Two Separate Continually Online-Trained Neurocontrollers for Excitation and Turbine Control of a Turbogenerator

Ganesh K. Venayagamoorthy, Missouri University of Science and Technology
Ronald G. Harley

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This paper presents the design of two separate continually online trained (COT) neurocontrollers 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 artificial neural network is used to identify the complex nonlinear dynamics of the power system. Results are presented to show that the two COT neurocontrollers 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