A novel study for hydro-generators loss of excitation faults detection using ANFIS

被引：7

作者：

Abdel Aziz M.S. ^{[1
]}

Elsamahy M. ^{[2
]}

Moustafa Hassan M.A. ^{[3
]}

Bendary F.M.A. ^{[4
]}

机构：

[1] Dar Al-Handasah (Shair and Partners), Cairo

[2] Elec. Power Department, Higher Institute of Engineering, El-Shorouk Academy, Cairo

[3] Elec. Power Department, Faculty of Engineering, Cairo University, Giza

[4] Elec. Power Department, Faculty of Engineering at Shoubra, Benha University, Cairo

来源：

International Journal of Modelling and Simulation | 2017年 / 37卷 / 01期

关键词：

Adaptive neuro fuzzy inference system; Dynamic performance; Hydro-generator; Loss of excitation; Simulation;

D O I：

10.1080/02286203.2016.1232956

中图分类号：

学科分类号：

摘要：

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 345 kV 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. Three techniques are used in this article based on the type of inputs to the proposed ANFIS unit, the generator terminal impedance measurements (R and X), the generator RMS Line to Line voltage and Phase current (Vtrms and Ia) and the positive sequence components of the generator voltage magnitude, phase current magnitude, and angle (|V+ve|, |I+ve|, and 90 I+ve). The obtained results from these schemes are compared with each other and are compared with other techniques. The results show that the proposed technique is effective in detecting the LOE faults and the obtained results are very encouraging. © 2016 Informa UK Limited, trading as Taylor & Francis Group.

引用

页码：36 / 45

页数：9

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