Date of Award
Master of Science in Engineering
Electrical and Computer Engineering
Dr. Johnson Asumadu
Dr. Ikhlas Abdul-Qader
Dr. Raghvendra Gejji
Dr. Christopher Cho
Fault detection, fault classification, fault localization, transmission line, composite relay
Masters Thesis-Open Access
This thesis focuses on new approach to detect, classify, and localize the fault in transmission line. Firstly, fault detection was carried out using the New Composite Relay (CR) which, has different characteristics and the ability to detect any type of fault including series faults. Secondly, fault classification was conducted using the Feed Forward Artificial Neural Network (FFANN). In addition, the fault classification led to the investigation of the best use of the FFANN. The data used come from MATLAB/SIMULINK three phase series compensated network. The results obtained using FFANN, were compared with the type of the fault that have been actually applied on the system. Finally, a digital controller was combined with FFANN to appropriately select the type of fault localization that should be used.
Altaie, Ahmed Sabri, "Design of a New Digital Relay for Transmission Line Fault Detection, Classification and Localization Based on a New Composite Relay and Artificial Neural Network Approach" (2015). Masters Theses. 652.