An Adaptive Grid-Forming Control Strategy Based on Capacitor Energy State Estimation

Conventional grid-forming (GFM) inverter control strategies often rely on fixed parameters and overlook the dynamic variation in energy stored in the DC link capacitor. This limitation can degrade transient performance and stability, particularly under power fluctuations and grid disturbances in renewable energy systems. To address this issue, this paper proposes an adaptive GFM control method that integrates real-time estimation of the DC link capacitor energy into the control loop. A Kalman filter-based observer is designed to estimate the capacitor energy state accurately and robustly using only local voltage and current measurements. The estimated energy deviation is then used to dynamically adjust key control parameters, including the virtual inertia and droop coefficients in the virtual synchronous generator (VSG) framework. These adaptive adjustments enhance the inverter’s damping and inertial behavior according to the internal energy buffer, improving performance under variable operating conditions. Simulation results in MATLAB/Simulink R2023b demonstrate that the proposed method significantly reduces power and voltage overshoots, shortens settling time, and improves DC link voltage regulation compared to conventional fixed-parameter control.