Adaptive Virtual Inertia-Damping System Based on Model Predictive Control for Low-Inertia Microgrids

Abstract

In this paper, an adaptive virtual inertia-damping system based on model predictive control (MPC) is proposed to enhance the frequency dynamic performance of islanded microgrids (MGs) considering a high penetration level of renewable energy sources (RESs). Recently, a large amount of RESs is replacing traditional generating units, causing an undesirable effect on the MG frequency stability and system inertia, and thus weakening the MG. Therefore, the proposed control system handles this challenge to enhance the robust performance and stability of the MG with high RESs penetration during contingencies. The proposed online MPC strategy estimates the gains of the virtual inertia control (VIC) system (i.e., inertia and damping coefficients) in high RESs MG. The performance of the proposed adaptive VIC system is compared with the conventional VIC system (i.e., constant values of inertia and damping coefficients) using MATLAB/Simulink under numerous disturbances and system uncertainties. Moreover, the effectiveness of the proposed adaptive VIC system based on the online MPC strategy is verified by comparing its performance with the adaptive VIC system based on fuzzy logic control, which is designed to estimate only the inertial gain. The results highlight that the frequency stability is upgraded, and the adaptive virtual inertia system based on MPC successfully supports low-inertia islanded MGs with RESs and load fluctuations.

Keywords

• Adaptive virtual inertia system
• model predictive control (MPC)
• microgrid (MG)
• frequency stability
• high penetration of renewable energy sources (RESs)