DWT-based Denoising and Power Quality Disturbance Detection

Muhammad Ramzan; Sangho Choe

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IEIE Transactions on Smart Processing & Computing 학술저널
IEIE Transactions on Smart Processing & Computing Vol.4 No.5
2015.10 330 - 339 (10page)

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Muhammad Ramzan (The Catholic University of Korea)
Sangho Choe (The Catholic University of Korea)

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Power quality (PQ) problems are becoming a big issue, since delicate complex electronic devices are widely used. We present a new denoising technique using discrete wavelet transform (DWT), where a modified correlation thresholding is used in order to reliably detect the PQ disturbances. We consider various PQ disturbances on the basis of IEEE-1159 standard over noisy environments, including voltage swell, voltage sag, transient, harmonics, interrupt, and their combinations. These event signals are decomposed using DWT for the detection of disturbances. We then evaluate the PQ disturbance detection ratio of the proposed denoising scheme over Gaussian noise channels. Simulation results also show that the proposed scheme has an improved signal-to-noise ratio (SNR) over existing scheme.

#Discrete wavelet transform (DWT) #Power quality disturbances #Thresholding #Denoising #Detection