基于BP网络的谐波干扰误差修正方法在介质损耗角测量中的应用研究
Harmonic Interference Error Correction Method Based on BP Neural Network for Dielectric Loss Angle Measurement

作者: 任明辉 * , 巨健 :宝鸡供电局电力调度控制中心,宝鸡;

关键词: 氧化锌避雷器介质损耗角BP神经网络Metal-Oxide Arresters Dielectric Loss Angle BP Neural Network

摘要:
介质损耗角计算精度是影响氧化锌避雷器绝缘在线监测系统性能的关键因素,本文针对谐波对氧化锌避雷器绝缘在线监测系统中的介质损耗角计算精度的影响,提出了一种基于BP网络的谐波干扰误差修正方法,即用BP网络来辨识电力系统中的三次、五次谐波含量与介质损耗角误差修正值Δδ之间的非线性关系,构建基于BP网络的介质损耗角修正模型,并通过该修正模型得出介质损耗角修正值Δδ,来对在线监测系统介质损耗角测量值进行修正,仿真研究和实验室试验结果表明,该方法对于抑制谐波干扰误差具有良好的效果。

Abstract:
The measurement precision of dielectric loss angle is a key factor of the performance of on-line monitoring system of metal-oxide arresters. The causes of data error of on-line insulating monitoring system for MOA are intro- duced in the paper. Questions about harmonic interference in on-line monitoring insulation system of MOA are stated. For the effect of harmonic interference in on-line monitoring insulation system, a harmonic interference error correction method based on BP neural network is presented for modifying dielectric loss angle. This method is used to identify the nonlinear relation between 3nd, 5th harmonic and dielectric loss angle modified value Δδ through BP network. Finally the adjusting dielectric loss angle model based on BP network is gained. The dielectric loss angle modified value Δδ, which can be got from the adjusting model, is used to modify the measured value of dielectric loss angle. The results from tests and simulation show that the two methods above-mentioned have a good result on eliminating harmonic interference error.

文章引用: 任明辉 , 巨健 (2013) 基于BP网络的谐波干扰误差修正方法在介质损耗角测量中的应用研究。 智能电网, 3, 101-105. doi: 10.12677/SG.2013.34018

参考文献

[1] 唐炬, 李剑, 苟海丰. 一种在线监测绝缘介质损耗的方法[J]. 重庆大学学报, 2001, 24(5): 111-115.

[2] 阎平凡, 张长水. 人工神经网络与模拟进化计算[M]. 北京: 清华大学出版社, 2000.

[3] A. Hoffmann. A methodological and computational analysis. Paradigms of Artificial Intelligence, Singapore: Springer, 1998.

[4] 张乃尧, 阎平凡. 神经网络与模糊控制[M]. 北京: 清华大学出版社, 1980.

[5] 张立明. 人工神经网络的模型及应用[M]. 上海: 复旦大学出版社, 1994.

[6] 袁曾任. 人工神经网络及其应用[M]. 北京: 清华大学出版社, 1990.

[7] M. T. Hagan, H. B. Demuth and M. Beale. Neural Network Design. Stamford: Thomson Learning, 1996.

[8] B. Widrow. Neural Networks Application in Industry. Business and Science, Communication of the ACM, 1994, 37: 93-105.

[9] 袁曾任. 人工神经元网络及其应用[M]. 北京: 清华大学出版社, 第三版, 1999.

[10] J. W. Han. 范明, 孟小峰译. 数据挖掘: 概念与技术[M]. 北京: 机械工业出版社, 2001.

[11] 楼顺天, 胡昌华, 张伟. 基于MATLAB的系统分析与设计—— 模糊系统[M]. 西安: 西安电子科技大学出版社, 2001.

[12] S. Chiu. Fuzzy model identification based on cluster estimation. Journal of Intelligent and Fuzzy Systems, 1994, 2(3): 267-278.

[13] R. Y. Ronald, P. F. Dimitar. Essentials of fuzzy modeling andcontrol. New York: John Wiley & Sons Inc., 1994.

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