AN ARTIFICIAL NEURAL-NET BASED METHOD FOR PREDICTING POWER-SYSTEM VOLTAGE HARMONICS

被引：51
|
作者：
MORI, H
ITOU, K
UEMATSU, H
TSUZUKI, S
机构：
[1] Department of Electrical Engineering, Meiji University, Tama-ku
来源：
IEEE TRANSACTIONS ON POWER DELIVERY | 1992年 / 7卷 / 01期
关键词：
HARMONICS; ADAPTIVE PREDICTION; ARTIFICIAL NEURAL NETWORK; BACKPROPAGATION; AR MODELS;
D O I：
10.1109/61.108934
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 presents a new method for predicting power system voltage harmonics with an artificial neural network. The method is based on the backpropagation learning technique for feedforward neural networks. This paper shows how the proposed method is promising in harmonics prediction. In order to demonstrate the effectiveness, the proposed method is applied to voltage harmonics observed through a personal computer based measurement system and the performance is compared with the ten conventional methods.
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页码：402 / 409
页数：8
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