基于多元数据驱动的配电网户变关系识别方法

Identification Method of User-transformer Relationship in Distribution Network Based on Voltage and Power Data

针对配电网户变关系识别不准确而影响配电网正常运作和故障诊断定位的问题,提出了一种基于多元数据驱动的配电网户变关系识别方法。首先,定义了电压的多维波动特征参数指标;其次,采用t分布随机邻域嵌入(t-SNE)算法对电压波动特征矩阵进行降维;然后,利用BIRCH聚类算法对降维后的电压波动特征进行聚类,生成虚拟用户;最后,基于用户功率与上级电表的功率平衡关系假设进行户变关系配对,完成配电网户变关系的识别。案例分析结果表明,相比于之前的户变关系识别方法,所提方法提高了识别准确率。

Aiming at the problem of inaccurate identification of user-transformer relationship in distribution networks,which affects the normal operation of distribution networks and fault diagnosis and localisation,a multivariate data-driven user-transformer relationship identification method based on multivariate data is proposed.Firstly,the multidimensional fluctuation characteristic parameter index of voltage is defined,secondly,the t-distributed stochastic neighbourhood embedding(t-SNE)algorithm is used to downscale the voltage fluctuation characteristic matrix,and then the BIRCH clustering algorithm is used to cluster the downsized voltage fluctuation characteristics to form virtual users,and finally,based on the assumption of the user’s power balance relationship with the higher-level meter,user-transformer relationship identification is carried out,and user-transformer relationship identification is completed in the distribution network.The results show that compared with the previous identification methods,the identification accuracy is improved.