With the popularity of electric vehicles (EVs), EVs have shown great potential as virtual energy storage resources to participate in grid ancillary services such as peak shaving and frequency regulation. However, due to the spatiotemporal distribution characteristics of EVs and the capacity limitations of charging facilities, how to efficiently coordinate multiple charging stations and their internal EV resources has become a key challenge. This article constructs a two-layer optimization model: the upper substation model is responsible for allocating the total power demand of the power grid to each charging station, considering the electricity price and capacity limitations of the charging stations; The lower-level charging station model optimizes the charging and discharging strategies of EVs within the station under the allocated power demand, while satisfying the constraint of the number of charging stations. To cope with the computational complexity of dual layer optimization, we propose a price coordination based solution scheme. By introducing grid operators to collect cost quotes and capacity boundaries from each charging station, the power allocation problem is solved centrally, and then each charging station independently completes internal scheduling. Through simulation, the effectiveness and feasibility of the proposed model have been verified, providing theoretical support for the large-scale application of virtual energy storage.