Research on optimization of electric vehicle charging station network based on cost model

Jin Sun; Rujin Zhou; Li Wang; Kai Huang; Bo Xiang

doi:10.1117/12.3026952

8 April 2024 Research on optimization of electric vehicle charging station network based on cost model

Jin Sun, Rujin Zhou, Li Wang, Kai Huang, Bo Xiang

Proceedings Volume 13090, International Conference on Computer Application and Information Security (ICCAIS 2023); 1309020 (2024) https://doi.org/10.1117/12.3026952
Event: International Conference on Computer Application and Information Security (ICCAIS 2023), 2023, Wuhan, China

Abstract

The promotion of electric vehicles can reduce greenhouse gas emissions. However, drivers prefer using traditional cars, because the electric cars have some problems that currently cannot be solved. It cannot fulfill a long-distance driving performance and has mileage anxiety problem. This problem can be eased by installing more charging stations in appropriate locations. In order to determine the location of the public charging station and minimize the total cost while satisfying a certain degree of coverage, this article proposes two optimization models: the complementary partial (CP) coverage method and geometric segmentations (GS) strategy. Two mathematical models are employed to identify the most cost-effective sites for Electric Vehicle (EV) charging stations. This project utilizes the CP method and the GS strategy. Through case studies, it is demonstrated that GS proves to be a more precise approach compared to CP.

Citation Download Citation

Jin Sun, Rujin Zhou, Li Wang, Kai Huang, and Bo Xiang "Research on optimization of electric vehicle charging station network based on cost model", Proc. SPIE 13090, International Conference on Computer Application and Information Security (ICCAIS 2023), 1309020 (8 April 2024); https://doi.org/10.1117/12.3026952

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