An intelligence technique-based control model for power system stabiliser

Abstract

In the power system, voltage instability is one of the important issues and it may cause voltage sag, voltage swell, change in load and generation of harmonics. To tackle all these problems, the transmission power system makes use of an intelligent control model to improve the stability of power system. In this paper, a new adaptive neuro fuzzy inference system (ANFIS) based power system stabiliser (PSS) for the enhancement of voltage stability in power systems is proposed. A hybrid learning algorithm, which combines the least squares method and the back propagation algorithm, is used to train the ANFIS. The performance of the power system by using fuzzy based PSS is about 60.1% when compared to that of the conventional PSS. To evaluate the effectiveness of the proposed technique the performance of the proposed technique was compared with the results obtained by using fuzzy PSS model and its performance was analysed. Simulation results described in the paper demonstrate that the adaptive neuro-fuzzy based PSS can give 33.43% of improvement in voltage stability when compared to that of fuzzy based PSS over a wide range of operating conditions.