Prediction and Distribution of Ev Charging Stations

被引:4
|
作者
Zuo, Anbang [1 ]
机构
[1] Sch North China Elect Power Univ, Baoding 300000, Hebei, Peoples R China
关键词
multi-objective charging station quantitative prediction resources allocation;
D O I
10.1063/1.5089090
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In this paper, we established a multi-objective model of quantitative prediction and resources allocation of electric-vehicle charging station, based on the American situation. We came up with the priorities for urban and rural development of charging stations and got the density map of charging station in America, which can help the maturity of the electric-vehicle industry. First, we built a model of quantitative prediction of charging stations based on the daily charging demand of Ev and the aggregate demand of charging stations. We used it to calculate the number of public charging stations when all the passenger vehicles turn to electric vehicles. We acquired the current distribution of charging stations according to the urban-rural demarcation standards from relevant scholars, then we get the proportion of urban and rural distribution based on the assumption. Second, we chose the charging demand, charging mode, charging station operating mode, charging station construction goal, charging station service radius, power grid planning, road network planning, land use planning, technology development and policy as influencing factors according to the central theory of three principles. Therefore, this model suits for countries with different population density, geography and wealth distribution. Ultimately, We chose the charging demand and the charging station service radius as the main factor, and we concluded that we should prioritize developing the cities.
引用
收藏
页数:7
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