服务质量
计算机科学
电动汽车
调度(生产过程)
充电站
稳健性(进化)
实时计算
可靠性工程
功率(物理)
汽车工程
计算机网络
工程类
物理
化学
基因
量子力学
生物化学
运营管理
作者
Dingsong Cui,Zhenpo Wang,Peng Liu,Zhaosheng Zhang,Shuo Wang,Yiwen Zhao,David G. Dorrell
出处
期刊:IEEE Transactions on Transportation Electrification
日期:2023-11-21
卷期号:10 (3): 6449-6459
被引量:6
标识
DOI:10.1109/tte.2023.3334809
摘要
The widespread adoption of electric vehicles (EVs) with fast-charging capability has presented significant challenges to the safe operation of power distribution networks. Issues such as node overvoltage and frequency fluctuations should be addressed to ensure power quality while maximizing charging Quality-of-Service (QoS) for EV users. This challenge is particularly crucial for fast-charging events that have more flexible demands. Charging priority has traditionally been used to determine an EV charging scheme, including waiting time, arrival order and other factors. However, the scheduling potential predicted from the vehicle side has not been fully considered in the priority establishment when determining real-time operation. To address this gap, a bi-level framework is proposed for a coordinated charging scheme at the fast-charging station that factors in demand-based priority. The framework considers available charging power allocation at different priority levels and optimizes the charging scheme under the same priority level based on three real-time QoS objectives. This approach can improve the average charging QoS for EV users compared to traditional algorithms without considering the demand priority. In robustness evaluation, the QoS of scheduled charging events can reach 86.9% (median) of the optimal solution, and the range of fluctuations in different trials is relatively more stable.
科研通智能强力驱动
Strongly Powered by AbleSci AI