Title :
A practical continually online trained artificial neural network controller for a turbogenerator
Author :
Venayagamoorthy, Ganesh K. ; Harley, Ronald G.
Author_Institution :
Dept. of Electr. Eng., Natal Univ., Durban, South Africa
Abstract :
This paper reports on the simulation and practical studies carried out on a single turbogenerator connected to an infinite bus through a short transmission line, with a continually online trained (COT) artificial neural network (ANN) controller to identify the turbogenerator, and another COT ANN to control the turbogenerator. This identifier/controller augments/replaces the automatic voltage regulator and the turbine governor. Results are presented to show that this COT ANN identifier/controller has the potential to allow turbogenerators to operate more closely to their steady-state stability limits and nevertheless “ride through” severe transient disturbances such as three phase faults. This allows greater usage of existing power plant
Keywords :
control system analysis; learning (artificial intelligence); machine control; machine theory; neurocontrollers; stability; turbogenerators; artificial neural network controller; automatic voltage regulator; continual online training; control simulation; disturbance ride-through; identifier/controller; steady-state stability limits; three-phase faults; turbine governor; turbogenerator; Artificial neural networks; Automatic control; Automatic voltage control; Fault diagnosis; Power transmission lines; Regulators; Stability; Steady-state; Turbines; Turbogenerators;
Conference_Titel :
Industrial Electronics, 1998. Proceedings. ISIE '98. IEEE International Symposium on
Conference_Location :
Pretoria
Print_ISBN :
0-7803-4756-0
DOI :
10.1109/ISIE.1998.711552
