Power system switching transients analysis using multiresolution signal decomposition

Deregulation and embedded generation are two important reasons for the recent interest in power quality. Other important reasons are the increased emission of disturbances by equipment and the increased susceptibility of equipment, production processes, and manufacturing industry to voltage disturbances. Thus it is essential to establish a real time power quality monitoring system to detect power quality disturbance. Wavelet transform (WT) is a mathematical tool, which provides an automatic detection of power quality disturbance (PQD) waveforms, especially using Daubechies family. Several types of Wavelets Network algorithms have been considered for detection of power quality problems. But both time and frequency information are available by multi resolution analysis (MRA) alone. This paper presents the application of wavelet transform to detect, localize, and extract power switching disturbance. A power system switching transients have been simulated using MATLAB-7.01. The key idea underlying the approach is to decompose a given disturbance signal into other signals which represent a smoothed version and a detailed version of the original signal. The decomposition is performed using multiresolution signal decomposition techniques. The proposed technique appears to be robust for detection and localization of power quality disturbances created due to capacitor switching and load switching.