Application of safety and stability optimization algorithms for charging connection devices in high-power charging systems

Abstract In response to the safety and stability issues of current electric vehicle charging connection devices, this study proposes a charging system planning for electric vehicles with different capacity charging piles based on the user behavior characteristics of electric vehicles and Monte Carlo methods. It is found that the predicted results under the set management strategy are most consistent with the trend of actual load changes. Moreover, in the prediction of weekly load, the research strategy has better performance than traditional unmanaged strategies. Under the research scheme, the average charging speed of charging piles with capacity of A and B in the peak period was 41.4 min/ and 18.8 min/, respectively, which increased by 29.3% and 11.7% respectively compared with 58.6 min/ and 21.3 min/ in the normal period. The total economic cost of the research plan was 4.871 million yuan, which was 67.0 million yuan and 3.833 million yuan lower than the control methods 1 and 2, respectively. The total number of charging stations of types a and b that need to be purchased for the research method decreased by 18.47% and 63.24% compared to the comparative method 3. The results indicate that the research method significantly improves the utilization rate of charging stations in the electric vehicle charging system. This study has important application value in the intelligent management of electric vehicle charging systems.