摘要
城市电力负荷的空间分布提供负荷大小及其空间位置,是配电网现状评价和空间负荷预测的基础和前提条件。提出了一种城市负荷空间分布的聚类群簇分析方法,基于Python爬虫技术利用百度地图收集规划区域用户开源信息,并采用正则匹配识别用户所在的建筑体及其属性,依据建筑体单位面积用电功率估计电力负荷,构建具有时间、空间和负荷功率的负荷空间分布样本集合。采用样本局部密度和样本间距两个指标进行中低压用户负荷的聚类,依据群簇属性计算得到负荷群簇的负荷中心坐标、局部负荷密度大小以及分布半径以分析负荷空间分布特征。针对某城市供电网格算例,对比分析群簇属性与规划数据的一致性,开展变电站配置的合理性分析,说明所提方法的准确有效性。
The spatial distribution of urban power load provides accurate data of load size and its spatial location, which is the basis and precondition for the evaluation of current distribution network and spatial load forecasting. A clustering analysis method for urban load spatial distribution is proposed. Open source information of users in planning areas on about:blank map based on Python crawler technology is collected and then the building where the users are located and their attributes is identified by regular matching function. Power load is estimated according to the power consumption per unit area of building body to construct a sample set of spatial distribution of power load in which the samples have three attributes: time, space and load power. Further, clustering analysis of medium and low voltage user load is performed based on the two indexes of sample local density and sample spacing and the coordinates of load center, the local load density and the distribution radius of load clusters are calculated on the basis of the clusters’ attributes. Finally, taking a power grid of a city as an example, the consistency of the clusters’ attribute indicators is compared with the planning data. Rational analysis of substation configuration is carried out and the accuracy and effectiveness of the proposed method is illustrated.
作者
刘婉兵
李妍
杜明秋
王少荣
LIU Wanbing;LI Yan;DU Mingqiu;WANG Shaorong(State Key Laboratory of Advanced Electromagnetic Engineering and Technology,Huazhong University of Science and Technology,Wuhan 430074,China)
出处
《电力系统自动化》
EI
CSCD
北大核心
2019年第5期59-65,306,66-287,共9页
Automation of Electric Power Systems
基金
国家重点研发计划智能电网技术与装备重点专项资助项目(2017YFB0902800)~~
关键词
电力负荷空间分布
开源信息
配电网评估
配电网规划
spatial distribution of power load
open source information
distribution network evaluation
distribution network planning
