Article (Scientific journals)
Design of a Resistive Brake Controller for Power System Stability Enhancement Using Reinforcement Learning
Glavic, Mevludin
2005In IEEE Transactions on Control Systems Technology, 13 (5), p. 743-751
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Keywords :
Closed-loop control; reinforcement learning; resistive brake
Abstract :
[en] Computation of the closed-loop control laws, capable to realize multiple switching operations of a resistive brake (RB) aimed to enhance power system stability, is the primary topic of this brief. The problem is formulated as a multistage decision problem and use of a model-based reinforcement learning (RL) method, known as prioritized sweeping, to compute the control law is considered. To illustrate the performances of the proposed approach results obtained using the model of a synthetic four-machine power system are given. Handling measurement transmission delays is discussed and illustrated.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Glavic, Mevludin ;  Université de Liège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation : Optimisation discrète
Language :
English
Title :
Design of a Resistive Brake Controller for Power System Stability Enhancement Using Reinforcement Learning
Publication date :
September 2005
Journal title :
IEEE Transactions on Control Systems Technology
ISSN :
1063-6536
Publisher :
IEEE, Piscataway, United States - New Jersey
Volume :
13
Issue :
5
Pages :
743-751
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 13 April 2017

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