Loss of Excitation Faults Detection in Hydro-Generators Using an Adaptive Neuro Fuzzy Inference System

Mohamed Salah El-Din Abdel Aziz (Dar Al-Handasah (Shair and partners), Al mohandesin, Egypt.)
Mohamed Elsamahy (Elec. Power& Computer Engineering Dept., University of Saskatchewan, Canada)
Mohamed Moustafa (Elec. Power Dept., Faculty of Engineering, Cairo University, Egypt)
Fahmy Bendary (Elec. Power Dept., Faculty of Engineering, Benha University, Egypt)

Indonesian Journal of Electrical Engineering and Computer Science
Vol 1, No 2: February 2016

This paper presents a new approach for Loss of Excitation (LOE) faults detection in Hydro-generators using Adaptive Neuro Fuzzy Inference System. The proposed scheme was trained by data from simulation of a 345kV system under various faults conditions and tested for different loading conditions. Details of the design process and the results of performance using the proposed technique are discussed in the paper. Two different techniques are discussed in this article according to the type of inputs to the proposed ANFIS unit, the generator terminal impedance measurements (R & X) and the generator RMS Line to Line voltage and Phase current (Vtrms & Ia). The two proposed techniques results are compared with each other and are compared with the traditional distance relay response in addition to other technique. The results show that the proposed Artificial Intelligent based technique is efficient in the Loss of Excitation faults (LOE) detection process and the obtained results are very promising.