SmartGridComm · 2021
Data-driven Electric Vehicle Charging Station Placement for Incentivizing Potential Demand
IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids
Where should a city place charging stations with a limited budget?
A proximity based satisfaction model turns station placement into monotone submodular maximization. A greedy algorithm has a provable approximation ratio, with a Haikou case study using population, travel, and point of interest data.
Research themes
Cite this paper
Chenxi Sun, Tongxin Li, Xiaoying Tang. Data-driven Electric Vehicle Charging Station Placement for Incentivizing Potential Demand. IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, 2021. https://doi.org/10.1109/SmartGridComm51999.2021.9632309
BibTeX
@inproceedings{tongxin-station-placement,
title = {{Data-driven Electric Vehicle Charging Station Placement for Incentivizing Potential Demand}},
author = {Chenxi Sun and Tongxin Li and Xiaoying Tang},
year = {2021},
booktitle = {IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids},
url = {https://doi.org/10.1109/SmartGridComm51999.2021.9632309},
doi = {10.1109/SmartGridComm51999.2021.9632309}
}
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