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Artificial Neural Network Based Fault Classification and Location for Transmission Lines

Research Abstract
Due to various faults occur to transmission lines and because it was necessary to find and recover these faults quickly as possible. This paper discussing fault detection, classification and determining fault location as fast as possible via Artificial Neural Network (ANN) algorithm. The software used for modeling the proposed network is a MATLAB/SIMULINK software environment. The training, testing and evaluation of the intelligent locator processes are done based on a multilayer Perceptron feed forward neural network with back propagation algorithm. Mean Square Error (MSE) algorithm is used to evaluate the performance of the detector/classifier as well as fault locator. The results show that the validation performance (MSE) for the fault detector/classifier is 2.36e-9 and for fault locator is 2.179e-5. The system can detect if there is a fault or not, can classify the fault type and determine the fault location very precisely.
Research Authors
Ahmed Elnozahy,
Khairy Sayed,
Mohamed Bahyeldin.
Research Department
Research Journal
2019 IEEE Conference on Power Electronics and Renewable Energy (CPERE)
Research Pages
pp. 140-144
Research Publisher
IEEE
Research Rank
3
Research Vol
NULL
Research Website
https://ieeexplore.ieee.org/document/8980173
Research Year
2019