DocumentCode :
1578753
Title :
A robust artificial neural network based speed/voltage regulator for synchronous generators
Author :
Sharof, A.M. ; Lie, Tjing T.
Author_Institution :
Dept. of Electr. Eng., New Brunswick Univ., Fredericton, NB, Canada
Volume :
1
fYear :
34881
Firstpage :
384
Abstract :
The paper presents a novel coordinated excitation/governor artificial neural network (ANN) based controller for AC synchronous generators. The proposed ANN based controller replaces the full global action of the voltage regulator, power system stabilizer, and speed governor controls. The detailed design methodology of the ANN based controller, the training, and validation results based on the performance of the best benchmark conventional excitation and speed controls are presented in the paper. The dynamic simulation results and study of the performance of ANN based coordinated control scheme in comparison with the conventional excitation/governor action are also presented in the paper
Keywords :
control system analysis computing; control system synthesis; electric machine analysis computing; learning (artificial intelligence); machine control; neurocontrollers; robust control; synchronous generators; velocity control; voltage control; voltage regulators; control design; control simulation; coordinated control scheme; dynamic simulation; excitation; governor; performance; robust neurocontroller; speed/voltage regulator; synchronous generators; training; Artificial neural networks; Control systems; Design methodology; Power system dynamics; Power system simulation; Regulators; Robustness; Synchronous generators; Velocity control; Voltage control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics, 1995. ISIE '95., Proceedings of the IEEE International Symposium on
Conference_Location :
Athens
Print_ISBN :
0-7803-7369-3
Type :
conf
DOI :
10.1109/ISIE.1995.497027
Filename :
497027
Link To Document :
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