A generalized model for short-term forecasting of solar irradiance

被引:0
|
作者
Lago, Jesus [1 ,2 ]
De Brabandere, Karel [3 ]
De Ridder, Fjo [2 ]
De Schutter, Bart [1 ]
机构
[1] Delft Univ Technol, Delft Ctr Syst & Control, Delft, Netherlands
[2] VITO, Algorithms Modeling & Optimizat, Energyville, ThorPk, Genk, Belgium
[3] 3E, Brussels, Belgium
关键词
NEURAL-NETWORKS; RADIATION; VALIDATION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, as the share of solar power in the electrical grid has been increasing, accurate methods for forecasting solar irradiance have become necessary to manage the electrical grid. More specifically, as solar generators are geographically dispersed, it is very important to have general models that can predict solar irradiance without the need of ground data. In this paper, we propose a novel technique that can accomplish that: using satellite images, the proposed model is able to forecast solar irradiance without the need of ground measurements. To illustrate the performance of the proposed model, we consider 15 locations in The Netherlands, and we show that the proposed model is as accurate as local models that are individually trained with ground data.
引用
收藏
页码:3165 / 3170
页数:6
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