Dynamic Response Assessment of Optimal Shunt Active Power Filter Using Novel Controllers

Abstract

This study presents a comprehensive dynamic response evaluation of shunt active power filters (SAPFs), using proportional-integral (PI), tilt derivative (TD)&Tilt-integral (TI) controllers and optimum TD&TI controllers. The study uses a unique metaheuristic algorithm called Dynamic Opposite Learning-based Enhanced Mountain Gazelle Optimisation to optimize controller settings. The study also considers various operating conditions, such as harmonic distortion, reactive power compensation, and sudden load removal, to evaluate the performance of these controllers. The proposed methodology minimizes Integral Time Square Error (ITSE) as cost functions. The simulation results show an enhanced settling time (Ts) with ITSE as the cost function. The results show that the optimum TD and TI controllers perform better than standard PI, TD&TI controllers in terms of dynamic responsiveness and power quality improvement. These findings can be used to design high-performance SAPF systems suitable for commercial and industrial settings.