학술논문
Fault detection in Electrical Power Transmission System using Artificial Neural Network
Document Type
Conference
Author
Source
2020 International Conference on Computational Intelligence for Smart Power System and Sustainable Energy (CISPSSE) omputational Intelligence for Smart Power System and Sustainable Energy (CISPSSE), 2020 International Conference on. :1-4 Jul, 2020
Subject
Language
Abstract
Since the number of transmission line is increasing day by day to meet the increasing load demand; occurrence of faults is also increasing. For clearance of faults their detection has to be spontaneous and accurate so that it will cause less damage to the power system. One of the best methods for detection of fault in transmission lines is Artificial Neural Network (ANN). After creation of the Simulink model the phase currents of different faults are generated and it has been given as input to the Neural Network Model. For the input data a target data is generated which consist values for no fault and fault conditions. Programming is used through which all the variables and target data are passed for creation of ANN model. After creation of the model, it is trained and tested for the same input & label data. The testing results show the good performance of the Artificial Neural Network for all types of faults