scholarly journals Single-phase-to-ground fault detection with distributed parameters analysis in non-direct grounded systems

Author(s):  
Baowen Liu ◽  
◽  
Hongzhong Ma ◽  
Honghua Xu ◽  
Ping Ju ◽  
...  
1970 ◽  
Vol 1 (1) ◽  
Author(s):  
Yang Fan

The current distribution network single-phase ground fault detection model knowledge expression is poor, its production process only based on the normal distribution network sample data, no single-phase ground fault data, did not make full use of a prior knowledge, resulting in low detection accuracy. The automatic detection model of single-phase earth fault of new distribution network is proposed. The fault characteristic vector is taken as the input vector, and the degree of matching between the input vector and the weight vector element is introduced as the second layer. The fault vector is used as the input vector, and the fault vector is used as the input vector. Node input, the second layer of the output as the third layer of the input, the model training, the output of the results of the distribution network is a single-phase ground fault detection results. The experimental results show that the proposed model has high detection accuracy. 


2016 ◽  
Vol 818 ◽  
pp. 47-51
Author(s):  
Ahmad Rizal Sultan ◽  
Mohd Wazir Mustafa ◽  
Makmur Saini

This paper proposes an approach for the detection of the single line to ground fault on a unit generator-transformer, based on the extraction of statistical parameters from wavelet transform based neural network. In the simulation, the current and voltage signals were found decomposed over wavelet analysis into several approximations and details. The simulation of the unit generator-transformer was carried out using the Sim-PowerSystem Blockset of MATLAB. The statistical parameters analysis involved measurement of the dispersion factors (range and standard deviation) of wavelet coefficients. Regarding the pattern recognition of neural networks performance, the accuracy of SLG-fault detection of neural networks was 97.45 %. The results indicated that dispersion factor feature of wavelet transforms was accurate enough in distinguishing a single line to ground-fault and normal condition for a unit generator-transformer.


2019 ◽  
Vol 87 ◽  
pp. 264-271 ◽  
Author(s):  
Zhiwen Chen ◽  
Xueming Li ◽  
Chao Yang ◽  
Tao Peng ◽  
Chunhua Yang ◽  
...  

IEEE Access ◽  
2020 ◽  
pp. 1-1
Author(s):  
Na An ◽  
Hongchun Shu ◽  
Bo Yang ◽  
Pulin Cao ◽  
Jian Song ◽  
...  

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