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

Volume

3

fYear

2002

fDate

25-25 July 2002

Firstpage

1534

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Engineering Society Summer Meeting, 2002 IEEE

Conference_Location

Chicago, IL, USA

Print_ISBN

0-7803-7518-1

Type

conf

DOI

10.1109/PESS.2002.1043648

Filename

1043648