Abstract: China is building a new power system with an increasing proportion of new energy. The electric energy transaction of prosumers with dual attributes of collecting source and charge brings new opportunities and challenges to the local consumption of distributed energy. In this context, to improve the nearby renewable energy consumption, this paper constructs a distributed optimization strategy for energy community prosumers, considering the attractive factor of electricity price. Firstly, the attraction level of prosumers participating in electricity trading within energy communities is quantified, and the electricity price attraction model is constructed to represent the impact of electricity prices within energy communities on electricity trading by prosumers. Secondly, with the transaction price as the consistency variable, the adjacent prosumers reach the price agreement through information interaction, establish the day-ahead optimal scheduling model with the minimum operating cost of all prosumers in the energy community, and use the augmented Lagrange method to solve the problem. Finally, an example is given to verify that the model not only guarantees the privacy of prosumers but also effectively improves the economy of community operation and the consumption level of new energy.