scholarly journals Single line to ground fault detection and location in medium voltage distribution system network based on neural network

2021 ◽  
Vol 23 (2) ◽  
pp. 621
Author(s):  
Ahmed K. Abbas ◽  
Sumaya Hamad ◽  
Nuha A. Hamad
Keyword(s):  
Neural Network ◽  
Transmission Lines ◽  
Distribution System ◽  
Electromagnetic Transients ◽  
Single Line ◽  
Ground Failure ◽  
Medium Voltage ◽  
Ground Fault ◽  
The Neural Network ◽  
The Waves

<p>The aim of this project was to detect and locate the single ground failure lines that occurs in medium voltage (MV) networks on the transmission lines (TL). Compared with anther faults, single line-to-ground (SLG) is the most frequent. The neural network (NN) algorithm was advanced in order to discover and locate SLG faults. The network is simulated through simulated numerous defects at various locations, as well as changing earth resistance from (or 100 Ω) to TL to gather all of the data. In the electromagnetic transients’ program (EMTP) program software, the existing fault have been measured. In addition, the waves were evaluated by utilize MATLAP's fastfourier-transform to calculate the waves of top three of them, On the MV network are fifty hundred faults are simulated all data in the neural network at MATLAB were trained and examined to improve the NN algorithm according to this data. Comparing all the simulated location faults that have been applied with those all locations detected in the NN algorithm, the overall error between them has been found to be very low and not to exceed 0.7. The Simulink circuit was created from this algorithm and checked in order to predict each failure could occur in the future in the MV network.</p>

Method for Protection of Single-Line-Ground Fault of Distribution System with DG Using Distance Relay and Directional Relay

2020 ◽  
Vol 15 (4) ◽  
pp. 1607-1616
Author(s):  
Jung-Hun Lee ◽  
Min-Su Park ◽  
Hong-Seon Ahn ◽  
Kyung-Won Park ◽  
Jun-Seok Oh ◽  
...  
Keyword(s):  
Distribution System ◽  
Single Line ◽  
Distance Relay ◽  
Ground Fault ◽  
Directional Relay

On the Selection of Bypassing Schemes Affecting the Secondary Arc Current and TRV in Series Compensated Lines

2012 ◽  
Vol 13 (5) ◽  
Author(s):  
Zeynab Zandi ◽  
Keyhan Sheshyekani ◽  
Ebrahim Afjei
Keyword(s):  
Transmission Lines ◽  
Frequency Domain Analysis ◽  
Capacitive Coupling ◽  
System Stability ◽  
Single Line ◽  
Arc Model ◽  
Ground Fault ◽  
In Series ◽  
Arc Current ◽  
Recovery Voltage

Abstract This paper investigates the effect of different bypassing schemes and grounding methods on the secondary arc current and the transient recovery voltage (TRV) of series compensated transmission lines. It is known that in series compensated lines, the peak value of the TRV may exceed the insulation strength. Furthermore, a secondary arc current is generated during a single line to ground fault mainly affected by the capacitive coupling between the healthy lines and the faulted line and can persist for seconds. The steadiness of secondary arc current prevents line reclosers from having a prompt closing to fulfill the system stability. This paper discusses different scenarios that can be employed to limit the secondary arc current consistency and to suppress a severe TRV during a single line to ground fault. A frequency domain analysis is conducted to better understand the nature of the secondary arc current. It is noted that an accurate arc model based upon the Kiziclay’s arc model is used in the simulations.

Study of Reconfiguration Algorithm in Distribution System Based on Hopfield Network

2012 ◽  
Vol 241-244 ◽  
pp. 1900-1903
Author(s):  
Na Wei ◽  
Zhe Cheng ◽  
Xiao Meng Wu
Keyword(s):  
Neural Network ◽  
Energy Function ◽  
Distribution System ◽  
Distribution Network ◽  
Hopfield Neural Network ◽  
Hopfield Network ◽  
Network Reconfiguration ◽  
Power Sources ◽  
Distribution Network Reconfiguration ◽  
The Neural Network

In accordance with the characteristic of radial running an algorithm for distribution network reconfiguration based on Hopfield neural network is put forward. The in-degree of each node is determined by Hopfield neural network, it is determined whether the lines run according to the in-degree of the nodes, and the state of each loop switch is determined according to whether the lines run, and thus the distribution network reconfiguration scheme is determined finally. The energy function of the neural network and its solution method are presented. In the energy function are considered the radial running of distribution network, the lowest distribution network loss and no loop switch in some lines. The IEEE distribution network structure with three power sources obtained by the algorithm is basically consistent to that obtained by genetic algorithm, but the time spent using the former is shorter than that the latter.

scholarly journals COMPARISON OF EARTHING TECHNIQUES FOR SINGLE LINE TO GROUND FAULT IN 11 kV DISTRIBUTION SYSTEM USING SIMULINK

2019 ◽  
Vol 23 (04) ◽  
pp. 1-17
Author(s):  
Ali Abdulabbas Abdullah ◽  
◽  
Inaam Ibrahim Ali ◽  
Alameer Abbas Thamir ◽  
◽  
...  
Keyword(s):  
Distribution System ◽  
Single Line ◽  
Ground Fault

Single-Line to Ground-Fault Detection for Unit Generator-Transformer Based on Wavelet Transform and Neural Networks

2016 ◽  
Vol 818 ◽  
pp. 47-51
Author(s):  
Ahmad Rizal Sultan ◽  
Mohd Wazir Mustafa ◽  
Makmur Saini
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Wavelet Transform ◽  
Fault Detection ◽  
Wavelet Transforms ◽  
Single Line ◽  
Statistical Parameters ◽  
Ground Fault ◽  
Parameters Analysis ◽  
Ground Fault Detection

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.

scholarly journals Simplified Method for Single Line to Ground-Fault Location in Electrical Power Distribution Systems

2015 ◽  
Vol 5 (2) ◽  
pp. 221
Author(s):  
Mustapha Zahri ◽  
Youssef Menchafou ◽  
Hassane El Markhi ◽  
Mohamed Habibi
Keyword(s):  
Power Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Fault Location ◽  
Electrical Power ◽  
Modern Society ◽  
Single Line ◽  
Power Distribution Systems ◽  
Ground Fault

<p>Power distribution systems play important roles in modern society. When distribution system outages occur, speedy and precise fault location is crucial in accelerating system restoration, reducing outage time and significantly improving system reliability, and then improves the quality of services and customer satisfaction. In this paper, we propose a reduced algorithm utilizing the sum of sending-end currents of the three phases to calculate the fault current, and therefore, avoid the iterative aspect of the classic algorithm for single line to ground fault location and reduce its computational charge. The test results are obtained from the numerical simulation using the data of a distribution line recognized in the literature.</p>

Sign in / Sign up

Export Citation Format

Share Document