Virtual Inertia Predictive Control for Frequency Regulation in a Low-Inertia Autonomous Microgrid

High penetration level of inverter-based energy sources (IES) in power networks can substantially reduce the overall system inertia. Owing to the little inertia support from these sources, autonomous microgrid (MG) systems populated with IES have very low inertia, thus, making it susceptible to incessant frequency instabilities. Therefore, this study aims to improve the load frequency control (LFC) of a multi-source, two-area MG using the virtual inertia control (VIC) concept. An optimized Model Predictive Controller (MPC) is used as the supplementary controller due its efficient constraints handling. Among the key contributions of the study is constraining the Rate of the Change of Frequency (RoCoF). To assess the performance of the LFC, the MG was simulated in MATLAB/Simulink, with both step and randomly fluctuating disturbances. It is observed that the proposed scheme has better response vis-à-vis not only smaller frequency nadir, shorter settling time, but also lower RoCoF compared to those obtained using PID, FOPID and unconstrained MPC control schemes.