As it is crucial to protect the transmission line from inevitable faults consequences

intelligent scheme must be employed for immediate fault detection and classification. The application of Artificial Neural Network (ANN) to detect the fault

identify it’s section

and classify the fault on transmission lines with improved zone reach setting is presented in this article. The fundamental voltage and current magnitudes obtained through Discrete Fourier Transform (DFT) are specified as the inputs to the ANN. The relay is placed at section-2 which is the prime section to be protected. The ANN was trained and tested using diverse fault datasets; obtained from the simulation of different fault scenarios like different types of fault at varying fault inception angles

fault locations and fault resistances in a 400 kV

216 km power transmission network of CSEB between Korba-Bhilai of Chhattisgarh state using MATLAB. The simulation outcomes illustrated that the entire shunt faults including forward and reverse fault

it’s section and phase can be accurately identified within a half cycle time. The advantage of this scheme is to provide a major protection up to 99.5% of total line length using single end data and furthermore backup protection to the forward and reverse line sections. This routine protection system is properly discriminatory

rapid

robust

enormously reliable and incredibly responsive to isolate targeted fault.