Transient Stability Analysis of SMIB in Power System Using Artificial Neural Network

In this paper, a Neural network based PSS is proposed to control the low-frequency oscillation present in single machine infinite bus system (SMIB). The Neuro-PSS consists of two neural networks Neuro-Identifier, which emulates the characteristics of power flow and Neuro-Controller, which produce supplementary excitation signal. Proposed PSS helps in improving stability-constrained operating limits in large generators. The action of proposed PSS is to provide damping to the oscillations of the synchronous machine rotor through generator excitation. This damping is provided by an electric torque applied to the rotor that is in phase with speed variation, which is feedback input signal to proposed PSS. The control objective is Quadratic function applied by neuro-controller over outputs produced by system plant and neuro- identifier.