Saturday, August 19th, 2017

Generation of synthetic daily global solar radiation data based on ERA-Interim reanalysis and artificial neural networks

Publication year: 2011brbSource:/b Energy, In Press, Corrected Proof, Available online 24 July 2011brAlvaro, Linares-Rodríguez , José Antonio, Ruiz-Arias , David, Pozo-Vázquez , Joaquín, Tovar-PescadorbrFour variables (total cloud cover, skin temperature, total column water vapour and total column ozone) from meteorological reanalysis were used to generate synthetic daily global solar radiation via artificial neural network (ANN) techniques. The goal of our study was to predict solar radiation values in locations without ground measurements, by using the reanalysis data as an alternative to the use of satellite imagery. The model was validated in Andalusia (Spain), using measured data for nine years from 83 ground stations spread over the region. The geographical location (latitude, longitude), the day of the year, the daily clear sky global radiation,…br Highlights: ► Accuracy synthetic daily global solar radiation data were generated using neural networks techniques. ► Meteorological variables from ERA-Interim reanalysis were used as input variables. ► Data from 83 stations for 10 years were used, and daily global radiation maps were generated. ► The method could be used as a good alternative to the use of satellite imagery. ► Furthermore, the forecasting capability of the model was successfully probed.


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