An EV Charging Demand Model for the Distribution System Using Traffic Property

Abstract

This paper proposes a mathematical model for the spatial-temporal charging demand for electric vehicle (EV). The determination of spatial-temporal charging demand is a key step for the planning of distribution systems with a scalable application of EV. The spatial-temporal allocation of EV is conventionally obtained through a simulation procedure using traffic topology data, which is not suitable for the regions lacking such information. This model converts the problem of travel distance to travel duration so that the requirement of network geographic information can be avoided. Static EV parameters, EV spatial-temporal moving parameters and system charging model parameters are treated as the deterministic factors for the charging demand allocation. A stochastic travel route simulation procedure, which relies purely on statistical data of traffic flow, is also developed to obtain the EV moving parameters by adopting the traffic property information. The designed procedure derives travel time parameters from the vehicle dynamic-location-property (DLP) model and the travel time probability distribution. The DLP model is established using the traffic property matrix and the regional origin-destination matrix. A simple case is presented to illustrate the result of stochastic travel route simulation. Then, a modified eastern China system is used as an example to analyze the EV charging demand under multiple scenarios. The feasibility and versatility of the proposed model in the large complex system are verified by the test results.