摘要
文中提出一种基于动态车流的电动汽车充电负荷时空分布概率建模方法,所建立的模型由交通路网模型、车辆时空转移模型和居民出行概率模型3个部分组成。交通路网模型考虑了车辆过红绿灯的影响,将道路分为3段计算车流密度。车辆时空转移模型反映了交通路况对行驶速度和耗电量的影响,行驶车辆可根据交通路况动态调整速度和行驶路径。居民出行概率模型基于NHTS2017数据集,得到出行目的地和出发时间的联合概率分布模型,进而抽样模拟出行链。以某市路网模型为例,采用蒙特卡洛法仿真预测电动汽车充电负荷的时空分布特性,并与现有方法的仿真结果及实际充电负荷曲线进行对比分析,验证了所提概率模型的正确性和有效性。
A probabilistic modeling method for the spatial-temporal distribution of electric vehicle(EV)charging load based on dynamic traffic flow is proposed.The model is composed of the traffic road network model,the spatial-temporal transfer model of vehicles and the probabilistic model of residents’traveling.Considering the influence of traffic lights,the road is divided into three sections to calculate the traffic density in the traffic road network model.The spatial-temporal transfer model of vehicles reflects the influence of traffic condition on the speed and power consumption of EVs.The marching vehicles can dynamically adjust the speed and traveling path according to the traffic condition.The probabilistic model of residents’traveling establishes the joint probability distribution of travel destination and departure time based on the NHTS2017 data set,and the trip chains are obtained by sampling simulation from the model.Simulations are performed based on the road network model of a typical urban area,and the Monte Carlo method is adopted to predict the spatial-temporal distribution characteristics of EV charging load.Compared with the results of the existing methods and the actual EV charging load curve,the correctness and effectiveness of the proposed probabilistic model are demonstrated.
作者
宋雨浓
林舜江
唐智强
何森
卢艺
毛田
SONG Yunong;LIN Shunjiang;TANG Zhiqiang;HE Sen;LU Yi;MAO Tian(School of Electric Power.South China University of Technology,Guangzhou 510640,China;Power Dispatching and Control Center of Shenzhen Power Supply Co..Ltd.,Shenzhen 518001,China;Electric Power Research Institute of China Southern Power Grid Company L.imited,Guangzhou 510080,China)
出处
《电力系统自动化》
EI
CSCD
北大核心
2020年第23期47-56,共10页
Automation of Electric Power Systems
基金
国家自然科学基金资助项目(51977080)
中央高校基本科研业务费专项资金资助项目(2019MS015)
深圳供电局有限公司科技项目(SZKJXM20160174)的资助。
关键词
电动汽车
动态车流
充电负荷
时空分布
概率模型
蒙特卡洛法
electric vehicle
dynamic traffic flow
charging load
spatial-temporal distribution
probability model
Monte Carlo method
