Transmission Line Monitoring and Protection with ANN aided Fault Detection, Classification and Location
Gokul Krishna N, Jithu Raj, Lekshmi R. Chandran
Abstract
Accurate and fast detection of fault is important for reliable protection of power systems. This paper presents an intelligent Transmission Line protection system, which can detect faults, classify them and also identify the location of the fault. Artificial Neural Networks (ANN) were employed to develop the Fault Detector, Classifier and Locator models. ANN was selected because it can handle non-linear and dynamic problems with greater ease and reliability. The fault dataset was generated through simulation by changing the fault parameters such as different types of symmetrical and asymmetrical faults, fault resistance and fault distances. Finally, a real time model for transmission line protection was also developed. The proposed model detects the faults and trips the circuit breaker in the event of a fault. Different faults were introduced to demonstrate the trip action being taken to protect the system.