Corona Current De-Noising Method Based on Empirical Wavelet Transform

被引：0
|
作者：
Wang Q. [1 ]
Chen L. [1 ]
Yuan H. [1 ]
Liu Y. [2 ]
Liu Y. [2 ]
机构：
[1] School of Automation Science and Electrical Engineering, Beihang University, Haidian District, Beijing
[2] China Electric Power Research Institute, Haidian District, Beijing
来源：
Dianwang Jishu/Power System Technology | 2017年 / 41卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Corona current; Empirical wavelet transform; Noise suppression; Ultra-high voltage direct current transmission;
D O I：
10.13335/j.1000-3673.pst.2016.1230
中图分类号：
学科分类号：
摘要：
With increase of transmission voltage level and transmission distance, power loss and environmental problems caused by corona current on UHV DC transmission line become more serious. Detailed analysis of corona current is of great importance for suppressing corona effects and achieving efficient large-scale power transmission. Complexity of corona current leads to difficulties in analysis of time and frequency characteristics. This paper proposes an empirical wavelet transform (EWT) based de-noising method for corona current. Firstly, piecewise EWT is proposed for practically measured overlong corona current. Secondly, local maximum searching method is improved according to spectral characteristics of corona current. Finally, de-noised corona current is reconstructed based on decomposition result of piecewise EWT. Experimental results show that the proposed method suppresses various noise components of the measured corona current with different voltage levels effectively and realizes efficient overlong corona data processing. This paper provides a new method for corona current research and offers theoretical and technical support for accurate power loss calculation and exploration of corona discharge rules. © 2017, Power System Technology Press. All right reserved.
引用
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页码：670 / 676
页数：6
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