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Method for division of urban load power supply district based on cluster analysis

机译:基于聚类分析的城市负荷供电区划分方法

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摘要

The division of urban power supply district is an essential issue in the medium voltage distribution network plan. This study develops a method for division of an urban load power supply district, integrating the open source data into the distribution network planning, at first, raw georeferenced point of information data is crawled by crawler program based on location retrieval service interface (Place API), the buildings' data of the planned urban district is extracted and power load estimation are introduced in detail, the dataset of the low-voltage load spatial distribution is set-up; secondly, the clustering algorithm selects both the local density of samples ρiand the distance between samples δias criteria to form the clusters, cluster centres are recognised from the binary pair in `decision map', as load density peaks. Thirdly, the spatial distribution dataset of the low-voltage users is taken as the data points in the clustering algorithm; the result of clusters corresponds to division in the power distribution with certain capability. Consequently, the methodologies proposed are verified on one example district of ~71.7587 hectares, the division scheme can provide theoretical guidance for the location and sizing of power distributors in the urban distribution network.
机译:在中压配电网规划中,城市供电区的划分是至关重要的问题。本文研究了一种将城市负载供电区划分的方法,将开源数据集成到配电网络规划中,首先,基于位置检索服务接口(Place API)的爬虫程序对原始数据的地理参考点进行爬网。提取规划城区的建筑物数据,详细介绍电力负荷估算,建立低压负荷空间分布数据集。其次,聚类算法选择样本的局部密度ρ n i和样本之间的距离δ n i nas准则来形成集群,集群中心从“决策图”中的二进制对中识别出来,当负载密度达到峰值时第三,以低压用户的空间分布数据集为聚类算法的数据点。集群的结果对应于具有一定能力的功率分配。因此,本文提出的方法在一个约71.7587公顷的示例区域中得到了验证,该划分方案可以为城市配电网中配电设备的位置和规模确定提供理论指导。

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