基于DBSCAN聚类的电力工程数据完整性分析

针对电力工程数据完整性分析困难的问题,提出了一种基于DBSCAN聚类算法的电力工程完整性分析方法.该分析方法包括数据获取、数据预处理、特征提取和聚类分析4个步骤,能从大规模电力工程数据中快速找出所缺失的数据,并对其进行形态分析.对电能表与智能终端数据缺失数量和数据缺失同步性进行多角度分析的结果表明,所提出的方法可以有效分析电力工程数据的完整性及其缺失的形态分布,对于提高电力工程数据的完整性及分析用户的用电情况均具有较好的参考价值.

Integrity analysis of power engineering data based on DBSCAN clustering

Aiming at the difficulty of data integrity analysis in power engineering, an integrity analysis method for power engineering based on the DBSCAN clustering algorithm was proposed. The proposed analysis method includes four steps, i.e.the data acquisition, data preprocessing, feature extraction and cluster analysis, and can quickly find the missing data from the large-scale power engineering data and perform the corresponding morphological analysis. The results of multi-angle analysis of the quantity and synchronization of data missing for the electric energy meter and intelligent terminal indicate that the proposed method can effectively analyze the integrity and the missing morphological distribution of power engineering data, and has good reference values for improving the integrity of power engineering data and analyzing the power consuming situation of users.