actions, one for each possible discrete state of the state space observed by the agent. Trading agents co-evolve their own populations of bidding strategies using a Genetic Algorithm. Simulation results have shown that in this competitive environment, participants can learn to improve their trading profit and the proposed state-based bidding strategy can help facilitate this learning process.