Under the “dual-carbon” goals

the rapid development of new energy has led to a scarcity of rotational inertia

making inertia support from wind power systems increasingly important. However

providing inertia support by adjusting active power output reduces the economic efficiency of wind farms. To address this issue

a dynamic pricing and optimal allocation method for wind farm virtual inertia in the ancillary service market is proposed based on a Stackelberg game framework. First

the inertia support capability of wind farms is assessed based on rotor speed and power change constraints of wind turbines. The wind farm capacity is also evaluated

and a differentiated reward-penalty mechanism is established accordingly. Second

a Stackelberg leader-follower game model is constructed

where the power market operator acts as the leader and the wind farm cluster as followers. The market operator determines dynamic pricing and reward-penalty mechanisms to incentivize wind farms to participate in system inertia support. Finally

the proposed model and method are solved in MATLAB using the Gurobi commercial solver

and case studies verify their feasibility and effectiveness.