Introduction  The widespread adoption of electric vehicles (EVs) enhances environmental sustainability during travel, yet it simultaneously elevates strain on the mains supply. To assess the impact of EV charging on the power grid, a specialized charging load calculation method is developed for large EV cluster on the basis of the Monte Carlo method.

  Method  In this approach, EVs were categorized into six groups based on their usage: private EVs, electric buses, electric taxis, online ride-hailing EVs, official EVs, and logistics EVs. Typical battery performance parameters for each group were identified, and probability models were established to characterize the variability in their travel and charging patterns. By integrating group scale forecasts, daily charging schedules for each group were simulated through random sampling. Subsequently, the daily charging load for each group was calculated, culminating in the total charging load for the EV cluster through an aggregation method.

  Result  The EV cluster in a southern province in 2030 was taken as the simulation case.

  Conclusion  The case analysis reveals that the proposed approach can provide the daily charging load of various EV groups and the entire EV cluster. Furthermore, among all types of EVs, electric buses have the highest peak charging load at 4 639.5 MW, followed by that of private EVs (not higher than 70% of the electric buses' peak load), and electric taxis have the lowest peak charging load. The charging peak of the entire EV cluster occurs between 19:00 and 23:00 at night, and the peak load can reach 10.0927 GW.