scholarly journals Study on Fault Location in the T-Connection Transmission Lines Based on Wavelet Transform

2015 ◽  
Vol 03 (03) ◽  
pp. 106-115
Author(s):  
Penggao Wen ◽  
Hong Song ◽  
Zhiting Guo ◽  
Quan Pan
Keyword(s):  
Wavelet Transform ◽  
Transmission Lines ◽  
Fault Location

scholarly journals Fault simulation in networks with isolated neutral to find the fault location in power transmission lines

2021 ◽  
Vol 2131 (3) ◽  
pp. 032045
Author(s):  
I V Belitsyn ◽  
M I Pestov ◽  
I A Pavlichenko ◽  
A I Belitsyn
Keyword(s):  
Wavelet Transform ◽  
Transmission Lines ◽  
Fault Location ◽  
Power Transmission ◽  
Fault Simulation ◽  
Time Interval ◽  
Temporal Position ◽  
Power Transmission Lines ◽  
Neutral Mode ◽  
Isolated Neutral

Abstract The paper deals with an urgent problem - determining the location of damage to an overhead power transmission line. In particular, the application of the wavelet transform is considered, which makes it possible to localize the temporal position of the frequencies and to determine the time interval of the presence of the frequency in the event of damage to the power line. The paper presents a mathematical model that makes it possible to determine the amplitude-frequency spectrum, by which it is possible to determine the presence of a certain frequency in the signal under study, by which it is possible to determine the fault location. Based on the wavelet transform, the spectra of the current and voltage in the damaged phase in the isolated neutral mode are obtained. It is shown that when the neutral mode is switched, there are no dangerous overvoltage or current surges in the network, and the overvoltage level is reduced.

Detecting faults in VSC-HVDC systems by deep learning and K-means

2020 ◽  
Vol 13 ◽  
Author(s):  
Roohollah Sadeghi Goughari ◽  
Mehdi Jafari Shahbazzadeh ◽  
Mahdiyeh Eslami
Keyword(s):  
Signal Processing ◽  
Deep Learning ◽  
Wavelet Transform ◽  
Transmission Lines ◽  
Fault Location ◽  
Learning Algorithm ◽  
Hvdc Transmission ◽  
Deep Learning Algorithm ◽  
Processing Techniques ◽  
Signal Processing Techniques

Background: In this paper, two methods and their comparison used to determine the fault locaton in VSC-HVDC transmission lines. Fast and reliable control are features of these systems. Methods: Additionally, wavelet transform from advanced techniques of signal processing is employed for the purpose of extracting important characteristics of fault signal from both sides of the line by PMU. To do so, Deep learning is used to identify the relation between the extracted features from wavelet analysis of the fault current and variations under fault conditions. As such, wavelet transform and advanced signal processing techniques are used to extract important features of fault signal from both sides of the line by the PMU. Results: The results show the high accuracy of finding fault location by the deep learning algorithm method compared to the k-means algorithm with an error rate of <1%. Conclusion: Studies on the 50 kV VSC-HVDC transmission line with a length of 25 km in MATLAB have been simulated.

A Novel Fault-location Method for HVDC Transmission Lines Based on Concentric Relaxation Principle and Wavelet Packet

2020 ◽  
Vol 13 (5) ◽  
pp. 705-716
Author(s):  
Congshan Li ◽  
Ping He ◽  
Feng Wang ◽  
Cunxiang Yang ◽  
Yukun Tao ◽  
...  
Keyword(s):  
Transmission Lines ◽  
Traveling Wave ◽  
Fault Location ◽  
Wave Attenuation ◽  
Wavelet Packet ◽  
Low Frequency ◽  
Evaluation Process ◽  
Location Method ◽  
Hvdc Transmission ◽  
Instantaneous Energy

Background: A novel fault location method of HVDC transmission line based on a concentric relaxation principle is proposed in this paper. Methods: Due to the different position of fault, the instantaneous energy measured from rectifier and inverter are different, and the ratio k between them is the relationship to the fault location d. Through the analysis of amplitude-frequency characteristics, we found that the wave attenuation characteristic of low frequency in the traveling wave is stable, and the amplitude of energy is larger, so we get the instantaneous energy ratio by using the low-frequency data. By using the method of wavelet packet decomposition, the voltage traveling wave signal was decomposed. Results: Finally, calculate the value k. By using the data fitting, the relative function of k and d can be got, that is the fault location function. Conclusion: After an exhaustive evaluation process considering different fault locations, fault resistances, and noise on the unipolar DC transmission system, four-machine two-area AC/DC parallel system, and an actual complex grid, the method presented here showed a very accurate and robust behavior.

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