title: Fault detection and classification in electrical power transmission system using artificial neural network.
abstract: This paper focuses on the detection and classification of the faults on electrical power transmission line using artificial neural networks. The three phase currents and voltages of one end are taken as inputs in the proposed scheme. The feed forward neural network along with back propagation algorithm has been employed for detection and classification of the fault for analysis of each of the three phases involved in the process. A detailed analysis with varying number of hidden layers has been performed to validate the choice of the neural network. The simulation results concluded that the present method based on the neural network is efficient in detecting and classifying the faults on transmission lines with satisfactory performances. The different faults are simulated with different parameters to check the versatility of the method. The proposed method can be extended to the Distribution network of the Power System. The various simulations and analysis of signals is done in the MATLAB(®) environment.
authors.affiliation: Department of Electrical Engineering, Faculty of Engineering, Jamia Millia Islamia, New Delhi, 110025 India.
authors.forename: Majid
authors.initials: M
authors.lastname: Jamil
authors.affiliation: Department of Electrical Engineering, Faculty of Engineering, Jamia Millia Islamia, New Delhi, 110025 India.
authors.forename: Sanjeev Kumar
authors.initials: SK
authors.lastname: Sharma
authors.affiliation: Department of Electrical Engineering, Faculty of Engineering, Jamia Millia Islamia, New Delhi, 110025 India.
authors.forename: Rajveer
authors.initials: R
authors.lastname: Singh
keywords: Artificial neural networks; Back propagation algorithm; Feedforward networks; Levenberg–Marquardt algorithm