Characteristic Extraction and Assessment Methods for Transformers DC Bias Caused by Metro Stray Currents

被引:0
作者
Wang, Aimin [1 ]
Lin, Sheng [2 ]
Wu, Guoxing [3 ]
Li, Xiaopeng [4 ]
Wang, Tao [1 ]
机构
[1] Xihua Univ, Sch Elect Engn & Elect Informat, Chengdu 610039, Peoples R China
[2] Southwest Jiaotong Univ, Sch Elect Engn, Chengdu 611756, Peoples R China
[3] Shenzhen Power Supply Bureau Co Ltd, China Southern Power Grid, Shenzhen 518000, Peoples R China
[4] State Grid Sichuan Elect Power Res Inst, Chengdu 610044, Peoples R China
基金
中国国家自然科学基金;
关键词
metrostray current; transformers DC bias; characteristic extraction; risk assessment; neutral DC; vibration;
D O I
10.3390/e26070595
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Metro stray currents flowing into transformer-neutral points cause the high neutral DC and a transformer to operate in the DC bias state.Because neutral DC caused by stray current varies with time, the neutral DC value cannot be used as the only characteristic indicator to evaluate the DC bias risk level. Thus, unified characteristic extraction and assessment methods are proposed to evaluate the DC bias risk of a transformer caused by stray current, considering the signals of transformer-neutral DC and vibration. In the characteristic extraction method, the primary characteristics are obtained by comparing the magnitude and frequency distributions of transformer-neutral DC and vibration with and without metro stray current invasion. By analyzing the correlation coefficients, the final characteristics are obtained by clustering the primary characteristics with high correlation. Then, the magnitude and frequency characteristics are extracted and used as indicators to evaluate the DC bias risk. Moreover, to avoid the influence of manual experience on indicator weights, the entropy weight method (EWM) is used to establish the assessment model. Finally, the proposed methods are applied based on the neutral DC and vibration test data of a certain transformer. The results show that the characteristic indicators can be extracted, and the transformer DC bias risk can be evaluated by using the proposed methods.
引用
收藏
页数:11
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