Load Prediction Of RBF Neural Network Considering Weather Factors

被引：1

作者：

Wei, Renran ^{[1
]}

Wei, Zhenzhu ^{[1
]}

Yang, Haibo ^{[2
]}

Jiang, Jiandong ^{[1
]}

机构：

[1] Zhengzhou Univ, Sch Elect Engn, Zhengzhou 450001, Henan, Peoples R China

[2] Weihui Power Supply Co, Weihui 453100, Henan, Peoples R China

来源：

ADVANCED DESIGN AND MANUFACTURING TECHNOLOGY III, PTS 1-4 | 2013年 / 397-400卷

关键词：

RBF neural network; BP neural network; Weather factors; Load prediction;

D O I：

10.4028/www.scientific.net/AMM.397-400.1103

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In order to improve the precision of the short-term load prediction, a new method based on radial basis function (RBF) neural network is proposed. The weather data of samples includes the temperature, humidity, date, type, etc., and is quantified according the relevance to load, and then forecasting the power load using RBF neural network model in a region, Actual example shows that this method improves the convergence speed and prediction accuracy of load forecasting.

引用

页码：1103 / +

页数：2

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