With the widespread popularity of distributed photovoltaics, charging piles, 5G base stations and other new infrastructure, residential stations are prone to problems such as large peak-valley difference and reverse power transmission. In order to solve the above problems, by means of fully mining the energy storage potential of a variety of elastic resources, an optimal dispatching strategy is proposed, which takes into account the coordination of multiple elastic resources. Firstly, the mathematical model of each unit in the residential station area is established, and the energy consumption law and energy storage potential of the three elastic resources of electric vehicle, 5G base station and temperature control load are analyzed. Secondly, taking the power of the three elastic resources as the decision-making variable, considering the constraints such as power balance and equipment characteristics, an optimal scheduling model with peak shaving and valley filling and new energy consumption as the goals is established, and the MOMVO algorithm is used to solve the optimal scheduling scheme. Finally, considering the changes of electric vehicle penetration rate in the short-term, medium-term and long-term time scales, the proposed optimal scheduling strategy is simulated and verified by example. The results show that compared with the original station, after optimizing the scheduling of various elastic resources, the peak-valley difference of power load in the platform area decreases by 58.8% on average, eliminating the phenomenon of voltage exceeding the limit and photovoltaic power generation reverse transmission. Therefore, the proposed method can fully mine the energy storage potential of different elastic resources, effectively reduce the overload operation of distribution and enhance the absorption capacity of new energy, which is of great significance for improving the safety reliability and energy utilization efficiency of residential areas.