ANN-Based Approach for Fault Detection in GIS

This paper introduces an artificial neural netw (GIS). Faults in GIS have to be located and classified as soon as possible to start the processes of reconfiguration and restoration of the normal power supply. A practical case study is an represents a critical generation point in the Egyptian Electric Power Network. Firstly, the layout of the Talkha 220 kV GIS is discussed and modeled using ATP/EMTP. Secondly, the ANN is built and trained. Finally, the p approach is tested using solidly grounded faults and high impedance faults. The results ensure the success of the proposed approach to locate and classify any fault in and/or out the GIS