[1]都洪基,苏炜宏,邓烽.一种基于神经网络的谐波电流抑制方法[J].南京理工大学学报(自然科学版),2003,(01):28-32.
 DuHongji SuWeihong DengFeng.Adaptive Approach to Detection of the Harmonic Currents on Artificial Neural Network[J].Journal of Nanjing University of Science and Technology,2003,(01):28-32.
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一种基于神经网络的谐波电流抑制方法()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
期数:
2003年01期
页码:
28-32
栏目:
出版日期:
2003-02-28

文章信息/Info

Title:
Adaptive Approach to Detection of the Harmonic Currents on Artificial Neural Network
作者:
都洪基苏炜宏邓烽
南京理工大学动力工程学院, 南京210094
Author(s):
DuHongji SuWeihong DengFeng
School of Power Engineering,NUST,Nanjing 210094
关键词:
神经网络 谐波 有源滤波器
Keywords:
neural netw ork harmonic w aves act ive f ilter
分类号:
TM761
摘要:
在传统谐波注入法基础上提出一种神经网络自适应谐波电流抑制方法 ,根据自适应噪声抵消技术运用人工神经网络的自适应和自学习特性检测出谐波电流并注入电力系统 ,达到抑制谐波的目的。通过对一典型正弦电流的仿真研究结果表明 ,该方法是可行和有效的 ,它不但有较高的检测精度 ,而且能跟踪检测 ,根据环境的变化能自适应地调整神经网络的权值 ,以便正确地检测出线路的谐波电流
Abstract:
An adaptive approach to detection of the harmonic currents based on the classical w ay of harmonic injection and artificial neural network is presented in this paper. The ANN has teo orthogonal inputs and its weights are adjusted through BP algorithms, its output can vary adaptively with the input. The results obtained from simulation on a typical sine wave show that the approach is feasible and effective. It can detect and track the harmonic currents accurately, for it can adjust the weights of artificial neural network with sett ing.

参考文献/References:

1 Akag i H. Instantaneous react ive power compensators compr ising sw itching dev ice w ithout energy storage components[ J] . IEEE Trans Industry Applications, 1984, 20( 3) : 625~ 633.
2 袁曾任. 人工神经网络及其应用[M] . 北京: 清华大学出版社, 1999.
3 杨行峻, 郑君里. 人工神经网络[ M]1 北京: 高等教育出版社, 1992.
4 Widrow B. Adaptive signal processing[M] . New Jersey: Prntice Hall, Englewood Cliffis, 1985. 5 钱照明, 叶忠明, 董伯 . 谐波抑制技术[ J] . 电力系统自动化, 1997, 21( 10) : 48~ 54.
6 郝晓弘, 张明光, 侯景阳. 电力系统高次谐波的危害及抑制方法[ J] . 甘肃工业大学学报, 1998, 24( 3) : 79~ 84.
7 任元, 陈宝喜. 电网各种电压等级的谐波电压[ J] . 中国电力, 1994( 10) : 7~ 10.

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备注/Memo

备注/Memo:
都洪基 男 47 岁 高级工程师
更新日期/Last Update: 2013-03-17