基于APFFT和神经网络的谐波检测方法

X. Zhu, Changguo Shen, X. Ren
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引用次数: 6

摘要

提出了一种基于全相位FFT (APFFT)和人工神经网络(ANN)的电力系统整数谐波和非整数谐波检测新算法。为了提高谐波参数估计的精度,该方法将APFFT的相不变性与高速寻优求解函数相结合。首先,对采样数据进行加窗APFFT算法处理,得到谐波参数,包括谐波个数、谐波的准确相位、谐波的不准确幅值和频率。其次,根据APFFT分析结果,设置神经网络的节点个数、初始权值和基函数的迭代初始参数;最后,通过训练人工神经网络得到准确的谐波参数。仿真结果表明,该方法具有较高的谐波参数检测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Harmonic Detection Method Using APFFT and Neural Network
A new algorithm, which utilizes all-phase FFT (APFFT) and artificial neural network (ANN), is presented to detect integer harmonics and non-integer harmonics in power system. In order to improve the accuracy of harmonic parameter estimation, the method incorporates the property of phase invariant of APFFT with high speed sought optimization solution function of ANN. First, the sampled data is processed by windowed APFFT algorithm, and then some of harmonic parameters can be obtained, including the number of harmonics, accurate phases of harmonics, inaccurate magnitudes and frequencies of harmonics. Second, the number of neural nodes, the initial weights and the iterative initial parameters of base function of neural network are set according to the results analyzed with APFFT. Finally, accurate harmonic parameters can be obtained by training ANN. Simulation results demonstrate that the method can detect harmonic parameters with high precision.
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