Recurrent neuro fuzzi controller power system stabilizer

Abstract

Power system stabilizers (PSS) have been widely used to damp low frequency electromechanical oscillations which occur in power systems due to disturbances. If no adequate damping is available, the oscillation can increase and cause system separation. Power system stabilizers (PSS) are installed in power system generator to help the damping of power system oscillations. There are many approaches to enhance damping while extending the power stability limit. To improve power system stabilizer (PSS) design problem include optimal control ,adaptive and self-tuning control, PID control, robust control, variable structure control and intelligent control. In this paper the power stabilizer is based on Recurrent Neuro-fuzzy Inference System (RNFIS) design controller. In order to test the robustness of the proposed design procedure of the (RNFIS), simulations will be carried out for the three-phase to ground fault and 1- phase fault at the middle of one of the transmission line. After these simulations, we will compare the result between a lead-lag and recurrent neuro-fuzzy controllers to see their difference in disturbances. The optimal solutions will be compared where the expected result will show that the oscillations in time response of the machine speed and the rotor angle is damped more effectively when the recurrent neuro-fuzzy controller and applied to the system.