Voltage sag homologous identification method based on Pearson correlation coefficient and OPTICS

Abstract

The invention provides a voltage sag homologous identification method based on a Pearson correlation coefficient and OPTICS. The method comprises the following steps: S1, acquiring sag monitoring data recorded by a voltage sag monitoring device; S2, quantifying the sag monitoring data similarity based on a Pearson correlation coefficient; S3, obtaining homologous recognition features of the sag monitoring data, performing homologous clustering based on the homologous recognition features of the sag monitoring data through an OPTICS algorithm, and outputting a clustering result reachable graph, wherein the homologous recognition features comprise sag monitoring data similarity and sag duration; and S4, obtaining a clustering result cluster number based on a reachable graph sag number, and outputting a homologous recognition result. The problem that homologous identification features are too single is avoided, clusters of different densities can be found, the voltage sag homologous identification result is finally obtained, repeated redundant information can be effectively removed through the voltage sag homologous identification result, the real occurrence level of regional sag can be obtained, the value density of data is improved, and the intensity and difficulty of calculation and analysis are reduced.

Description

technical field [0001] The invention relates to the technical field of voltage sag homology identification, in particular to a voltage sag homology identification method based on Pearson correlation coefficient and OPTICS. Background technique [0002] The rapid development of modern industry and high-tech has led to a large number of intelligent and automated industrial equipment sensitive to voltage sags being put into production, and equipment failures caused by voltage sags often cause huge economic losses to users. Based on this, the prevention and treatment of voltage sags become particularly important. The monitoring of voltage sag is the basis and premise of prevention and control. With the development of my country's smart grid, more and more power quality monitoring devices are installed in the power system, and the monitoring data containing voltage sag information in many areas gradually presents redundant information. remaining status. How to grasp the real lev...

AI Technical Summary

Problems solved by technology

However, the existing research has the problem that only using waveform similarity as the homology identification feature is too simple, and the clustering method used cannot find clusters of different densities

Images