Open AccessImprovement global solar radiation estimation
Author(s) -
Loghmari Ismail,
Timoumi Youssef
Publication year - 2017
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2017.0118
Subject(s) - satellite , computer science , mean squared error , reliability (semiconductor) , photovoltaic system , solar energy , remote sensing , reliability engineering , data mining , database , root mean square , environmental science , power (physics) , statistics , mathematics , engineering , aerospace engineering , physics , electrical engineering , quantum mechanics , geology
Energy yields of photovoltaic power plants are directly related to the availability of the global solar radiation (GHI). An accurate performance analysis of these power plants depends strongly on the quality and the reliability of the solar resource assessment. This study proposed to improve the accuracy of the GHI database provided by satellites. Two quality improvement methods have been proposed and evaluated in this study. The first developed method consists in combining a GHI satellite‐derived database with the best ground station models, while the second one consists in performing a linear correction of a satellite database. The purpose of this study is to investigate the quality improvement method that gives more accurate GHI prediction. The comparison between the two developed methods shows that the resulting combination method database achieves higher GHI prediction accuracy than the linearly corrected satellite database. This combination reduces the uncertainty of the original satellite database by 1.95%, with a resulting relative root‐mean‐square error (rmse%) reaching 4.74%.