The rise of electric vehicles has increased the electrical load in airport service areas. Therefore, by utilizing the development of photovoltaic and energy storage around the airport, combined with the charging characteristics of electric vehicles during parking, a two-layer optimization model for electric vehicles to participate in the price-based demand response and the capacity configuration of photovoltaic and energy storage in service areas is established. The upper model is optimized for the capacity configuration of photovoltaic and energy storage equipment, with the goal of minimizing the configuration cost of photovoltaic and energy storage; the lower model proposes a power optimization management strategy for service areas that considers time-of-use tariff and different charging demands during electric vehicle parking. Simultaneously, a load stochastic model of electric vehicles and a price-based demand response model are established, with the goal of maximizing the benefits of charging, photovoltaic and energy storage , a typical daily optimization control model is established, and the load curve of electric vehicles and the control of energy storage in service areas are optimized. In the simulation, the randomness of photovoltaic output and charging load is considered, and the Monte Carlo method is used to eliminate its impact on the results, and the impact of demand response uncertainty on the optimization results is analyzed. The results show that optimizing the configuration of photovoltaic and energy storage systems considering time-of-use tariff and the charging benefits of electric vehicles can save one-time investment costs, and utilizing the time-of-use electricity pricing policies for charging and the optimization control of photovoltaic and energy storage can achieve better economic benefits. Therefore, reasonable system configuration, site utilization, charging management, and photovoltaic and energy storage control are effective ways to improve energy utilization and economic benefits.