2022
Liu, Kai; Gao, Hong; Wang, Yang; Feng, Tao; Li, Cheng
Robust charging strategies for electric bus fleets under energy consumption uncertainty Journal Article
In: Transportation Research Part D: Transport and Environment, vol. 104, pp. 103215, 2022, ISSN: 1361-9209.
Abstract | Links | BibTeX | Tags: Battery performance, Column generation, Damage prevention, Energy consumption uncertainty, Robust optimization
@article{LIU2022103215,
title = {Robust charging strategies for electric bus fleets under energy consumption uncertainty},
author = {Kai Liu and Hong Gao and Yang Wang and Tao Feng and Cheng Li},
url = {https://www.sciencedirect.com/science/article/pii/S1361920922000451},
doi = {https://doi.org/10.1016/j.trd.2022.103215},
issn = {1361-9209},
year = {2022},
date = {2022-01-01},
journal = {Transportation Research Part D: Transport and Environment},
volume = {104},
pages = {103215},
abstract = {Charging management has a profound impact on the reliability and safety of electric bus (EB) services. However, the actual charging operation of EB fleets is a critical challenge due to uncertain energy consumption, limited charging resources and other factors. A deterministic model and a robust model with a probability-free uncertainty set are proposed and compared. The power is optimized via rational allocation of charging resources, where the uncertainty of energy consumption is addressed to achieve the dual goals of reducing charging expenses and improving system robustness. A column generation algorithm is designed to solve the optimization issue. The experimental results show that the obtained robust charging strategies can achieve up to 97.88% utilization of charging resources at low electricity prices. Moreover, the robust model can effectively prevent low electric quantity and delayed departure issues for EBs caused by the uncertainty of energy consumption.},
keywords = {Battery performance, Column generation, Damage prevention, Energy consumption uncertainty, Robust optimization},
pubstate = {published},
tppubtype = {article}
}
Charging management has a profound impact on the reliability and safety of electric bus (EB) services. However, the actual charging operation of EB fleets is a critical challenge due to uncertain energy consumption, limited charging resources and other factors. A deterministic model and a robust model with a probability-free uncertainty set are proposed and compared. The power is optimized via rational allocation of charging resources, where the uncertainty of energy consumption is addressed to achieve the dual goals of reducing charging expenses and improving system robustness. A column generation algorithm is designed to solve the optimization issue. The experimental results show that the obtained robust charging strategies can achieve up to 97.88% utilization of charging resources at low electricity prices. Moreover, the robust model can effectively prevent low electric quantity and delayed departure issues for EBs caused by the uncertainty of energy consumption.