Applications of ANFIS in Loss of Excitation Faults Detection in Hydro-Generators

Mohamed Salah El-Din Ahmed Abdel Aziz, Mohamed El Samahy, Mohamed A. Moustafa Hassan and Fahmy El Bendary
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Mohamed Salah El-Din Ahmed Abdel Aziz: Dar Al-Handasah (Shair and Partners), Giza, Egypt
Mohamed El Samahy: Elec. Power Dept., The higher Institute of Engineering, El-Shorouk Academy, Egypt
Mohamed A. Moustafa Hassan: Electrical Power Department, Faculty of Engineering, Cairo University, Giza, Egypt
Fahmy El Bendary: Electrical Power Department, Faculty of Engineering, Banha University, Banha, Egypt

International Journal of System Dynamics Applications (IJSDA), 2016, vol. 5, issue 2, 63-79

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

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jsda00:v:5:y:2016:i:2:p:63-79

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