Artificially intelligent MPPT ‐based photovoltaic integrated smart dynamic voltage restorer

Abstract

Complexity and sensitivity related to modern machinery navigate electrical engineers more apprehensive owing to upraise power quality. In this effort, a series-connected voltage regulating arrangement furnishes apposite aids towards this sizeable interconnected system. Consequently, a dynamic voltage restorer (DVR) is realized to proffer customized power to the end-users. In accordance, the present research illustrates a student psychology-based optimization modulated DVR control mechanism. In the context of real-time realization, artificial neural network (ANN) is also embodied herein to obtain optimized online results. To intensify the potential of the implemented DVR, combined ANN and closed-loop type 2 fuzzy logic (CLT2-FL) modified maximum power point tracking-based partially shaded photovoltaic (PV) aided energy storage unit is also realized in the test network topology. This hybrid CLT2-FL module is adopted herein to trace the optimal power effectively under distinct practical scenarios. In order to assist the PV array, a supercapacitor-based charge controller is also incorporated. Consequently, the results are evaluated to divulge the potency of the propounded mechanism against the oddity seen in the voltage waveform, thereby, exhibiting better voltage regulation and lesser harmonics with effectual optimal power tracking.