Neuro-Fuzzy Based Fault Detection Identification and Location in a Distribution Network

被引：0
|
作者：
Babayomi, Oluleke [1 ]
Oluseyi, Peter [2 ]
Keku, Godbless [3 ]
Ofodile, Nkemdilim A. [4 ]
机构：
[1] Nat Space Res & Dev Agcy, Cent Space Transport & Prop, Abuja, Nigeria
[2] Univ Lagos, Dept Elect & Elect Engn, Lagos, Nigeria
[3] Nig Mar Admin & Safety Agcy, Plan Res & Data Mgt Serv, Apapa, Nigeria
[4] Nigerian Air Force, Nig Air Force Res & Dev Cent, Abuja, Nigeria
来源：
2017 IEEE PES POWERAFRICA CONFERENCE | 2017年
关键词：
three phase faults; adaptive neuro-fuzzy inference system; distribution network; fault identification; fault location; fuzzy-logic; POWER-SYSTEMS; DIAGNOSIS;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
This paper presents an investigation into neuro-fuzzy techniques for the accurate detection, classification and location of an electric power fault in a distribution network. Ten different types of faults were studied with respect to a real network. These include: line-to-ground faults (on each of phases A, B and C); line-to-line faults (on phases A-B, B-C and A-C); line-to-line-to-ground faults (on phases A-B, B-C and A-C) and three phase fault. A Mandami-type fuzzy controller was also applied to fault type determination. The results reveal that the developed models detect, identify and locate fault incidences to a high degree of accuracy.
引用
收藏
页码：164 / 168
页数：5
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