Charging demand for electric vehicle based on stochastic analysis of trip chain

With its popularisation, electric vehicle (EV) has been part of the important load of smart grid. The analysis on charging demands of EVs is the basis of the study of influences on power grid and charging infrastructures planning. Charging demand calculation is based on the precise analysis on the driving law of users. This study proposes a method based on the stochastic simulation of trip chain to solve the existing problem. First, the concept and characteristic variables (trip start time, driving time, parking duration, driving distance and trip purpose) of trip chain are introduced. Second, the probability distribution models of these variables are established considering their correlative relationships. Third, using Monte Carlo method, the complete trip chains are simulated, and then the spatial–temporal distributions of charging demands are calculated. Finally, based on the National household trip survey data, and according to the proposed method, charging demands in different areas are studied. The results show that the proposed method can accurately simulate the driving law of users and reflect spatial–temporal distribution characteristics of charging demands, and different charging scenarios will lead to different forms of charging demand distribution, which will exert different impacts on power system.