Online Adaptive Neurofuzzy Based SVC Control Strategy for Damping Low Frequency Oscillations in Multi-Machine Power System

An online auxiliary control was designed for Static Var Compensator (SVC) to improve the poorly damped oscillations in multi-machine power system subjected to small and large disturbances. This paper presents auxiliary control based on Adaptive NeuroFuzzy (ANF) control using triangular membership function. Such a model free based control does not require any prior information about the system and is robust to system changes quickly. To minimize the cost function and to tune the parameters of the antecedent and consequent part of the proposed control, a Gradient Descent (GD) learning algorithm is used. The time domain simulation results were carried out for two machine test system for four different cases. In order to exploit the performance and robustness of ANF control, the results were compared with conventional PI and no control. Simulation results and performance indices reveal that the proposed control outperforms during various fault conditions and hence improves the transient stability to a great extend.

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