Article ID Journal Published Year Pages File Type
5482997 Renewable and Sustainable Energy Reviews 2017 16 Pages PDF
Abstract
Three different tiers of estimations were obtained being SARAH and OK the best performing methods overall. The SARAH dataset (MAE=1.10±0.13 MJ/m2, MBE=0.22±0.36 MJ/m2) generated estimates with the lowest spread, but led to a slight overestimation in low-altitude flat areas. The OK (MAE=1.10±0.25 MJ/m2, MBE=0.00±0.31 MJ/m2) outperformed SARAH in these flat areas (high density of stations), but at the expense of a higher variability. Alternatively, SARAH surpassed Ordinary Kriging (OK) when the distance to the closest station exceeded 20-30 km. The ERA-Interim reanalysis and the XGBoost were in the second tier of estimations, and the parametric model yielded the worst results overall. ERA-Interim exhibited a systematic overestimation. The locally trained Antonanzas and XGBoost struggled to model the atmospheric transmissivity, showing large positive errors in spring months and a small underestimation of clear-sky days. Finally, a summary with the strengths and weaknesses of the five methods provides a deeper understanding for the selection of the adequate estimation approach.
Related Topics
Physical Sciences and Engineering Energy Renewable Energy, Sustainability and the Environment
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