Abstract
The current signal harmonic detection method(s) cannot reduce the errors in the analysis and extraction of mixed harmonics in the power grid. This paper designs a harmonic detection method based on discrete Fourier transform (DFT) and discrete wavelet transform (DWT) using Bartlett–Hann window function. It improves the detection accuracy of the existing methods in the low frequency steady-state part. In addition, it also separates the steady harmonics from the attenuation harmonics of the high frequency part. Simulation results show that the proposed harmonic detection method improves the detection accuracy of the steady-state part by 1.5175% compared to the existing method. The average value of low frequency steady-state amplitude detection of the proposed method is about 95.3375%. At the same time, the individual harmonic components of the signal are accurately detected and recovered in the high frequency part, and separation of the steady-state harmonics and the attenuated harmonics is achieved. This method is beneficial to improve the ability of harmonic analysis in the power grid.
Highlights
In recent years, as the smart grid enters the comprehensive construction stage, more and more power electronic equipment is put into operation
This paper designs an improved method based on discrete Fourier transform (DFT) and discrete wavelet transform (DWT) using Bartlett–Hann window function hybrid detection
The interpolation DFT and DWT mixed harmonic detection methods based on the Hanning window function can restore the attenuated harmonic components through layering
Summary
As the smart grid enters the comprehensive construction stage, more and more power electronic equipment is put into operation. Among these power electronic devices, there are devices with nonlinear impedance characteristics, such as rectifiers, inverters, and phase speed control and voltage regulation devices. The use of non-linear power electronic equipment generates a lot of harmonic pollution, which causes significant voltage and current distortions and severely affects power quality. Accurate harmonic detection is of great significance for improving power quality and ensuring the reliability and safety of a power system [1,2]. The earliest harmonic measurements were achieved by analog filtering methods, which are very sensitive to the parameters of circuit components. It is difficult to obtain ideal amplitude frequency and phase frequency characteristics, with large errors and poor real-time performance [3]
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