Multiple power quality disturbances detection and classification with fluctuations of amplitude and decision tree algorithm

Recently, power quality (PQ) researches have attracted great remarks by increasing the PQ issues in power systems. In the current study, a new and straightforward classification method of PQ events such as voltage sag, voltage swell, voltage interruption, voltage flicker, voltage harmonics, and voltage sag with harmonics, voltage swell with harmonics, and voltage interruption with harmonics is presented and investigated. The dataset for synthesizing the PQ events is produced in MATLAB R2016a software. Three classifiers, such as K-nearest neighbors', support vector machine, and decision tree (DT) algorithms, are utilized to recognize the PQ events categories. Moreover, the calculated results show that the DT algorithm is more capable and accurate in classifying the different varieties of PQ events.

Automated summary

In this study, a new classification method for power quality (PQ) events is proposed and three classifiers are used to recognize different types of PQ events. The results show that the decision tree algorithm is more accurate and capable in classifying PQ events.