A New High Impedance Fault Detection Technique Using Deep Learning Neural Network

2021 ◽  
pp. 179-195
Author(s):  
M. M. Eissa ◽  
M. H. Awadalla ◽  
A. M. Sharaf
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Fault Detection ◽  
Detection Technique ◽  
High Impedance ◽  
High Impedance Fault ◽  
Deep Learning Neural Network

An ANN-Based High Impedance Fault Detection Scheme: Design and Implementation

2005 ◽  
Vol 4 (2) ◽  
Author(s):  
Hassan Khorashadi Zadeh
Keyword(s):  
Neural Network ◽  
Fault Detection ◽  
Performance Studies ◽  
Digital Signal Processor ◽  
Distribution System ◽  
Distribution Systems ◽  
Design Procedure ◽  
Detection Scheme ◽  
High Impedance ◽  
High Impedance Fault

This paper presents a new approach to detection of high impedance faults in distribution systems using artificial neural networks. The proposed neural network, was trained by data from simulation of a distribution system under different faults conditions, and tested by data with different system conditions. The proposed neural network has been implemented on a digital signal processor board and its behavior is investigated on a computer power system model. Details of the design procedure, implementation and the results of performance studies with the proposed relay are given in this paper. Performance studies results show that the proposed algorithm performs very well in detecting a high impedance fault with nonlinear arcing resistance. It is clearly shown that with this integrated approach, the accuracy in fault detection is significantly improved compared to other techniques based on conventional algorithms.

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