Stability analysis using non linear auto regressive moving average controller based power system stabilizer

In this paper, the novel approach to design the power system stabilizer using artificial neural network based Non Linear Auto Regressive Moving Average-L2 (NARMA-L2) controller has been presented. The controller has been used to generate the appropriate supplementary control signal for the excitation system of synchronous generator. The signal generated has been used to damp the low frequency oscillations and improves the performance of power system dynamics. The analysis of Signal Machine Infinite Bus (SMIB) system has been carried out with NARMA-L2 controller and the performance has been compared with genetics search algorithm based Conventional Power System Stabilizer (CPSS). To reflect the effectiveness of NARMA-L2 based PSS, the non-linear simulations have been performed under various disturbances and different operating conditions.