Keywords
DC charging station, risk assessment, traffic simulation, optimized operation and maintenance
Abstract
With the rapid growth of the number of electric vehicles, in view of the rough and inefficient operation and maintenance of the current DC charging station, a method based on risk assessment for the operation and maintenance of DC charging stations is proposed. Firstly, this paper establishes the operation and maintenance system. The consequences of the charging pile failure event to the user is defined as the loss of time (LOT) combining the fault parameters to establish the risk assessment model and realize system risk quantification. The risk tracking of the charging station is carried out by the energy not charged (ENC). The risk level of each station is evaluated while the operation and maintenance timing is determined. Secondly, the model of driving and charging of users is built. The dynamic traffic simulation is used to calculate risk indicators. Finally, the optimal operation and maintenance model of DC charging station aiming at economy and reliability is constructed to determine the maintenance duration of each station. The results is used to calculate the relevant risk indicators imitatively. Finally, a DC charging station optimization operation and maintenance model with the goal of economy and reliability is constructed to determine the operation and maintenance time of each station. The results of simulation examples show that compared with the current operation and maintenance work, this strategy can not only meet the operation and maintenance requirements, but also significantly improve the reliability of the system and improve the overall operation and maintenance efficiency.
DOI
10.19781/j.issn.16739140.2021.01.011
First Page
96
Last Page
105
Recommended Citation
FANG, Hualiang; LIAO, Jiaqi; XU, Yan; QIAN, Kejun; ZHOU, Chengke; and DING, Yurong
(2021)
"Maintenance strategy research of DC charging stations for electric vehicle based on risk assessment,"
Journal of Electric Power Science and Technology: Vol. 36:
Iss.
1, Article 11.
DOI: 10.19781/j.issn.16739140.2021.01.011
Available at:
https://jepst.researchcommons.org/journal/vol36/iss1/11