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.
G. K. Venayagamoorthy and R. G. Harley, "A Practical Continually Online Trained Artificial Neural Network Controller for a Turbogenerator," Proceedings of the IEEE International Symposium on Industrial Electronics, 1998. ISIE '98, Institute of Electrical and Electronics Engineers (IEEE), Jan 1998.
The definitive version is available at https://doi.org/10.1109/ISIE.1998.711552
IEEE International Symposium on Industrial Electronics, 1998. ISIE '98
Electrical and Computer Engineering
Keywords and Phrases
Artificial Neural Network Controller; Automatic Voltage Regulator; Continual Online Training; Control Simulation; Control System Analysis; Disturbance Ride-Through; Identifier/Controller; Learning (Artificial Intelligence); Machine Control; Machine Theory; Neurocontrollers; Stability; Steady-State Stability Limits; Three-Phase Faults; Turbine Governor; Turbogenerator; Turbogenerators
Article - Conference proceedings
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