文章摘要
电动汽车充电负荷时空分布预测
Prediction of Time and Space Distribution of Electric Vehicle Charging Load
投稿时间:2018-10-10  修订日期:2018-10-28
DOI:
中文关键词: 充电负荷  蒙特卡洛  最小二乘法  灰色关系度  时空分布
英文关键词: Charging load  Monte Carlo  least square method  grey relational degree  spatiotemporal distribution
基金项目:
作者单位E-mail
李丹奇 东南大学电气工程学院 ldq19960313@163.com 
郑建勇 国网江苏省电力有限公司电力科学研究院  
史明明 东南大学电气工程学院  
李陶然 东南大学电气工程学院  
沙浩源 东南大学电气工程学院  
梁馨予 东南大学电气工程学院  
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中文摘要:
      采用最小二乘法与灰色关系度理论建立了电动汽车保有量预测模型,将车辆状态转移矩阵引入传统停车需求模型,预测了电动汽车随时刻变化的实际泊车分布特性;基于蒙特卡洛方法,针对电动私家车、电动公交车、电动出租车、电动公务车各自对应的充电需求,分别模拟了其充电行为,推测出了不同用地类型区域的电动汽车充电负荷曲线。本文结合了徐州市公共汽车运营现状,给出大型充电站的规划布局建议,为充电站规划建设提供理论支撑。
英文摘要:
      Based on the least square method and grey relational degree theory, a model for predicting the ownership of electric vehicles is established. The state transition matrix is introduced into the traditional parking demand model to predict the actual parking distribution characteristics of electric vehicles. Based on the Monte Carlo method, this paper aims at electric private cars, electric buses and electric taxis. The charging requirements of electric business vehicles are simulated respectively, and their charging behaviors are simulated respectively. The daily curve of charging load is obtained by simulation. The results show that the peak-valley difference of daily curve of electric vehicle charging load is large, and the demand of electric bus charging load will take up a large proportion.
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