Voltage ranking using artificial neural network

被引：1
|
作者：
Lo, KL [1 ]
Luan, WP
Given, M
Macqueen, JF
Ekwue, AO
Chebbo, AM
机构：
[1] Univ Strathclyde, Glasgow, Lanark, Scotland
[2] Natl Grid Co Plc, Sindlesham, England
来源：
COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING | 1999年 / 18卷 / 04期
关键词：
voltage; propagation; networks; artificial neural networks;
D O I：
10.1108/03321649910296618
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Voltage ranking attempts to rank busbar voltage deviations from their normally accepted security margins based on a set of performance indices (PI), without performing a full load flow. Existing methods suffer from either masking effects or long computation time. In this paper, an artificial neural network method is proposed for voltage ranking Counterpropagation network (CPN) has been employed to overcome the problems listed above. A variety of input features are used with the aim of lowering the dimension of the proposed ANN to make it applicable for large power systems. The method is tested on two example systems, a five-bus system and a 71-bus system with very encouraging results.
引用
收藏
页码：587 / 599
页数：13
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