Research Situation Analysis of On-line Detection Technology for Power Transformer Winding Deformation

2020 ◽  
Vol 13 (6) ◽  
pp. 823-832
Author(s):  
Zhenhua Li ◽  
Weihui Jiang ◽  
Li Qiu ◽  
Zhenxing Li ◽  
Yanchun Xu
Keyword(s):  
Detection Method ◽  
Theoretical Research ◽  
Line Detection ◽  
Response Analysis ◽  
Advantages And Disadvantages ◽  
Detection Technology ◽  
The Future ◽  
Transformer Winding ◽  
On Line ◽  
Winding Deformation

Background: Winding deformation is one of the most common faults in power transformers, which seriously threatens the safe operation of transformers. In order to discover the hidden trouble of transformer in time, it is of great significance to actively carry out the research of transformer winding deformation detection technology. Methods: In this paper, several methods of winding deformation detection with on-line detection prospects are summarized. The principles and characteristics of each method are analyzed, and the advantages and disadvantages of each method as well as the future research directions are expounded. Finally, aiming at the existing problems, the development direction of detection method for winding deformation in the future is prospected. Results: The on-line frequency response analysis method is still immature, and the vibration detection method is still in the theoretical research stage. Conclusion: The ΔV − I1 locus method provides a new direction for on-line detection of transformer winding deformation faults, which has certain application prospects and practical engineering value.

Transformer Winding on-Line Monitoring and Diagnosis Using Current Source Method

2013 ◽  
Vol 291-294 ◽  
pp. 2272-2277
Author(s):  
Li Peng Liu ◽  
Yong Li Zhu ◽  
Guo Qiang Wang
Keyword(s):  
Frequency Response ◽  
Current Source ◽  
Response Analysis ◽  
Current Frequency ◽  
Monitoring And Diagnosis ◽  
Source Method ◽  
Transformer Winding ◽  
On Line ◽  
Winding Deformation ◽  
Response Method

Transformer winding deformation is a main type of transformer fault. The Frequency Response Analysis is a effective method to detect transformer winding deformation. Based on the traditional Frequency Response Method, the current source method is a new way to detect winding deformation. This method adopts the current source as sweep frequency source and uses the current frequency response curve to judge winding deformation. The simulation shows that the current source method is feasible. For some special transformers, this method can realize transformer winding on-line monitoring and diagnosis.

scholarly journals Optimization of Transformer Winding Deformation Assessment Criterion Considering Insulation Aging and Moisture Content

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6491
Author(s):  
Qian Wu ◽  
Yizhuo Hu ◽  
Ming Dong ◽  
Bo Song ◽  
Changjie Xia ◽  
...  
Keyword(s):  
Moisture Content ◽  
Frequency Response ◽  
High Sensitivity ◽  
Response Analysis ◽  
Frequency Response Analysis ◽  
Response Curves ◽  
Insulation Aging ◽  
Transformer Winding ◽  
Winding Deformation ◽  
Paper Insulation

Frequency response analysis is widely used to diagnose transformer winding deformation faults due to its high sensitivity, strong anti-interference capability, and equipment portability, but the results of frequency response analysis can be affected by insulation aging and moisture in the transformer, leading to errors in the diagnosis of winding deformation faults. Currently, there is no effective method to prevent such errors. This paper focuses on optimizing the criterion for diagnosing winding deformations when insulation aging and moisture are present. First, the winding frequency response curves of oil-paper insulation were determined by combining insulation aging and moisture tests of the oil-paper insulation with frequency response simulations of the transformer winding. Next, the winding deformation criterion predicting the likelihood and extent of errors diagnosing transformer winding deformations due to the insulation aging and moisture content is discussed. Finally, the corresponding criterion optimization method is proposed. The corresponding results show that insulation aging and moisture can lead to errors when using the correlation coefficient R criterion to diagnose the transformer winding deformations. Moreover, the possibility of winding deformation errors caused by the change of insulation state can be reduced by introducing the corresponding auxiliary criterion through comparing the capacitance change rate based on the frequency response method and that based on the dielectric spectrum method.

scholarly journals A transformer winding deformation detection method based on the analysis of leakage inductance changes

2015 ◽  
Vol 64 (2) ◽  
pp. 333-346
Author(s):  
Li Jiansheng ◽  
Tao Fengbo ◽  
Wei Chao ◽  
Lu Yuncai ◽  
Wu Peng ◽  
...  
Keyword(s):  
Measurement Errors ◽  
Detection Method ◽  
Time Window ◽  
Short Circuit ◽  
Normal Function ◽  
Random Fluctuation ◽  
Least Squares Regression ◽  
Leakage Inductance ◽  
Transformer Winding ◽  
Winding Deformation

Abstract The detection of transformer winding deformation caused by short-circuit current is of great significance to the realization of condition based maintenance. Considering the influence of environment and measurement errors, an online deformation detection method is proposed based on the analysis of leakage inductance changes. First, the operation expressions are derived on the basis of the equivalent circuit and the leakage inductance parameters are identified by the partial least squares regression algorithm. Second, the amount of the leakage inductance samples in a detection time window is determined using the Monte Carlo simulation thought, and then the samples in the confidence interval are obtained. Last, a criteria is built by the mean value changes of the leakage inductance samples and the winding deformation is detected. The online detection method considers the random fluctuation characteristics of the leakage inductance samples, adjust the threshold value automatically, and can quantify the change range to assess the severity. Based on the field data, the distribution of the leakage inductance samples is analyzed to obey the normal function approximately. Three deformation experiments are done by different sub-winding connections and the detection results verify the effectiveness of the proposed method

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