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
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;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.939494