Open AccessVoltage sag analysis based on cluster analysis and correlation analysis
Author(s) -
Hao Líu,
Zeng Qi,
Shaohui Liu,
Zhuojun Wu,
Lei Li,
Rongrong Ma
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/853/1/012018
Subject(s) - voltage sag , cluster analysis , cluster (spacecraft) , correlation , voltage , basis (linear algebra) , data mining , computer science , statistics , mathematics , engineering , power quality , electrical engineering , geometry , programming language
Based on data mining algorithm, a voltage sag analysis method is proposed, which first performs clustering analysis and then correlation analysis. Firstly, the climatic factors are used to cluster the data, and then the correlation analysis of each cluster is carried out according to the selected voltage sag feature dimensions, finally, the strong association rules are obtained. Through the analysis of the example, it is found that there are some certain correlations between the climatic factors, the voltage sag dimensions and the causes of the voltage sag. These correlations can provide a theoretical basis for the prevention and control of voltage sag.