Enhanced GWO Controller Strategy for High Power Quality Improvement in AC Microgrids

Abstract

The power quality issues are increasing every day in AC microgrids (MG) due to improper functionality of controllers. The conventional controllers like filters, regulators, fuzzy, and model predictive controllers (MPCs) are failed to maintain the optimal power flow in two parallel MGs, because these approaches are failed to optimize the fluctuations generated in the system. In general, the MGs contain both smart impedance (SI) and power electronically coupled distributed energy resources (PEC-DER) inverters, where the performance of MG purely depends on the continuous power flow of PEC-DER. Recently, nature-inspired and swarm intelligence-based approaches are resulted in superior performance for optimizing the controlling parameters in the MGs system. Therefore, this article develops the enhanced grey-wolf optimizer (EGWO)-based controller for MGs system, where the proposed EGWO-based controller is used to reduce the integral errors generated in the PEC-DER inverter by selecting the best environmental properties like terminal voltages, generated real power, and dc link voltage. In addition, it is also maintained that the synchronization between PEC-DER and SI converters, which is used to uphold the optimal power flow. Finally, the Simulink results shows that proposed EGWO controller-based PEC-DER resulted in reduced fault setting time (FST) and total harmonic distortion (THD) in MGs as compared to state-of-art controllers from the literature