A Practical Continually Online Trained Artificial Neural Network Controller for a Turbogenerator

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

This document has been relocated to http://scholarsmine.mst.edu/ele_comeng_facwork/1393

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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.