Since charging stations are aggregation centers which provide charging service for electric vehicles and adjustment flexibility for power grid,it is necessary for charging stations to give consideration to interests of all partners with respect to users' independent choices. Focused on multi-element charging stations (MCS) which contain conventional load,energy storage,distributed renewable energy generation (DRG),charging price mechanism is firstly designed in this paper to improve participation motivation of users in providing charging flexibility. Then,both rational model based on expected utility (EUT) theory and bounded rational model based on prospect theory (PT) are established to describe users' selections. Model predictive control (MPC) is adopted to deal with uncertainties. Both operating economy and adjustment flexibility of charging stations have been taken into account in the comprehensive scheduling strategy. Finally,double-layer optimization is converted into single-layer through dummy variables to reduce calculation time and make the strategy suitable for online application. Advantages of the bounded rational model in predicting users' behavior are verified by experiments towards real people. In the simulation experiment,the proposed scheduling strategy integrating social-physical methods shows good performance in following requirements of power grid and reducing operating costs.