Submitted manuscript, 316 KB, PDF document
Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Accepted author manuscript, 316 KB, PDF document
Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Electric Vehicle Charging Reservation Under Preemptive Service
AU - Cao, Yue
AU - Liu, Shuohan
AU - He, Ziming
AU - Dai, Xuewu
AU - Xie, Xiaoyan
AU - Wang, Ran
AU - Yu, Shengping
PY - 2019/9/30
Y1 - 2019/9/30
N2 - Electric Vehicles (EV) are environment-friendly with lower CO2 emissions, and financial affordability (in term of battery based refuel) benefits. Here, when and where to recharge are sensitive factors significantly impacting the environmental and financial gains, these are still challenges to be tackled. In this paper, we propose a sustainable and smart EV charging scheme enables the preemptive charging functions for heterogeneous EVs equipped with various charging capabilities and brands. Our scheme intents to address the problems when EVs are with various ownerships and priority, in related to the services agreed with charging infrastructure operators. Particularly, the anticipated EVs' charging reservations information with heterogeneity (are multiscale) including their EV type, expected arrival time and charging waiting time at the charging stations (CSs), have been considered for design, planning and optimal decision making on the selection (i.e., where to charge) among the candidature CSs. We have conducted extensive simulation studies, by taking the realistic Helsinki city geographical and traffic scenarios as an example. The numerical results have confirmed that our proposed preemptive approach is better than the First-Come-First-Serve (FCFS) based system, associated with its significant improvement on the reservation feature in EV charging.
AB - Electric Vehicles (EV) are environment-friendly with lower CO2 emissions, and financial affordability (in term of battery based refuel) benefits. Here, when and where to recharge are sensitive factors significantly impacting the environmental and financial gains, these are still challenges to be tackled. In this paper, we propose a sustainable and smart EV charging scheme enables the preemptive charging functions for heterogeneous EVs equipped with various charging capabilities and brands. Our scheme intents to address the problems when EVs are with various ownerships and priority, in related to the services agreed with charging infrastructure operators. Particularly, the anticipated EVs' charging reservations information with heterogeneity (are multiscale) including their EV type, expected arrival time and charging waiting time at the charging stations (CSs), have been considered for design, planning and optimal decision making on the selection (i.e., where to charge) among the candidature CSs. We have conducted extensive simulation studies, by taking the realistic Helsinki city geographical and traffic scenarios as an example. The numerical results have confirmed that our proposed preemptive approach is better than the First-Come-First-Serve (FCFS) based system, associated with its significant improvement on the reservation feature in EV charging.
U2 - 10.1109/ICIAI.2019.8850812
DO - 10.1109/ICIAI.2019.8850812
M3 - Conference contribution/Paper
SN - 9781728135946
BT - IEEE International Conference on Industrial Artificial Intelligence (IAI) Proceedings 2019
PB - IEEE
T2 - IEEE International Conference on Industrial Artificial Intelligence (IAI)
Y2 - 23 July 2019 through 25 July 2019
ER -