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METHOD OF POWER USER CLASSIFICATION BASED ON DISTRIBUTED K-MEANS, STORAGE MEDIUM AND CLASSIFICATION DEVICE

机译:基于分布式k型k均值,存储介质和分类装置的电力用户分类方法

摘要

A method of a power user classification based on distributed K-means, a storage medium and a classification device are provided. The method includes: obtaining, by N load aggregators, power consumption data of power users managed by respective load aggregators; performing, by each load aggregator, a normalization operation on time series load data of the power users managed by the load aggregator; forming a N×N dimensional adjacency matrix A; performing K-means clustering on normalized time series load data, to obtain the respective centroids and user groups characterized by the respective centroids; sharing, by the respective load aggregators, the centroids and the number of users under the respective centroids based on the adjacency matrix A, and obtaining consistent centroids by multiple load aggregators; after an overall iteration ends, obtaining, by the respective load aggregators, the consistent centroids consistent with the K-means centroid based on global data, to realize user classification.
机译:提供了一种基于分布式K-icl,存储介质和分类装置的功率用户分类的方法。该方法包括:通过N负载聚合器获得由相应负载聚合器管理的功率用户的功耗数据;按每个负载聚合器执行由负载聚合器管理的功率用户的时间序列加载数据的归一化操作;形成N×N尺寸邻接矩阵A;在归一化时间序列负载数据上执行K-means聚类,以获得各个质心特征的各个质心和用户组;根据相邻矩阵A共享,由各个负载聚合器,质心和相应质心下的用户数,并通过多个负载聚合器获取一致的质心;在整体迭代结束之后,通过相应的负载聚合器获得与基于全局数据的K-均值质心一致的一致质心来实现用户分类。

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