Selecting wavelet functions for detection of power quality disturbances

This paper considers Discrete Wavelet Transform (DWT) for the detection of power quality disturbances. Wavelet Function Biorthogonal 3.9 is used as a base function due to its frequency response and information time localization properties. A methodology is proposed in order to choose the wavelet function that holds the best characteristics. Disturbances considered are low frequency disturbances such as flicker and harmonics and high frequency disturbances such as transient and voltage sags. Due to time-frequency localization properties, Discrete Wavelet Transform permits decomposition of signals in different energy levels. The first level of decomposition allows for detecting the start or the end of a disturbance by convolving the high pass decomposition filter (HPDF) with the disturbance.