DocumentCode :
2441565
Title :
Rearch on RBF Neural Network Fuzzy Control for STATC0M
Author :
Li, Yang ; Xiangjie, Chen
Author_Institution :
Dept. of Electr. & Autom. Eng., Nanchang Univ., Nanchang, China
Volume :
1
fYear :
2009
fDate :
26-27 Aug. 2009
Firstpage :
413
Lastpage :
416
Abstract :
The basic principle for static synchronous compensator is analyzed in this paper, a new mode controller for STATCOM is proposed, which is based on RBF neural network and fuzzy control theory. The controller can improve the power angle stability for the power system and the local voltage characteristics. The power system transient simulation results on a single-machine infinite-bus system which is include STATCOM shown that the RBF neural network fuzzy controller can improve stability and dynamic response characteristics for the power system more effectively in contrast to conventional STATCOM controllers. The availability in this control method has been verified with digital simulation.
Keywords :
digital simulation; dynamic response; fuzzy control; neurocontrollers; stability; static VAr compensators; RBF neural network fuzzy control; STATCOM controllers; digital simulation; dynamic response characteristics; local voltage characteristics; new mode controller; power angle stability; radial basis function networks; single-machine infinite-bus system; static synchronous compensator; Automatic voltage control; Control systems; Fuzzy control; Neural networks; Power system analysis computing; Power system dynamics; Power system simulation; Power system stability; Power system transients; Voltage control; RBF neural network; STATCOM; fuzzy control; simulation; single-machine infinite-bus system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics, 2009. IHMSC '09. International Conference on
Conference_Location :
Hangzhou, Zhejiang
Print_ISBN :
978-0-7695-3752-8
Type :
conf
DOI :
10.1109/IHMSC.2009.111
Filename :
5336126
Link To Document :
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