Optimizing DC Microgrid: Fuzzy PI Controller with Metaheuristic Energy Storage Management

Abstract

Abstract One of the main issues with power systems that has a direct impact on voltage stability is the balance between power generation and load demand. On the other hand, due to the unpredictable nature of output power generation and the low inertia of these sources in comparison to other conventional sources, raising the penetration ratio of solar and wind power in the Microgrid (MG) may result in a lack of frequency control. The frequency stability performance can also be greatly improved by adjusting the gain of the inertia and drop control loops. However, it seems difficult to modify the aforementioned control coefficients with ordinary PI controllers in order to expect the greatest performance in all circumstances due to variations in wind speed, solar radiation, and load. Therefore, this work, by modelling load fluctuations and generation variations with the cooperation of battery and supercapacitor energy storage in the MG, suggests a control scheme based on a fuzzy gain scheduling PI (FGS-PI) model and improved grey wolf optimization (GWO) algorithm for faster performance and more robustness. Further, the effectiveness of the proposed technique is confirmed by simulation results in MATLAB/Simulink 2021b.