摘要
准确的户变关系是配网线损计算、故障定位和三相平衡等高级应用的基础。低压配网的户变关系辨识算法大多基于电压相关性原理,而电压相关性随供电半径增加而减弱,电压采集频次较低无法可靠捕获电压的“共性波动”,使得辨识准确率普遍不高。提出了一种基于等距特征映射(isometric mapping,ISOMAP)降维和改进K-means聚类的户变关系辨识方法,为了增长电压序列的时间尺度,首先研制基于窄带物联网(narrow band internet of things,NB-IoT)技术的智能电表本地通信模块,优化电压采集方案,提高电压采集频次至288点/d;其次将各节点之间的拓扑关系视为高维流型,采用ISOMAP对高维矩阵进行降维处理;最后利用测地距离对K-means算法改进,做聚类计算得到最终户变关系辨识结果。所提算法提高了节点之间的距离置信度,与主成分分析法(principal component analysis,PCA)和K-means算法相比,所提算法对户变关系辨识准确率高达97.1%,在配网实际运行的数据验证了所提算法的辨识有效性。
Accurate user-transformer relationship is regarded as the basis of advanced applications such as line loss calculation,fault location and three-phase imbalance analysis.The identification algorithm of user-transformer relationship in power distribution is mainly based on the principle of voltage correlation.Due to the voltage correlation weakens with the increase of power supply radius,the“common fluctuation”of voltage can not be captured reliably with lower acquisition frequency.The low identification accuracy is caused.An identification algorithm of user-transformer relationship based on ISOMAP(isometric mapping)and improved K-means was proposed.Firstly,the local communication module of smart meter based on NB-IoT was designed to extend the time scale of voltage sequence.By optimizing the acquisition architecture,the voltage sequence was increased to 288 points each day.Secondly,the topological relationship between nodes was regarded as a high-dimensional flow pattern,and ISOMAP algorithm was used to reduce the dimension of the voltage matrix.Finally,the K-means algorithm was improved by using the geodesic distance,and the identification result of user-transformer relationship was obtained by clustering.The confidence of the distance between nodes was improved by proposed method.The results show that the identification accuracy of user-transformer relationship can reach 97.1%compared with PCA(principal componet analysis)and K-means algorithm,respectively.The identification effectiveness of the proposed algorithm is verified by the actual operation data set of distribution network.
作者
刘洋
王剑
唐明
陆水锦
LIU Yang;WANG Jian;TANG Ming;LU Shui-jin(Institute of Electronic and Electrical Engineering, Civil Aviation Flight University of China, Guanghan 618307, China;Sichuan Energy Internet Research Institute of Tsinghua University, Chengdu 610200, China;Yangtze Delta Region Institute of Tsinghua University, Jiaxing 314006, China)
出处
《科学技术与工程》
北大核心
2022年第7期2725-2734,共10页
Science Technology and Engineering
基金
电力系统及大型发电设备安全控制与仿真国家重点实验室面上项目(SKLD20KM03)
中国民用航空飞行学院青年基金(XJ2020004401)。
关键词
户变关系
电压相关性
高维流形
测地距离
ISOMAP
改进K-MEANS
user-transformer relationship
voltage correlation
high dimensional flow pattern
geodesic distance
ISOMAP
improved K-means
作者简介
第一作者:刘洋(1993—),女,汉族,黑龙江黑河人,硕士,讲师,研究方向:电力系统数据挖掘、物联网技术研究及相关工程应用,E-mail:1640406407@qq.com;通信作者:王剑(1993—),男,汉族,四川南充人,硕士,工程师,研究方向:嵌入式系统、物联网通信技术,E-mail:wangjian@tsinghua-eiri.org。
