To address the challenge of dynamic pricing mechanisms in the efficient integration of electric vehicles (EVs) in virtual power plants (VPPs), a pricing method for EV charging stations based on carbon flow tracking is proposed. The method is designed to utilize node carbon potential to drive the formulation of differentiated electricity prices, thereby guiding the charging plans of EV users and achieving the economic and low-carbon synergistic optimization of grid operations. Specifically, the process is initiated with the quantification of EV traffic and queueing time costs, followed by the optimization of road network planning through an improved Dijkstra algorithm. Then, based on the optimal power flow results and carbon flow tracking theory, the node carbon potential at the charging station access points is accurately calculated. Subsequently, an innovative electricity-carbon coupled dynamic pricing mechanism is constructed based on the carbon potential calculation results, and a hierarchical iterative algorithm is designed to enable a closed-loop feedback optimization of electricity price signals, carbon potential distribution, and user response. Simulation results demonstrate that the proposed method can reduce carbon emissions by 16.7% at the same level of revenue, and increase system revenue by 30.4% at the same level of carbon emissions, thereby its effectiveness in guiding low-carbon behavior and enhancing the economic-environmental synergy of the grid is confirmed. A technically efficient and operable path for the VPP integration of EV resources and the realization of low-carbon economic operation in the grid is provided by this method.