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

页码：164 / 168

页数：5

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