浙江工业大学机械工程学院，浙江省 杭州市 310014
College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310014, China
This work is supported by National Natural Science Foundation of China (No. 61773347) and Zhejiang Commonweal Technology Research Project （No. LGF20F030001).
Existing studies on waiting time of charging stations often neglect the time-varying differences in charging requirements for different vehicles. A prediction method of charging waiting time distribution for electric vehicles (EVs) in Internet of Things (IOT) perception environment is proposed to comprehensively explore the time-varying law of charging waiting time. Firstly, on the basis of determining the quantity distribution of vehicles arriving at the charging stations and the charging duration distribution, the M/G/n queuing model is used to simulate the queuing system at charging stations and solve the distribution function of charging waiting time for EVs. Secondly, the utility function for user to select charging stations is established, the Multi-logit model is used to predict the charging demand in each charging station. Furthermore, the average arrival rate, service time and variation coefficient are updated according to the predicted value of charging demand and the real-time data of network-connected charging stations, and the short-time prediction of EVs charging waiting time is realized with the distribution function of charging waiting time. Finally, taking a certain area of a city as an example, the accuracy of this distribution is verified, and the influence of charging waiting time distribution and reliability on charging stations is analyzed, which provides a decision basis for reducing queuing congestion and balancing power system load.
DONG Hongzhao,FANG Yaxiu,FU Fengjie.Prediction Method of Waiting Time Distribution for Electric Vehicle in Internet of Things Perception Environment[J/OL].Automation of Electric Power Systems,http://doi.org/10.7500/AEPS20190523010.