Forecasting Portugal global load with artificial neural networks

被引:0
|
作者
Fidalgo, J. Nuno [1 ]
Matos, Manuel A.
机构
[1] Univ Porto, INESC Porto, Power Syst Unit, Oporto, Portugal
来源
ARTIFICIAL NEURAL NETWORKS - ICANN 2007, PT 2, PROCEEDINGS | 2007年 / 4669卷
关键词
artificial neural networks; load forecasting;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper describes a research where the main goal was to predict the future values of a time series of the hourly demand of Portugal global electricity consumption in the following day. In a preliminary phase several regression techniques were experimented: K Nearest Neighbors, Multiple Linear Regression, Projection Pursuit Regression, Regression Trees, Multivariate Adaptive Regression Splines and Artificial Neural Networks (ANN). Having the best results been achieved with ANN, this technique was selected as the primary tool for the load forecasting process. The prediction for holidays and days following holidays is analyzed and dealt with. Temperature significance on consumption level is also studied. Results attained support the adopted approach.
引用
收藏
页码:728 / +
页数:3
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