The large-scale application of energy storage is an important method to achieve the renewable energy consumption targets

and its promotion relies on capacity subsidy incentives. However

the capacity subsidy solely depends on capital costs

and the income is fixed

which cannot arouse the project’s initiative. Therefore

we propose a method for setting capacity subsidy based on Stackelberg game

which compromises the interests of both sides. The energy storage plant

as a leader of the game

formulates its capacity strategy according to capacity subsidy signals. The grid company

as a follower

adjusts capacity subsidy based on storage plant’s decision. The Stackelberg game is modeled as a bi-level optimization problem where storage plant seeks to maximize profit and grid company seek to minimize overall cost. The problem can be transformed to a mixed integer programming problem through the Karush-Kuhn-Tucker（KKT） optimal condition

which can be directly solved by commercial software. Computational examples are presented to reveal the rationality and effectiveness of the proposed model and method. The results show that the proposed method can effectively simulate the decision-making interplay between the power grid and the power station

and guarantee the rationality of the capacity subsidy. Compared with the conventional method

the proposed method can achieve energy consumption targets while reducing the subsidy cost of the grid.