Authors : M. Sushama and G. Tulasi Ram Das
Abstract: In this study, two prominent methods for detection and classification of power quality disturbance are proposed. The first one, based on the statistical analysis of adaptive decomposition signals is proposed, the second one is a new technique for detecting and characterizing disturbances in power systems based on wavelet transforms. The voltage signal under investigation is often corrupted by noises, therefore the signal is first de-noised and then wavelet transform is applied. Using the first detail wavelet coefficients, voltage disturbance is detected and its duration is determined. The combination of an adaptive prediction filter based sub-band decomposition structure with a rule based histogram analysis block produce successful detection and classification results on our real life power system transient data. In this study, voltage sag is considered for comparing both approaches. Proposed scheme is implemented using MATLAB (7.0.1), Simulink, DSP and Wavelet toolboxes.
M. Sushama and G. Tulasi Ram Das , 2009. Detection and Classification of Voltage Sags Using Adaptive Decomposition and Wavelet Transforms. International Journal of Electrical and Power Engineering, 3: 50-58.