Title :
Two separate continually online trained neurocontrollers for excitation and turbine control of a turbogenerator
Author :
Venayagamoorthy, Ganesh K. ; Harley, Ronald G.
Author_Institution :
Dept. of Electron. Eng., ML Sultan Technikon, Durban, South Africa
Abstract :
This paper presents the design of two separate continually online trained (GOT) artificial neural network (ANN) controllers for excitation and turbine control of a turbogenerator connected to the infinite bus through a transmission line. These neurocontrollers augment/replace the conventional automatic voltage regulator and the turbine governor of a generator. A third COT ANN is used to identify the complex nonlinear dynamics of the power system. Results are presented to show that the two COT ANN controllers can control turbogenerators under steady state as well as transient conditions and thus allow turbogenerators to operate more closely to their steady state stability limits
Keywords :
learning (artificial intelligence); machine control; neurocontrollers; nonlinear dynamical systems; turbines; turbogenerators; artificial neural network controllers; automatic voltage regulator; continually online trained neurocontrollers; excitation; steady state; transient conditions; transmission line; turbine control; turbogenerator; Artificial neural networks; Automatic control; Neurocontrollers; Power system dynamics; Power system stability; Power system transients; Power transmission lines; Steady-state; Turbines; Turbogenerators;
Conference_Titel :
Industry Applications Conference, 2000. Conference Record of the 2000 IEEE
Conference_Location :
Rome
Print_ISBN :
0-7803-6401-5
DOI :
10.1109/IAS.2000.882046