Research on the improvement of dynamic and steady-state performance of grid-connected inverters based on fuzzy adaptive control under weak grid conditions

With the continuous increase in the penetration of renewable energy generation, the characteristics of weak grids, such as high grid impedance and low short-circuit ratios (SCR), have become more prominent. Although the performance of grid-connected inverters can be adaptively adjusted according to the SCR to ensure stable operation under a wide range of SCR variations, this significantly reduces their responsiveness and makes it challenging to meet grid connection requirements. To address this issue, this paper proposes a control strategy based on a fuzzy adaptive PI controller. First, a mathematical model of the grid-connected inverter is established, and the D-segmentation method is employed to analyze the stability region of conventional PI control parameters, particularly addressing the balance between stability in weak grids and responsiveness in strong grids. Based on this analysis, a fuzzy adaptive PI controller is designed that incorporates fluctuations in the SCR and variations in current control errors, enabling adaptive adjustment of control parameters according to the dynamic and steady-state characteristics of the grid. Finally, the effectiveness of this strategy is validated through a hardware-in-the-loop simulation platform. The results demonstrate that the proposed method significantly enhances the steady-state performance of the grid-connected inverter in weak grids and the dynamic performance in strong grids, effectively balancing the dynamic and steady-state characteristics of the inverter.