Adaptive Control Strategies for Improving Frequency Response Parameters in VSG

The virtual synchronous generator (VSG) strategy addresses the challenges of low inertia and weak damping in a grid, exacerbated by the high penetration of renewable energy sources, by simulating the external characteristics of synchronous generators (SGs). However, the power electronic nature of VSGs can lead to a significant overshoot in the grid frequency response and issues with low-frequency oscillations when the system experiences disturbances. To mitigate these effects, this study proposes an improved self-adaptive control strategy to enhance VSGs’ frequency response characteristics of VSGs during grid connection and under perturbations, analyzed from a parametric perspective. Initially, the VSG active control model is employed to analyze the mechanism by which various parameters affect power frequency regulation during dynamic processes. The optimal initial values for virtual inertia and damping were determined using an enhanced particle swarm optimization algorithm. Subsequently, the impact of the power quality is incorporated into the selection of the fitness function. In addition, an inertia link was integrated into the control strategy, and the optimal value of the inertia coefficient was established through simulation. Finally, the proposed control strategy is compared with the fixed-parameter control strategy and classical adaptive control strategy under various operating conditions. The results indicate that substituting the initial value obtained from the improved algorithm nearly eliminates oscillations during a one-time frequency modulation. When the active power command of the system is increased by 20%, the overshoot of the frequency waveform using the improved strategy is reduced by 25.2% compared with the classical strategy. This suggests that the proposed control strategy facilitates a smoother transition of the system to the next state when subjected to disturbances, thereby enhancing the frequency response of the system.