Title :
A continually online trained neurocontroller for excitation and turbine control of a turbogenerator
Author :
Venayagamoorthy, Ganesh K. ; Harley, Ronald G.
Author_Institution :
M L Sultan Technikon, Durban, South Africa
fDate :
9/1/2001 12:00:00 AM
Abstract :
The increasing complexity of the modern power grid highlights the need for advanced modeling and control techniques for effective control of turbogenerators. This paper presents the design of a continually online trained (COT) artificial neural network (ANN) based controller for a turbogenerator connected to an infinite bus through a transmission line. Two COT ANNs are used for the implementation; one ANN, the neuroidentifier, to identify the complex nonlinear dynamics of the power system and the other ANN, the neurocontroller, to control the turbogenerator. The neurocontroller replaces the conventional automatic voltage regulator (AVR) and turbine governor. Simulation and practical implementation results are presented to show that COT neurocontrollers can control turbogenerators under steady state as well as transient conditions
Keywords :
control system analysis; control system synthesis; learning (artificial intelligence); machine control; machine theory; neurocontrollers; turbines; turbogenerators; artificial neural network; complex nonlinear dynamics identification; continually online trained neurocontroller; control design; control simulation; excitation control; infinite bus; neuroidentifier; power grid; power system; steady state conditions; transient conditions; transmission line; turbine control; turbogenerator; Artificial neural networks; Automatic control; Neurocontrollers; Nonlinear dynamical systems; Power grids; Power system dynamics; Power system simulation; Power system transients; Power transmission lines; Turbogenerators;
Journal_Title :
Energy Conversion, IEEE Transactions on
