A Grey Wolf-Driven Refinement of Fuzzy-Based Controller for Enhanced DC Microgrid Operation

Distributed energy sources play a pivotal role in microgrids, addressing the stochastic nature of load demand. To maintain power stability, reduce computational time, and have minimal power fluctuations in a DC microgrid, a Grey Wolf Optimization (GWO) based fuzzy logic controller has been designed for a fuel cell, battery, and supercapacitor-based DC microgrid connected to a DC load. For this purpose, a fuzzy inference system (FIS) has been implemented for effective control signal generation. The main goal of this design is to eliminate the hit-and-trial method for selecting the spread of membership functions of the FIS through GWO while maintaining a stable power supply to the load and keeping the energy storage system within safe limits. The optimized controller's membership functions have been extensively evaluated through simulations carried out in MATLAB/Simulink (2020a). Lastly, a detailed comparative illustration of optimized and unoptimized fuzzy logic controllers for fuel cell, battery, and supercapacitor has been presented to demonstrate the superior performance of the GWO-fuzzy logic controller.