Dynamic Stability Enhancement of Power Systems Using Neural-Network Controlled Static-Compensator

This paper aims at enhancement of dynamic stability of power systems using artificial neural network (ANN) controlled static VAR compensator (SVC). SVC is proven the fact that it improves the dynamic stability of power systems apart from reactive power compensation; it has multiple roles in the operation of power systems. The auxiliary control signals to SVC play a very important role in mitigating the rotor electro-mechanical low frequency oscillations. Artificial neural network based controller is designed using the generator speed deviation, as a modulated signal to SVC, to generate the desired damping, is proposed in this paper. The ANN is trained using conventional controlled data and hence replaces the conventional controller. The ANN controlled SVC is used to improve the dynamic performance of power system by reducing the steady-state error and for its fast settling. The simulations are carried out for multi-machine power system (MMPS) at different operating conditions.