基于Slepian和Parzen互卷积窗插值FFT的电力系统谐波分析方法

摘要：谐波是电力系统中最为突出的电能质量问题之一。谐波参数的准确估计是电力企业和用户评价电能质量的重要参考依据。目前，电网谐波参数的估计方法主要基于傅里叶变换算法，但该算法在分析和处理信号时需要对原始信号进行截断和离散化处理，会不可避免的导致频谱泄露和栅栏效应，从而严重影响电网谐波参数的准确测量。而具有优良旁瓣特性的窗函数以及插值算法可有效改善因频谱泄露和栅栏效应所带来的参数估计误差。为此，本文提出一种基于Slepian窗和Parzen窗的新型互卷积窗（SPMCW）插值FFT的谐波分析方法。SPMCW具有较低的旁瓣电平和快速的旁瓣衰减速率，因而可有效抑制频谱泄露，进而实现弱谐波幅值的检测。在MATLAB下的仿真实验验证了本文算法的准确性和可靠性。实际构建的硬件平台验证了算法的有效性和可行性。

Slepian and Parzen mutual convolution window-based interpolation FFT for harmonic analysis method in power system

Abstract: Harmonic is one of the most serious power quality problems in power system. Accurate estimation of harmonic parameters is an important reference for power enterprises and users to evaluate power quality. The estimation method of power grid harmonic parameters is mainly based on Fourier transform algorithm. However, the algorithm needs to truncate and discretize the original signal when analyzing and processing the signal, which will inevitably lead to spectrum leakage and fence effect.This will seriously affect the accurate measurement of power grid harmonic parameters. The window function with excellent side lobe characteristics and interpolation algorithm can effectively reduce the parameter estimation errors caused by spectrum leakage and fence effect. Therefore, this paper proposes a Slepian window and Parzen window mutual convolution window (SPMCW) with interpolation FFT for power system harmonic analysis. SPMCW has the advantages of low sidelobe level and fast sidelobe decay rate which can effectively suppress the spectrum leakage and realize the detection of weak harmonic amplitudes. The simulation experiments in MATLAB verify the accuracy and reliability of the algorithm. The actual hardware platform verifies the effectiveness and feasibility of the algorithm.