Title :
A co-evolutionary approach to modelling the behaviour of participants in competitive electricity markets
Author :
Cau, Thai Doan Hoang ; Anderson, Edward James
Author_Institution :
Graduate Sch. of Manage., New South Wales Univ., Sydney, NSW, Australia
Abstract :
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.
Keywords :
evolutionary computation; game theory; genetic algorithms; power markets; power system economics; bidding actions; bidding strategy; co-evolutionary approach; competitive electricity markets; competitive environment; economic game; game theory; genetic algorithm; participants behaviour modelling; state space; state-based bidding strategy; trading agent; trading intervals; Australia; Electricity supply industry; Environmental economics; Game theory; Genetic algorithms; Nash equilibrium; Nuclear power generation; Oligopoly; Power generation economics; State-space methods;
Conference_Titel :
Power Engineering Society Summer Meeting, 2002 IEEE
Conference_Location :
Chicago, IL, USA
Print_ISBN :
0-7803-7518-1
DOI :
10.1109/PESS.2002.1043648
