scholarly journals Precise Fault Location Detection Using IOT

2021 ◽  
pp. 74-79
Author(s):  
Prof. Sayyad Naimuddin ◽  
Prof. Nahid Khan ◽  
Vaishali Gupta ◽  
Tuba Farhat ◽  
Deepak Singh Mujeebuddin Ansari ◽  
...  
Keyword(s):  
Transmission Lines ◽  
Power Dissipation ◽  
Fault Location ◽  
Electrical Power ◽  
Precise Location ◽  
Human Errors ◽  
Location Detection ◽  
Short Circuits ◽  
To Come ◽  
Transmission And Distribution

Transmission and distribution lines are used to transmit and distribute electrical power throughout load center. The problem with these lines are, because the loads are unbalanced and their attraction towards various faults as a results of lightning, short circuits, faulty equipment’s, miss-operation, human errors, overload, and aging. To avoid this case and that we need the precise location of fault occurrence. To avoid this situation, we need the exact location of fault occurrence. This problem is handled by a set of resistors representing cable length in KMs and fault creation is made by a set of switches at every known KM to cross check the accuracy of the same. Only way to solve this problem is to come up with a mechanism that can detect the fault in an electricity transmission line automatically and intimate the authorities with a precise location. Through this project we develop a device that uses sensors to sense the incoming & outgoing values and detect healthy and faulty condition. And, the system will be integrated with IoT mechanism, to intimate the responsible people real time with the location information. Moreover technical losses occur naturally and are caused because of power dissipation in transmission lines, transformers, and other equipments. The system prevents the illegal usage of electricity.

scholarly journals Development of the method of determining the location of a short circuit in transmission lines

2021 ◽  
Vol 2061 (1) ◽  
pp. 012033
Author(s):  
K Suslov ◽  
N Solonina ◽  
Z Solonina ◽  
A Akhmetshin
Keyword(s):  
Transmission Lines ◽  
Fault Location ◽  
Short Circuit ◽  
Search Time ◽  
Distribution Networks ◽  
Power Lines ◽  
Supply And Distribution ◽  
Short Circuits ◽  
Reliable Power Supply ◽  
Short Time

Abstract One of the serious problems of the reliable functioning of energy systems is the disruption of the performance of overhead and cable transmission power lines caused by various reasons. Most of the power outages occur in distribution networks. Particularly dangerous short-circuits in the supply and distribution network, due to unpredictable natural disasters. To ensure uninterrupted and reliable power supply to consumers, it is necessary to identify and eliminate the malfunction in a short time to reduce damage. Finding and troubleshooting a line is an important task. The authors proposed a method for quickly determining the location of a short circuit in power lines. The proposed method allows to reduce search time and increase the accuracy of determining the fault location.

Gradient Ascent Optimization for Fault Detection in Electrical Power System Based on Wavelet Transformation

2019 ◽  
Vol 14 ◽  
Author(s):  
Iyappan Murugesan ◽  
Karpagam Sathish
Keyword(s):  
Feature Extraction ◽  
Fault Detection ◽  
Power System ◽  
Electrical Power ◽  
Daubechies Wavelet ◽  
Electrical Power System ◽  
Gradient Ascent ◽  
Neural Learning ◽  
Weight Value ◽  
Transmission And Distribution

: This paper presents electrical power system comprises many complex and interrelating elements that are susceptible to the disturbance or electrical fault. The faults in electrical power system transmission line (TL) are detected and classified. But, the existing techniques like artificial neural network (ANN) failed to improve the Fault Detection (FD) performance during transmission and distribution. In order to reduce the power loss rate (PLR), Daubechies Wavelet Transform based Gradient Ascent Deep Neural Learning (DWT-GADNL) Technique is introduced for FDin electrical power sub-station. DWT-GADNL Technique comprises three step, normalization, feature extraction and FD through optimization. Initially sample power TL signal is taken. After that in first step, min-max normalization process is carried out to estimate the various rated values of transmission lines. Then in second step, Daubechies Wavelet Transform (DWT) is employed for decomposition of normalized TLsignal to different components for feature extraction with higher accuracy. Finally in third step, Gradient Ascent Deep Neural Learning is an optimization process for detecting the local maximum (i.e., fault) from the extracted values with help of error function and weight value. When maximum error with low weight value is identified, the fault is detected with lesser time consumption. DWT-GADNL Technique is measured with PLR, feature extraction accuracy (FEA), and fault detection time (FDT). The simulation result shows that DWT-GADNL Technique is able to improve the performance of FEA and reduces FDT and PLR during the transmission and distribution when compared to state-of-the-art works.

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.

Fault location on transmission lines based on travelling waves using correlation and MODWT

2021 ◽  
Vol 197 ◽  
pp. 107308
Author(s):  
V.H. Gonzalez-Sanchez ◽  
V. Torres-García ◽  
D. Guillen
Keyword(s):  
Transmission Lines ◽  
Fault Location ◽  
Travelling Waves

Digital fault location for high resistance grounded transmission lines

1999 ◽  
Vol 14 (1) ◽  
pp. 80-85 ◽  
Author(s):  
T. Funabashi ◽  
H. Otoguro ◽  
Y. Mizuma ◽  
T. Kai ◽  
N. Takeuchi ◽  
...  
Keyword(s):  
High Resistance ◽  
Transmission Lines ◽  
Fault Location

scholarly journals Non-contact fault location and identification method for same-tower multi-circuit transmission lines

2021 ◽  
Vol 7 ◽  
pp. 147-158
Author(s):  
Tao Yin ◽  
Jian Li ◽  
Dongsheng Cai ◽  
Qi Huang ◽  
Weihao Hu
Keyword(s):  
Transmission Lines ◽  
Fault Location ◽  
Identification Method
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