基于BP神经网络和全相位快速傅里叶变换的电力系统谐波检测技术研究

摘要

On the basis of analyzing the available harmonic detection methods,the harmonic and interharmonic detection method based on all?phase fast Fourier transform and artificial neural network is studied. A new harmonic detection method based on all?phase fast Fourier transform and BP neural network is proposed to solve the problem of low harmonic detection pre?cision. And a harmonic detection method based on all?phase fast Fourier transform and adaptive neural network is used to further improve the accuracy of harmonic detection. A harmonic detection software based on all?phase fast Fourier transform and adap?tive neural network was designed on virtual instrument software development platform LabWindows/CVI. The software can realize the detection of harmonic amplitude and phase and calculation of total harmonic distortion,and give an alarm when the total har?monic distortion is out of limit.%在分析现有谐波检测方法的基础上，研究了基于全相位快速傅里叶变换和人工神经网络的谐波和间谐波检测算法。针对谐波检测精度不高的问题，提出了一种基于全相位快速傅里叶变换和BP神经网络的谐波检测方法，同时采用全相位快速傅里叶变换和自适应神经网络的谐波检测方法，进一步提高了谐波检测的精度。通过虚拟仪器软件开发平台LabWindows/CVI，设计了基于全相位快速傅里叶变换和自适应神经网络的谐波检测软件。软件实现了谐波幅值和相位的检测以及总谐波畸变率的计算，并能够在总谐波畸变率超标的情况下给出警报。