Design of a Resistive Brake Controller for Power System Stability Enhancement Using Reinforcement Learning

Glavic, Mevludin

doi:10.1109/TCST.2005.847339

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Design of a Resistive Brake Controller for Power System Stability Enhancement Using Reinforcement Learning

Glavic, Mevludin

2005 • In IEEE Transactions on Control Systems Technology, 13 (5), p. 743-751

Peer Reviewed verified by ORBi

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https://hdl.handle.net/2268/209460

DOI
10.1109/TCST.2005.847339

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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 :

Issue :

Pages :

743-751

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 13 April 2017

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