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Nash equilibria and reinforcement learning for active decision maker modelling in power markets
Krause, Thilo; Andersson, Goran; Ernst, Damien et al.
2004In Proceedings of the 6th IAEE European Conference: Modelling in Energy Economics and Policy
Peer reviewed
 

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Keywords :
electricity markets modeling; spot markets; Nash equilibria; reinforcement learning; matrix games
Abstract :
[en] In this paper, we study the behavior of power suppliers who submit their bids to the market place in order to maximize their payoffs. The market clearing mechanism is based on the locational marginal price. To study the interaction of the power suppliers, we rely on two different approaches and compare the results obtained. One approach consists of computing the Nash equilibria of the market, and the other models each player’s behavior by using reinforcement learning algorithms. Simulations are carried out on a five node power system.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Krause, Thilo
Andersson, Goran
Ernst, Damien  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Vdovina-Beck, Elena
Cherkaoui, Rachid
Germond, Alain
Language :
English
Title :
Nash equilibria and reinforcement learning for active decision maker modelling in power markets
Publication date :
2004
Event name :
6th IAEE European Conference: Modelling in Energy Economics and Policy
Event place :
Zurich, Switzerland
Event date :
2-3 September 2004
Audience :
International
Main work title :
Proceedings of the 6th IAEE European Conference: Modelling in Energy Economics and Policy
Peer reviewed :
Peer reviewed
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE]
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since 27 May 2009

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