摘要
为提高用于有源电力滤波器APF(active power filter)的谐波电流检测的性能,提出一种基于自适应神经网络的谐波电流检测方法。根据自适应噪声对消技术的基本原理,将基波电流从负载电流中滤除从而得到谐波电流。该方法能实时准确地检测出谐波,很好地弥补基于FFT方法、基于瞬时无功理论方法和基于小波变换方法等检测方法的缺陷。MATLAB/Simulink仿真结果证明该方法的实时性和准确性,可用于APF的谐波电流检测。
A novel harmonic current detection method based on the adaptive neural networks is proposed in this paper to improve the performance of active power filter（APF）＇s harmonic curent detection. According to the basic principle of adaptive noise cancelling technology, the harmonic current is obtained after the fundamental current is filtered from the load current. This method can accurately and fast detect harmonic current and well overcome the shortages of those detection methods based on FFT, the instantaneous reactive power theory and the wavelet transform. Simulation results based on MATLAB/Simulink testify the real-timing and accuracy of the method. So the method proposed in this paper can be used as the harmonic current detection of APF.
出处
《电力系统及其自动化学报》
CSCD
北大核心
2010年第3期46-49,101,共5页
Proceedings of the CSU-EPSA
基金
教育部科学技术研究重大项目(306004)
关键词
有源电力滤波器
人工神经网络
自适应噪声对消技术
谐波电流检测
active power filter（APF）
artificial neural networks
adaptive noise cancelling technology
harmonic current detection
