基于动态交通信息的电动汽车充电需求预测模型及其对配网的影响分析  

Electric Vehicle Charging Demand Prediction Model Based on Dynamic Traffic Information and Its Impacts on Distribution Networks

作　　者：李磊[1] 赵新[2] 李晓辉[1] 刘伟东 刘小琛[1] 冯炜 LI Lei;ZHAO Xin;LI Xiaohui;LIU Weidong;LIU Xiaochen;FENG Wei(Electric Power Science Research Institute of State Grid Tianjin Electric Power Company,Tianjin 300021,China;State Grid Tianjin Electric Power Company,Tianjin 300010,China;NARI Group Corporation,Nanjing 210003,China)

机构地区：[1]国网天津市电力公司电力科学研究院,天津300021 [2]国网天津市电力公司,天津3000101 [3]南瑞集团有限公司,南京210003

出　　处：《电网与清洁能源》2020年第3期107-118,共12页Power System and Clean Energy

基　　金：国家重点研发计划项目(2016YFB0101800);国网天津市电力公司科技项目(KJ18-1-31)。

摘　　要：针对电动汽车兼具交通工具和移动负荷的特性,考虑交通系统对电动汽车行驶行为和充电行为的影响,提出一种基于动态交通信息的电动汽车充电需求预测模型,并评估规模化充电对配网的冲击。该方法首先针对城市交通路网多交叉口特征,建立了融合动态交通信息以及考虑路段阻抗和节点阻抗的“时间-流量”实时动态路网模型,并根据城市路网规模确定了相应的交通网-配电网的交互模型。其次在分析电动汽车行驶特性和充电特性基础上构建了单体电动汽车移动模型。采用OD矩阵分析方法模拟EV随机移动行为和动态Dijkstra算法为车主推荐行驶和充电路线。最后,设计了电动汽车路径规划实验和不同场景下的充电负荷预测算例,验证所提模型的可行性和有效性。For the characteristics of electric vehicles(EVs)with both transportation and mobile loads,this paper presents an electric vehicle charging demand prediction model based on dynamic traffic information,considering the influence of the transportation system on the driving and charging behaviors of EVs.And the impact of large-scale charging on distribution networks is evaluated as well.In this methodology,given the feature of multiple intersections in the urban traffic road network,the"time-flow"realtime road network model is firstly established,which integrates the dynamic traffic information and takes the impedance of the road segment and the impedance of the node into consideration.And also,the corresponding interactive model of transportation networkdistribution network is determined according to the scale of road network.Furthermore,a single EV mobility model is constructed based on the analysis of EV driving and charging characteristics.The OD matrix analysis method is utilized to simulate EV random movement behavior and the driving and charging route is recommended for EV owners via dynamic Dijkstra algorithm.At last,the EV path planning experiment and charging load prediction examples under different scenarios are designed.The results have verified the feasibility and validity of the proposed model.

关 键 词：电动汽车 动态交通信息 充电负荷预测 配网评估 路径规划 

分 类 号：TM714[电气工程—电力系统及自动化]