Abstract
This paper proposes a method to predict the charging load demand of electric vehicles considering the spatial and temporal distribution characteristics of users’ travel. Based on the central limit theorem and travel chain theory, the temporal distribution of the charging load of different functional sites is simulated by the Monte Carlo method and calculated by combining NHTS2017 data to find the total daily charging load of electric private vehicles. The results show that in the case of disorderly charging, the charging loads of different areas have more obvious temporal characteristics, and the charging service can be optimized according to this charging load characteristic.
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