Keywords: denoising, discrete wavelet transform, power quality monitoring, voltage disturbances, power system disturbances, wavelets, simulation, transient disturbances, voltage sags, voltage swells, short-time interruptions, low-frequency transients, harmonics
Characterisation of power quality disturbances based on wavelet transforms
This paper presents a new technique for detecting and characterising disturbances in power systems based on wavelet transforms. The voltage signal under investigation is often corrupted by noises, therefore the voltage signal is first denoised using wavelet thresholding and then wavelet transform is applied to the denoised signal. Using the first-level detail wavelet coefficients, the voltage disturbance is detected and its duration is determined. The voltage disturbances are classified and its magnitude are determined using the root mean square of the approximation wavelet coefficients calculated over a half-cycle window. To test the developed scheme, diverse data obtained from MATLAB for different types of transient disturbances, voltage sags, voltage swells, short-time interruptions, and low-frequency transients are employed. Simulation results show that the proposed method is fast and accurate. Furthermore, remarkable efficiency in monitoring the power quality problems and high tolerance to the noises are approved.