Adaptive Control Strategy for VSG Inertia and Damping in the New Power System

When numerous energy storage devices are connected to the grid via virtual synchronous generators (VSGs), inappropriate selection of control parameters within the conventional fixed inertia and damping control strategy can result in extended regulation times or excessive overshooting. This impedes the full exploitation of the flexible VSG control advantage. Consequently, this paper proposes an adaptive control strategy for the energy storage system, based on the particle swarm algorithm (PSO), aimed at establishing the VSG of the energy storage system. Initially, the strategy incorporates the state of charge (SOC) constraints of the batteries to optimize the inertia and damping parameters. The PSO's objective function is formulated to minimize the cumulative error in the frequency of the energy storage VSG system and the total harmonic distortion rate of the voltage. This enhances convergence speed and effectively avoids the issue of local parameter solutions. Building on this, an improved inertia damping adaptive control strategy is designed to significantly enhance the dynamic performance of the VSG. The effectiveness of the proposed strategy is verified through a simulation model constructed using Matlab/Simulink.