With the widespread adoption of electric vehicles, the distinct features of their charging and switching technologies have a significant impact on the grid load. This paper focuses on the operation mechanism of charging and switching technologies, and after analyzing the temporal and spatial patterns of load variation in EV charging and switching modes, a Monte Carlo simulation method based on the momentary charging likelihood is adopted to establish a charging load prediction model to investigate the temporal–spatial distribution patterns of charging demand under different day categories, vehicle types, charging and switching modes, and charging areas. Example analysis shows that the model can accurately simulate the user’s travel pattern, capturing the temporal and spatial variation in charging and battery-swapping demand for electric vehicles across different driving and parking states. The charging load distribution of various vehicle categories varies greatly, while the charging loads of private cars and cabs account for a higher proportion, with higher regulation potential; compared with double holidays, the charging demand fluctuates more on weekdays, with a higher total demand; the charging demand also has obvious seasonal characteristics, with a greater demand in winter and summer, and the peak appears in an earlier time. The study offers a reference for the planning and development of electric vehicle charging facilities as well as for assessing their impact on the power grid.
