Evolutionary computation enabled game theory based modelling of electricity market behaviours and applications

Yin Jin, Chen Wei, Li Yun

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

The collapse of the Californian electricity market system in 2001 has highlighted urgency in research in intelligent electricity trading systems and strategies involving both suppliers and customs. In their trading systems, power generation companies under the New Electricity Trading Arrangement (NETA) of the UK are now developing gaming strategies. However, modelling of such "intelligent" market behaviours is extremely challenging, because traditional mathematical and computer modelling techniques cannot cope with the involvement of game theory. In this paper, evolutionary computation enabled modelling of such system is presented. Both competitive and cooperative game theory strategies are taken into account in evolving the intelligent model. The model then leads to intelligent trading strategy development and decision support. Experimental tests, verification and validation are carried out with various strategies, using different model scales and data published by NETA. Results show that evolutionary computation enabled game theory involved modelling and decision making provides an effective tool for NETA trading analysis, prediction and support.

Original languageEnglish
Title of host publication2007 IEEE Congress on Evolutionary Computation, CEC 2007
Pages1896-1903
Number of pages8
DOIs
Publication statusPublished - 1 Dec 2007
Event2007 IEEE Congress on Evolutionary Computation, CEC 2007 - , Singapore
Duration: 25 Sep 200728 Sep 2007

Conference

Conference2007 IEEE Congress on Evolutionary Computation, CEC 2007
CountrySingapore
Period25/09/0728/09/07

    Fingerprint

Keywords

  • electricity market
  • evolutionary computation
  • game theory
  • NETA

Cite this

Jin, Y., Wei, C., & Yun, L. (2007). Evolutionary computation enabled game theory based modelling of electricity market behaviours and applications. In 2007 IEEE Congress on Evolutionary Computation, CEC 2007 (pp. 1896-1903). [4424705] https://doi.org/10.1109/CEC.2007.4424705