Comprehensive Optimal Scheduling Strategy of Multi-Element Charging Station for Bounded Rational Users

While providing charging service for electric vehicles, charging stations are also aggregation centers which supply adjustment capabilities to the power grid. It is necessary for charging stations to take care of all parties' interests with respect to users' independent choice. This article focuses on multi-element charging stations which contain conventional load, energy storage and distributed renewable energy generation besides charging piles. Firstly, charging price mechanism that improves participation motivation of users in providing charging flexibility were designed. Next, rational model based on expected utility and bounded rational model based on prospect theory were established respectively. Model predictive control(MPC) has been selected to handle uncertainties caused by users' behavior and output of distributed renewable energy generation. Both operating economy and adjustment flexibility of charging stations have been taken into account in proposed comprehensive scheduling strategy. Based on the setting of dummy variables, double-layer optimization has been converted into single-layer optimization which can reduce the calculation time significantly, making the strategy suitable for online application. Advantage of the bounded rational model in predicting users' behavior was verified by experiments towards real people. The selection of time scale for MPC was discussed through simulation experiments in different scenarios. In the simulation experiment, the proposed scheduling model integrating social-physical methods has shown good performance in power grid requirement following and economic optimization.