Analysis of the Appropriate Decomposition Level Based on Discrete Wavelet Transform for Detection of Power Quality Disturbances

Abstract

The improvement in Power Quality has been a concern for both the public and private sectors in recent years. One of the main problems within this topic is the appearance of anomalies or disturbances in the power supply, which represent sudden changes in the waveforms of the signals and cause severe damage to the utility grid. This paper presents a comparative study of different resolution levels for the analysis of eight types of Single Power Quality Disturbances using Multiresolution Analysis. A set of disturbances was generated in MATLAB through their mathematical models and the extracted wavelet-based features were normalized by Z-score. The results show that the use of nine resolution levels leads to an appropriate decomposition, since it allows obtaining a greater amount of information, without compromising the computational performance, which would facilitate a future classification process.