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11

PKDD
2000
Springer

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Application of Reinforcement Learning to Electrical Power System Closed-Loop Emergency Control

13 years 8 months ago

Application of Reinforcement Learning to Electrical Power System Closed-Loop Emergency Control

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This paper investigates the use of reinforcement learning in electric power system emergency control. The approach consists of using numerical simulations together with on-policy Monte Carlo control to determine a discrete switching control law to trip generators so as to avoid loss of synchronism. The proposed approach is tested on a model of a real large scale power system and results are compared with a quasioptimal control law designed by a brute force approach for this system.

Christophe Druet, Damien Ernst, Louis Wehenkel

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Control Law | Data Mining | Discrete Switching Control | Monte Carlo Control | PKDD 2000 |

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Added	25 Aug 2010
Updated	25 Aug 2010
Type	Conference
Year	2000
Where	PKDD
Authors	Christophe Druet, Damien Ernst, Louis Wehenkel

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