Research Projects

A microgrid is a smaller-scale utility grid that can function in either grid-connected or islanded mode. Hybrid microgrid systems combine renewable energy sources like wind and solar power with traditional power sources like diesel generators and energy storage devices, providing fuel savings, increased system capacity, less pollution, and improved system reliability. However, when the microgrid system is subjected to load disruptions and uncertainties in renewable energy sources (RES), major difficulties such as frequency variations may emerge. To control these variations, a well-designed Low-Frequency Control (LFC) is needed. Various control methods have been devised to improve LFC performance, such as PID, Fuzzy PID, and MPC controllers. To improve microgrid frequency control, a robust controller is needed along with the turbine and diesel generator governor model. However, the challenge lies in tuning the suggested controller in line with the system. This proposal presents a design of a robust LFC controller for a two-area and four-area interconnected microgrid (ICMG) system, achieved by optimal tuning of PID, Fuzzy PID, and FOPID controller gains using an efficient Hybrid Constriction Coefficient Particle Swarm Optimization based Butterfly Optimization Algorithm (HCCPSOBOA) and Autonomous Model Predictive Controller (AMPC). The robustness of the proposed controllers is investigated against various load perturbations, system parameters modification, and uncertainties of renewable energy sources. Through time domain simulations in the MATLAB/SIMULINK environment and the implementation of the real-time hardware in loop (HIL) model, the efficiency of the proposed controller is demonstrated and validated.