Data-Based Intelligent Frequency Control of VSG via Adaptive Virtual Inertia Emulation

This article proposes an optimal virtual inertia control for the virtual synchronous generator (VSG) controlled inverter-based microgrid (MG) with the integration and application of large-scale renewable energy resources. Using a data-based optimization technique, the optimal virtual inertia is designed to adjust the emulated inertia parameter based on the frequency change in the MGs, while margin and the respective energy requirements are reserved at the same time. The proposed controller is combined into an up-to-date ac MG control and verified based on MATLAB/Simulink. The simulation results illustrate that the proposed control method improves the frequency drop and the rate of change of the frequency compared to the conventional droop control, VSG control, adaptive virtual inertia control proposed recently, while more dc-side energy is reserved.