The Analysis Of Voltage Fluctuation And Flicker Based On Wavelet Transform

With the rapid development of global industrialization, power quality requirements are also increasing. Power electronics industry and Technological revolution has brought great convenience to people's lives, but also brought the voltage fluctuation and flicker and other issues, causing serious pollution to the power environment. For this reason, more and more scientists working in power are committed to the study of power quality.This paper briefly introduces the phenomenon of power disturbances and its harm caused by them, elaborates the definition,characteristics and causes of voltage fluctuation and flicker. On the basis of the current situation of domestic and foreign scholars for voltage fluctuation and flicker study, it describes several detection methods and theories that are currently used. the wavelet transform has time-frequency localization characteristics, which can detect the starting time and ending time of flicker signal to overcome the drawbacks of Fast Fourier transform(FFT), especially fit for mutation analysis of the signal, so wavelet transform is commonly used in the Analysis of voltage fluctuation and flicker. In order to solve the problem of the folded spectrum,this paper integrates the Discrete Fourier Transform(DFT), Inverse Discrete Fourier Transform(IDFT) and tower Mallat algorithm to form a new DFT-Mallat(DMallat) algorithm. By calculating DFT short-term flicker severitystP of comparative experiments, to some certain extent, it improves the detection accuracy of short-term flicker value to verify the reliability and validity of DMallat algorithm, thus indicating wavelet transform plays an important role in analysis of voltage fluctuation and flicker.Finally, it uses the BP network to fit the model of the relationship between the unit value of the instantaneous flicker frequency and the corresponding frequency sinusoidal voltage fluctuations in value. BP network has a good nonlinear function approximation and interpolation features, so it improves the fitting accuracy.