Evaluating the minimum inertia of power systems with consideration for wind power in frequency regulation

• Proposes an accurate aggregation model applicable to multi-control-mode wind farms. Addressing the prevalent issue in existing research of using single-machine equivalent models that overlook the heterogeneity among wind turbines, this study innovatively adopts a parameter-weighted averaging method to construct a multi-machine aggregation model. This model accurately reflects the differences in various frequency control strategies, providing a more reliable foundation for system-level frequency and inertia studies. • Constructs a minimum inertia assessment framework integrating dual frequency security constraints. Breaking through the limitations of traditional single-constraint assessments, this research is the first to incorporate both the system Rate of Change of Frequency (RoCoF) and the maximum frequency deviation as simultaneous security constraints in the context of wind power participation. It establishes a more comprehensive minimum inertia assessment method, clarifies the dominant role of different constraints under various disturbance scenarios, and provides refined guidance for secure system operation. • Quantitatively reveals the regulatory effect of wind power control parameters on system inertia requirements. Beyond proposing an assessment methodology, this study further employs parametric sensitivity analysis to quantitatively elucidate how key control parameters—such as the virtual inertia constant and the primary frequency regulation (PFR) coefficient of wind turbines—affect the overall system’s minimum inertia requirement. This provides a theoretical basis and regulation pathways for leveraging the flexible frequency regulation capability of wind power to reduce reliance on traditional synchronous inertia. 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.