基于密度峰值聚类的电动汽车充电站选址定容方法

An electric vehicle charging station siting and sizing method based on a density peaks clustering algorithm

针对电动汽车充电需求,考虑路径交通流量,提出了基于密度峰值聚类的电动汽车充电站选址定容优化方法。首先分析规划区域交通流量和停车场开放指数,构建电动汽车充电需求的空间分布数据点集合。采用密度峰值的聚类方法分析充电需求空间分布密集程度,得到聚类备选群簇。其次考虑聚类群簇的内聚度和分离度,采用总体平均轮廓系数优选聚类结果,从而确定聚类中心为电动汽车充电站选址。最后预测规划区域内电动汽车保有量,计算聚类群簇覆盖范围内的充电需求总和,按各群簇充电需求比例确定相应群簇中心的充电站容量。依据所提方法开展某城市区域的电动汽车充电站选址定容,论证了所提方法的可行性。

An optimization method for the location and capacity of Electric Vehicle(EV)charging stations based on density peaks clustering of traffic flow is proposed to tackle the issue of EV demand.First,planning area traffic flow and parking lot opening index are analyzed,and the spatial distribution of EV charging demand data point collection is constructed.Then,the density peaks clustering method is used to analyze the density of the spatial distribution of charging demand,and the candidate clusters are obtained.Then,considering the cohesion and separation of clusters,the overall average contour coefficient is used to optimize the clustering results,so as to determine the location of the clustering center for EV charging stations.Further,based on the penetration rate of EVs,the number of EVs is predicted to determine the total charging demand of various types of EVs in the planned area.The charging station capacity of the corresponding cluster center is determined according to the charging demand proportion of each cluster.The location and capacity of EV charging stations in a particular urban area are determined,and the demonstration shows the feasibility of the method.