Massive electric vehicle (EV) integration has been an inevitable trend for future power distribution networks. However, the spatial-temporal randomness of EV charging behavior may cause insufficiency of power supply capability. This paper simulates the charging loads with massive EV integration, proposes a probabilistic evaluation index to evaluate the probability of insufficient power supply capability, and gives improvement measures for power distribution networks without hardware upgrading. First, the spatial-temporal distribution of EV charging loads is simulated via Monte Carlo method, which particularly divides EVs into three categories, private cars, buses, and taxis. Then, aggregated with conventional loads, total supply capacity of a power distribution network can be calculated on different time periods. Second, for the uncertainty of EV charging loads both in time and space, a probabilistic evaluation index is addressed to evaluate the probability of power supply capability insufficiency. After that, several improvement measures of the charging strategy are given to relieve the insufficiency of power supply capability. Finally, taking the simplified distribution network of a typical power supply mode in China’s Fujian province as an example, three scenarios with different vehicle quantities and parameters are designed, and the effectiveness of the evaluation index and improvement measures proposed are identified. The results can provide evidences for constraining EV charging behaviors with massive integration.
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