Discrimination of Inrush Current at Inconsistent Saturation Level and Fault Current Using Wavelet Transform Technique

2019 ◽  
Author(s):  
Shweta Kadam ◽  
Bhoopesh Chaudhry
Keyword(s):  
Wavelet Transform ◽  
Saturation Level ◽  
Inrush Current ◽  
Fault Current

scholarly journals Wavelet Transform Implementation to Differentiate Inrush Current and Fault Current in Power Transformer

2020 ◽  
Vol 8 (5) ◽  
pp. 3041-3044
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
Fast Fourier Transform ◽  
Power Transformer ◽  
Normal Faults ◽  
Inrush Current ◽  
Fault Current ◽  
Electrical System ◽  
Protection Circuit ◽  
Internal Faults

An electrical system is al complex network, to enhance power generation, transmission and distribution transformers play an important role. Power transformer is the heart of the electrical system. Even though electrical power is generated at lower rate in the coastal areas, it can be transmitted easily over hundreds of kilometer with the help of power transformer. So there must proper protection should given to power transformers. But in order to give the proper protection there should be proper discrimination between internal faults and inrush current. If there is no proper differentiation between faults and inrush current phenomena than the protection circuit will not trip when inrush current comes into the picture. But the protection circuit will trip at faster rate than the actual one when the normal faults or internal faults come into the picture. So there should be proper discrimination between inrush current and internal fault current so that the protection circuit will work properly. There are so many techniques available to get differentiation between inrush current and fault current. Fast Fourier transform is one of the method to differentiate between these two currents. Here we are using wavelet transform technique to get the difference between these two currents. The properties of the inrush current obtained from this technique are accurate and distinct from those obtained from the fast Fourier transform. The experimental set up is carried out in matlab simulink and results were discussed as shown below in results.

scholarly journals A Method for Identification of Transformer Inrush Current Based on Box Dimension

2017 ◽  
Vol 2017 ◽  
pp. 1-6
Author(s):  
Maofa Gong ◽  
Ran Zheng ◽  
Linyuan Hou ◽  
Jingyu Wei ◽  
Na Wu
Keyword(s):  
Fundamental Difference ◽  
Box Dimension ◽  
Inrush Current ◽  
Fault Current ◽  
Differential Protection ◽  
Phase Current ◽  
Magnetizing Inrush Current ◽  
Three Phase ◽  
Transformer Differential Protection ◽  
Box Dimensions

Magnetizing inrush current can lead to the maloperation of transformer differential protection. To overcome such an issue, a method is proposed to distinguish inrush current from inner fault current based on box dimension. According to the fundamental difference in waveform between the two, the algorithm can extract the three-phase current and calculate its box dimensions. If the box dimension value is smaller than the setting value, it is the inrush current; otherwise, it is inner fault current. Using PSACD and MATLAB, the simulation has been performed to prove the efficiency reliability of the presented algorithm in distinguishing inrush current and fault current.

New Method to Identify Transformer Inrush Current Based on FFT and SVM

2013 ◽  
Vol 313-314 ◽  
pp. 887-890
Author(s):  
Mao Fa Gong ◽  
Guo Liang Li ◽  
Wen Hua Xia ◽  
Hong Lin Yan ◽  
Jing Wen Qu ◽  
...  
Keyword(s):  
Cross Validation ◽  
Accurate Method ◽  
High Accuracy ◽  
Generation Mechanism ◽  
New Method ◽  
Inrush Current ◽  
Fault Current ◽  
Third Harmonic ◽  
Internal Fault ◽  
Three Phase

To improve transformer longitudinal differential protections reliability, this paper deeply analyzes generation mechanism and characteristic of transformer inrush current, and uses PSCAD/EMTDC software to simulate 188 kinds of transformer operation states. They are including internal fault current, inrush current and no-load closing with internal fault. On the background of those simulations, it proposes a simple and accurate method to identify inrush current based on SVM. SVM selects Gaussion Kernel, and takes three-phase differential current, fundamental, secondary harmonic and third harmonic as characteristic quantities. Many cross-validation results verify that the training SVM has high accuracy. This method can identify inrush current and internal fault current (including no-load closing with internal fault current) rapidly and accurately. It takes less time, and is easy to perform.

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