4.8 Review

Solar radiation prediction using Artificial Neural Network techniques: A review

期刊

RENEWABLE & SUSTAINABLE ENERGY REVIEWS
卷 33, 期 -, 页码 772-781

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2013.08.055

关键词

Solar energy; Solar radiation models; Artificial Neural Network; Solar radiation prediction; Meteorological data

向作者/读者索取更多资源

Solar radiation data plays an important role in solar energy research. These data are not available for location of interest due to absence of a meteorological station. Therefore, the solar radiation has to be predicted accurately for these locations using various solar radiation estimation models. The main objective of this study is to review Artificial Neural Network (ANN) based techniques in order to identify suitable methods available in the literature for solar radiation prediction and to identify research gaps. The study shows that Artificial Neural Network techniques predict solar radiation more accurately in comparison to conventional methods. The prediction accuracy of ANN models is found to be dependent on input parameter combinations, training algorithm and architecture configurations. Further research areas in ANN technique based methodologies are also identified in the present study. (C) 2013 Published by Elsevier Ltd.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据