DocumentCode :
2242064
Title :
Reinforcement learning for fuzzy logic control of large scale power systems
Author :
Chan, K.H. ; Jiang, L. ; Tillotson, P.R.J. ; Wu, Q.H.
Author_Institution :
Liverpool Univ., UK
fYear :
2000
fDate :
2000
Firstpage :
42430
Lastpage :
42434
Abstract :
This paper presents an application of reinforcement learning for control of large-scale power systems. The temporal difference reinforcement learning is investigated as an online learning strategy for optimising fuzzy logic controllers of synchronous generators interconnected in the power system. The simulation study is undertaken, based on a three-machine power system which has multimode oscillations, to evaluate the proposed learning control strategy
Keywords :
learning (artificial intelligence); fuzzy logic control; fuzzy logic controller optimisation; interconnected synchronous generators; large-scale power systems; multi-machine power system; multimode oscillations; online learning strategy; temporal difference reinforcement learning; three-machine power system;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Learning Systems for Control (Ref. No. 2000/069), IEE Seminar
Conference_Location :
Birmingham
Type :
conf
DOI :
10.1049/ic:20000344
Filename :
856948
Link To Document :
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