Breakthroughs in electric vehicle (EV) battery technology and the continuous enhancement of onboard computing power enable EVs to possess dual capabilities of mobile energy storage and edge computing. This paper considers the dual attributes of EVs as mobile energy storage and edge computing resources, and introduces the concept of “charging and computing station (CCS)”. Based on the analytical target cascading (ATC) method, a hierarchical operation optimization model for the distribution network and charging stations is proposed. First, an energy consumption model for EV charging/discharging and edge computing within a CCS is established. Then, aiming to minimize the operating costs of a CCS and the distribution network, a power flow optimization model for the distribution network incorporating multiple CCSs is constructed to achieve optimal decision-making for EV charging/discharging power, edge server task offloading, and computing resource allocation. Second, a hierarchical operation optimization calculation method for the distribution network and CCS based on the ATC algorithm is designed, enabling CCSs to perform autonomous energy and computing management while protecting the local data privacy of each CCS. Finally, simulation results demonstrate that the proposed optimization model can effectively enhance the computing revenue of a CCS by aggregating EV computing resources to assist edge servers in completing more computational tasks. Additionally, by optimizing EV charging/discharging and edge server power consumption, the overall system operating cost is further reduced.