electricity market modelling; game theory; reinforcement learning
Abstract :
[en] In this paper we compare Nash equilibria analysis and agent-based modelling for assessing the market dynamics of network-constrained pool markets. Power suppliers submit their bids to the market place in order to maximize their payoffs, where we apply reinforcement learning as a behavioral agent model. The market clearing mechanism is based on the locational marginal pricing scheme. Simulations are carried out on a benchmark power system. We show how the evolution of the agent-based approach relates to the existence of a unique Nash equilibrium or multiple equilibria in the system. Additionally, the parameter sensitivity of the results is discussed. (C) 2006 Elsevier Ltd. All rights reserved.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Krause, Thilo
Beck, Elena Vdovina
Cherkaoui, Rachid
Germond, Alain
Andersson, Goran
Ernst, Damien ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Language :
English
Title :
A comparison of Nash equilibria analysis and agent-based modelling for power markets
Publication date :
November 2006
Journal title :
International Journal of Electrical Power and Energy Systems
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