Power quality event detection using joint 2-D-wavelet subspaces

Abstract

In this work, we present a novel two-dimensional (2-D) representation of power system waveforms for the automatic analysis and detection of transient events. The representation is composed of a matrix whose rows are formed by time segments of digital waveforms. By the appropriate selection of the time segment length, the 2-D data exhibits wave-like image shapes. The general shape is immediately disturbed whenever a power quality transient event occurs. We propose the use of two dimensional discrete wavelet transforms (2-D-DWT) to detect these disturbances. It has been observed that, after omitting the approximation space signals of the wavelet transform and denoising the detail space signals, the inverse 2-D-DWT provides good detection and localization results, even for cases where conventional methods fail. Examples are presented.