Zhenjian Xie, YI TANG
In the context of high wind power penetration, low-inertia power systems face deteriorated frequency stability, making it critical to assess minimum inertia while accounting for wind turbines’ multi-mode frequency regulation (FR). To address this, this study proposes a parameter-weighted average multi-machine aggregation model—weighting key FR parameters by wind turbines’ output proportion—to resolve the accuracy deficit of traditional single-machine equivalent models; further, it establishes a dual-constraint (frequency rate of change, RoCoF; maximum frequency deviation, Δ f max ) minimum inertia evaluation method, quantifying how wind power FR reduces inertia demand. Validated through Matlab/Simulink simulations and comparisons with PSD-BPA results of an actual regional grid, the proposed model shows better consistency with real-system frequency responses than conventional approaches, providing practical guidance for frequency security in wind-integrated power systems.