Power system harmonic detection based on cubic spline function and Rife-vincent self-convolution window interpolation FFT algorithm

Abstract

When using the Fast Fourier Transform(FFT) to perform harmonic analysis on power systems, due to asynchronous sampling and data truncation, fence effect and spectrum leakage will occur, and accurate harmonic parameters cannot be obtained. In order to improve the accuracy of harmonic detection of asynchronous sampling, this paper proposes a Rife-vincent self-convolution window interpolation FFT algorithm based on cubic spline function. The Rife-vincent self-convolution window has low peak value and fast sidelobe attenuation, which can effectively suppress spectral leakage. The cubic spline function is used to approximate the amplitude ratio function, which can effectively suppress the fence effect and avoid solving high-order equations. The calculation accuracy is high. Through MATLAB simulation analysis, it is verified that the Rife-vincent self-convolution window interpolation FFT algorithm based on cubic spline function can effectively suppress spectrum leakage and fence effect and improve harmonic detection accuracy.

Keywords

• harmonic analysis
• rife-vincent self-convolution window
• cubic spline function
• spectrum leakage
• fence effect