A correlation-based noise suppression algorithm for power quality monitoring through wavelet transform

The wavelet transform (WT) technique has been proposed for detecting and localizing transient disturbance in the power systems. The disturbance is detected by comparing the transformed signal with an empirically-given threshold. However, as the signal under analysis contains noises, especially the white noise with flat spectrum, the threshold is difficult to give. Due to the nature of flat spectrum, a filter cannot just get rid of the noise without removing the significant disturbance signals together. To enhance the WT technique in processing the noise-riding signals, this paper proposes a noise-suppression algorithm. The abilities of the WT in detecting and localizing the disturbances can hence be restored. Finally, this paper employed the actual data obtained from the practical power systems of Taiwan Power Company (TPC) to test the effectiveness of the developed de-noising scheme