Research on optimization model of electric vehicle charging pile planning based on data-driven

Shuai Han; Ning Wu; Jianbin Lu; Leping Sun; Xiaoxuan Guo; Shiya Ruan

doi:10.1117/12.2684957

19 October 2023 Research on optimization model of electric vehicle charging pile planning based on data-driven

Shuai Han, Ning Wu, Jianbin Lu, Leping Sun, Xiaoxuan Guo, Shiya Ruan

Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 1270960 (2023) https://doi.org/10.1117/12.2684957
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China

Abstract

The rapid growth in the number of electric vehicles has revealed an imbalance between the urban charging network layout and charging demand. This paper analyzes the influencing factors and principles of charging station planning. Taking full account of users’ travel rules, charging characteristics, charging pile utilization rate and other factors, a planning optimization model with the lowest sum of users’ time cost and charging station investment operation and maintenance cost is constructed, which promotes the scientific and rational distribution of charging facilities, improves the utilization rate of charging infrastructure, and provides a scientific basis for subsequent rational pile construction and operation.

Citation Download Citation

Shuai Han, Ning Wu, Jianbin Lu, Leping Sun, Xiaoxuan Guo, and Shiya Ruan "Research on optimization model of electric vehicle charging pile planning based on data-driven", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 1270960 (19 October 2023); https://doi.org/10.1117/12.2684957

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