DocumentCode :
1749202
Title :
Excitation and turbine neurocontrol with derivative adaptive critics of multiple generators on the power grid
Author :
Venayagamoorthy, Ganesh K. ; Harley, R.G. ; Wunsch, D.C.
Author_Institution :
Dept. of Electron. Eng., ML Sultan Tech., Durban, South Africa
Volume :
2
fYear :
2001
fDate :
2001
Firstpage :
984
Abstract :
Based on derivative adaptive critics, neurocontrollers for excitation and turbine control of multiple generators on the electric power grid are presented. The feedback variables are completely based on local measurements. Simulations on a three-machine power system demonstrate that the neurocontrollers are much more effective than conventional PID controllers, the automatic voltage regulators and the governors, for improving the dynamic performance and stability under small and large disturbances
Keywords :
dynamics; learning (artificial intelligence); neurocontrollers; optimisation; power system control; power system stability; derivative adaptive critics; dynamics; excitation; heuristics; learning algorithm; neurocontrollers; power system control; stability; three-machine power system; turbine generator; Adaptive control; Automatic generation control; Electric variables control; Mesh generation; Neurocontrollers; Power system dynamics; Power system simulation; Power system stability; Programmable control; Turbines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
ISSN :
1098-7576
Print_ISBN :
0-7803-7044-9
Type :
conf
DOI :
10.1109/IJCNN.2001.939494
Filename :
939494
Link To Document :
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