Detection of power disturbances using morphological gradient wavelet

• DOI: 10.1016/j.sigpro.2007.07.018
• Publication Date: 2007-07-31T07:27:18Z
• Authors: T.Y. Ji; Z. Lu; Q.H. Wu
• Keywords: Daubechies wavelet; Stationary wavelet transform; Second-generation wavelet transform

This paper presents a novel algorithm, morphological gradient wavelet (MGW), for the detection of power disturbances. MGW is a nonlinear wavelet transform that involves morphological operation in the decomposition process and presents the gradient information in the output. Applied to power systems, MGW extracts the features of disturbances and detects their location and duration. A variety of power disturbances have been simulated to evaluate the validity of MGW. Moreover, the advantages of the new algorithm are also addressed in comparison with Daubechies DB4 wavelet transform (DB4).