Improving the Voltage Response of Grid Connected Three Inter-Connected Microgrids Using Artificial Intelligence Based Controllers

Abstract

Integrating microgrids (MGs) within the power has increased significantly to increase the reliability and improve the efficiency of the main grid. M Gs should be fitted with efficient controllers to provide high power quality and keep system stability when subjected to various disturbances. This paper investigates the dynamic performance enhancement of three interconnected M Gs connected to the utility grid. The most common controllers in M G applications are conventional linear controllers like PI and droop controllers that may provide undesired response under disturbances, which the micro-grids are subjected. Hence, a non-linear adaptive controller, fuzzy PI controller-based model reference adaptive control (FPI-MRAC), that can adapt to the various operating conditions is suggested in this paper for regulating the system voltage, and its performance is evaluated and compared with the traditional PI controller. The system under study is subjected to a variety of scenarios to assess the efficacy of the proposed controller, FPI-MRAC, during severe conditions. Simulation results demonstrate that FPI-MRAC is more effective than PI controller in keeping the system voltage at the desired value for various operating scenarios. Also, an advanced optimization technique, coronavirus herd immunity optimizer (CHID), is utilized to tune the proposed controllers.