Article ID Journal Published Year Pages File Type
7935687 Solar Energy 2018 13 Pages PDF
Abstract
The skill of the various models were evaluated using several metrics and statistical tests. We found that WRF-solar combined with our proposed statistical learning method outperformed smart persistence, a climatological forecast and GFS for day-ahead forecasts of irradiance. In particular, our model was shown to have a Root Mean Square Error (RMSE) 23% lower than smart persistence.
Related Topics
Physical Sciences and Engineering Energy Renewable Energy, Sustainability and the Environment
Authors
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