Pricing Adjustment System for Spatial-Temporal Load of Charging Station.

Electric vehicles(EVs) have lately received great attention due to their low emission pollution and recyclability. However, the spatial-temporal charging load has made it challenging to popularize EVs. In the temporal aspect, the extra charging load causes power loss to the power grid, which even results in an overload of the power gird. In the spatial aspect, a long waiting queue during the peak period of charging in some charging stations is detrimental to the development of EVs. Although some encouraging progress has been made, the extra charging load during the peak period of domestic electricity consumption remains an ongoing challenge, and the pricing adjustment system without considering the income of charging station companies is hard to implement and still requires further research. In this paper, we proposed an innovative pricing adjustment system to solve these problems. By studying the charging behaviors and consumption behaviors of drivers, our system will provide each driver with the location, real-time queuing, and customized charging fee of charging stations with the consideration of the income of charging station companies. We use a real data set from Xi'an, e-charge, which contains 241,346 of vehicle charging and driving records for three months with data from 400 charging stations. The experiment shows that our system is effective in decreasing the number of charging vehicles during the peak period of domestic electricity consumption. Also, it reduces the average queue waiting time and the peak waiting time while protecting the profit of charging station operators.