摘要
基于出行链理论提出一种电动汽车充电需求分析方法,探讨了电动汽车一天出行过程中在不同区域内停驻时长的概率分布特点,对电动汽车空间转移概率进行3次B样条最小二乘曲线拟合,通过蒙特卡洛法并结合NHTS2009数据构建了电动汽车一天出行链,实现对用户行为规律的精细化模拟,并在设计2种充电行为的基础上对不同停驻区域的电动汽车充电需求进行了分析。该方法有效弥补了传统方法对电动汽车日间充电需求分析的不足,具有较高的精确性和原理清晰、易于操作等特点。
A method of EV（Electric Vehicle） charging demand analysis based on the trip chain theory is proposed. The daily probability distribution of EV parking durations in different regions is discussed. The least squares curve fitting is performed for the cubic B spline of EV spatial transition probability and the Monte Carlo method is combined with the NHTS2009 dada for establishing the daily EV trip chain to precisely simulate user＇s behavior. Two kinds of charging behavior are designed,based on which,the EV charging demands of different parking regions are analyzed. The proposed method overcomes the shortages of traditional methods in the daytime EV charging demand analysis and has the advantages of high accuracy ,clear principle and easy application.
出处
《电力自动化设备》
EI
CSCD
北大核心
2017年第8期105-112,共8页
Electric Power Automation Equipment
基金
国家重点研发计划资助项目(2017YFB0902203)~~
关键词
电动汽车
出行链
蒙特卡洛法
充电行为
充电需求
electric vehicles
trip chain
Monte Carlo methods
charging behavior
charging demand
