Fault Detection in Transmission Line Using ANN
Supriya Kumari, Anchal Mishra, Ayush Singhal, Vikram Dahiya, Mayank Gupta, Suresh Kumar Gawre
Abstract
Transmission line plays a very important role in ensuring the continuous supply of electricity. However, there is no such thing as perfect or fault-free. Due to various reasons, may that be exposure to the environment, accident, transmission failure or faults due to mis operation; faults occur in transmission line. This results in sudden increase of current, more heat production in conductors leading to some major accidents. The objective of this paper is to fault detection by introducing Artificial Neural Network (ANN) which is not only fast but also very efficient. Initially, the neural network is feed with six input values, i.e., the values of current and voltages of three phases respectively, and trained using these six inputs. And when the fault occurs, the value of pre-fault and post-fault condition are different, the trained ANN compares these pre-fault and post-fault values to give us the result of its deduction. We have used MATLAB to implement ANN for fault detection.