Zhe Zhang

Under slow power-flow dynamics, a voltage instability phenomenon induced by low-voltage ride-through (LVRT) control switching rather than by saddle-node bifurcation (SNB) has been observed at a renewable energy station (RES) in China. The phenomenon leads to a large-scale disconnection of RESs. However, the understanding of the patterns and mechanisms of this LVRT-control-switching-induced (LCSI) voltage instability is still insufficient, resulting in potential operating risks for grid-connected RESs. This paper investigates the potential LCSI voltage instability patterns and develops a graphical discrimination method. First, three scenarios involving the triggering of LVRT control switching are identified. Second, a mathematical model of the grid-connected RES system is established. Then, based on the accessibility of equilibrium points, the LCSI voltage instability pattern and the corresponding bifurcation properties in each scenario are revealed. Furthermore, a graphical discrimination method that accounts for both SNB and LCSI voltage instability is proposed. Finally, the existence of three LCSI voltage instability patterns is verified, and the effectiveness and robustness of the proposed graphical discrimination method are validated.

The voltage instability induced by low‐voltage ride‐through (LVRT) control switching may occur in renewable energy stations (RESs) after faults, affecting the safe and stable operation of the power system. However, the post‐fault voltage patterns and practical discrimination methods associated with LVRT‐control‐switching‐induced (LCSI) voltage instability remain insufficiently understood, leading to potential operational risks for grid‐connected RESs. This paper investigates the potential post‐fault LCSI voltage patterns and proposes a graphical discrimination method. First, based on the physical model of LVRT control, five potential post‐fault LVRT control switching scenarios of the RES are identified. Second, an analysis method for the LVRT process based on equal voltage curves (EVCs) is proposed. The mechanisms of the LVRT control switching and voltage stability in each scenario are investigated. Two voltage recovery patterns and three voltage instability patterns are identified, including two additional patterns not reported in the previous studies. Then, a graphical method for distinguishing the LCSI voltage patterns is proposed, and the corresponding identification process is provided. Finally, EMT simulations verify the occurrence of the two additional voltage patterns. The computational efficiency, effectiveness, and robustness of the proposed method are further validated using the modified IEEE 39‐bus system and a simplified provincial‐level power system.