Neural network based fault diagnosis in an HVDC system

被引：7

作者：

Etemadi, H ^{[1
]}

Sood, VK ^{[1
]}

Khorasani, K ^{[1
]}

Patel, RV ^{[1
]}

机构：

[1] Concordia Univ, Dept Elect & Comp Engn, Montreal, PQ H3G 1M8, Canada

来源：

DRPT2000: INTERNATIONAL CONFERENCE ON ELECTRIC UTILITY DEREGULATION AND RESTRUCTURING AND POWER TECHNOLOGIES, PROCEEDINGS | 2000年

关键词：

NN; fault classification; HVDC system;

D O I：

10.1109/DRPT.2000.855665

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 a neural network (NN) based method for fault classification in a power system. A new method of generating the training data is proposed which has the advantage that the total number of fault simulations needed to generate the training patterns is less than that required by the conventional training method. This is obtained at the cost of a time delay in the NN output response. The performance of the proposed method is investigated using the Matlab simulation model of a simple HVDC system.

引用

页码：209 / 214

页数：6

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