DocumentCode :
3383312
Title :
Learning models to simulate electricity markets
Author :
Xiuming Dong
Author_Institution :
State Key Lab. of Water Resources & Hydropower Eng. Sci., Wuhan Univ., Wuhan, China
fYear :
2013
fDate :
23-25 March 2013
Firstpage :
726
Lastpage :
728
Abstract :
In this paper, we explore the reasons for electricity price diversity in electricity market from the view point of game learning theory. It is assumed each supplier can choose a learning model to help him to make strategy selection from Cournot adjustment and fictitious play learning models, which can produce two single learning models (when all suppliers choose the same learning model) and numerous multiple learning models (when different supplier chooses different learning model).Simulation results show numerical multiple learning models bring large price diversity to electricity market which can lead to market instability. Therefore, market designers should develop market rules to avoid this kind of behavior risks.
Keywords :
game theory; learning (artificial intelligence); power engineering computing; power markets; pricing; Cournot adjustment; electricity market; electricity price diversity; fictitious play learning model; game learning theory; market instability; strategy selection; Biological system modeling; Computational modeling; Electricity; Electricity supply industry; Games; Load modeling; Numerical models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Technology (ICIST), 2013 International Conference on
Conference_Location :
Yangzhou
Print_ISBN :
978-1-4673-5137-9
Type :
conf
DOI :
10.1109/ICIST.2013.6747648
Filename :
6747648
Link To Document :
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