Short Term Forecast of Wind Power by an Artificial Neural Network Approach

被引：0
|
作者：
Ouammi, Ahmed [2 ]
Dagdougui, Hanane [1 ]
Sacile, Roberto [2 ,3 ]
机构：
[1] Univ Genoa, Dept Commun Comp & Syst Sci DIST, I-16145 Genoa, Italy
[2] DIST, Genoa, Italy
[3] DELAB, Joint Res Lab DIST & Eni, Genoa, Italy
来源：
2012 IEEE INTERNATIONAL SYSTEMS CONFERENCE (SYSCON) | 2012年
关键词：
SPEED TIME-SERIES; PREDICTION;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The wind power forecasting constitutes a critical task for wind power generation system, since it is essential for the integration of wind energy into power system. In this paper, an artificial neural networks (ANNs) were applied to predict the wind power in a short term scale, in the Capo Vado site in Italy. Results from a real-world case study are presented. The development, training and validation of neural network model for the wind power prediction are discussed.
引用
收藏
页码：209 / 213
页数：5
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