With the increase in the number and penetration rate of electric vehicles year by year, the uneven layout and insufficient number of existing charging facilities in rural areas have become the main reason restricting the development of new energy vehicles in rural areas. Based on the master-slave game pricing strategy, this paper establishes a charging and storage plant optimisation model for rural power grids with a high percentage of photovoltaic penetration. First of all, based on the master-slave game theory to establish the charging and storage power station optimization model for the high proportion of PV penetration of rural power grid: the upper leader is the charging and storage power station investor, taking into account the construction and operation conditions of the rural distribution network and charging and storage power station, to optimize the decision-making charging and storage power station construction location, the supporting capacity of the storage equipment and the tariff strategy; the lower follower is the electric vehicle owner, according to the tariff strategy formulated in the upper leader model, to optimize the decision-making charging strategy for the electric vehicle. The lower level followers are EV owners, who make optimal decisions on EV charging strategies based on the tariff strategies developed by the upper level leader model. Secondly, the Karush Kuhn Tucker (KKT) condition and the dyadic principle are used to transform the model to obtain an easy-to-solve mixed-integer linear programming model. Finally, the algorithm is validated using a typical IEEE 33-node arithmetic system containing two charging regions. The example analysis shows that the proposed model can coordinate the interests of charging and storage plant investors and EV owners, and obtain a charging and storage plant configuration and operation policy with good economic benefits and strong PV consumption capacity.