FAULT IDENTIFICATION IN AN AC-DC TRANSMISSION-SYSTEM USING NEURAL NETWORKS

被引：55

作者：

KANDIL, N ^{[1
]}

SOOD, VK ^{[1
]}

KHORASANI, K ^{[1
]}

PATEL, RV ^{[1
]}

机构：

[1] HYDRO QUEBEC,IREQ,VARENNES J3X 1S1,QUEBEC,CANADA

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 1992年 / 7卷 / 02期

基金：

加拿大自然科学与工程研究理事会;

关键词：

NEURAL NETWORKS; HVDC TRANSMISSION; FAULT IDENTIFICATION;

D O I：

10.1109/59.141790

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper explores the possibility of using neural networks to identify faults that may have occurred in an ac-dc power system. Based on the ability of these networks to distinguish reliably between different types of faults, appropriate control measures can be taken to improve the dynamic performance of the ac-dc power system. In this paper, three different neural network architectures to distinguish between different types of faults on the ac-dc system are proposed, and a comparison between them is made.

引用

页码：812 / 819

页数：8

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