Optimal Performance of PI Controller for AC Microgrid Based on Metaheuristic Optimization Algorithms

Microgrids are small power systems with one or most distributed generating units (DGs). Frequency and voltage control are crucial for grid-independent operating. It is a complex problem and essential to provide reliability and stability. Thus, the operating control issue is one main problem for the microgrid that must be addressed during operation, which calls for developing an optimal control method. Among these techniques, droop control is a common method due to the lack of critical communication links between parallel inverters to regulate the distributed generating units inside a microgrid, which is used for optimizing power sharing among DGs sources. Unfortunately, this strategy isn't accurate in keeping the system frequency and voltage near their nominal values. As a result, the parameter values must be carefully selected utilizing the optimization techniques. This work aims to improve the droop controller based on optimized PI controller parameters to control the frequency and voltage of microgrids under various conditions by using three metaheuristic optimization algorithms, Slime Mould Algorithm (SMA), Sine Cosine Algorithm (SCA), and Sparrow Search Algorithm (SSA), and compare with the conventional method. Simulation findings using Simulink in MATLAB demonstrate the performance of the suggested microgrid stability techniques. Finally, to investigate the effectiveness of the suggested control strategies, the study's results are compared with those of the conventional control method. The simulation results demonstrated the significant superiority of the proposed methods, including the SMA, in terms of performance analysis standards, power deviations, frequency stability, voltage response, load-sharing balance, overshoot reduction, and improvement in settling time and rise time.