Cite as:
Urbich, I.; Bendix, J. &amp; M&uuml;ller, R. (2019): <b>The Seamless Solar Radiation (SESORA) Forecast for Solar Surface Irradiance—Method and Validation</b>. <i>Remote Sensing</i> <b>11</b>(21), 2576.

Resource Description

Title: The Seamless Solar Radiation (SESORA) Forecast for Solar Surface Irradiance—Method and Validation
FOR816dw ID: 344
Publication Date: 2019-11-04
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Resource Owner(s):
Individual: Isabel Urbich
Individual: Jörg Bendix
Individual: Richard Müller
Due to the integration of fluctuating weather-dependent energy sources into the grid<br/> the importance of weather and power forecasts grows constantly. This paper describes the<br/> implementation of a short-term forecast of solar surface irradiance named SESORA (seamless sola<br/> radiation). It is based on the the optical flow of effective cloud albedo and available for Germany<br/> and parts of Europe. After the clouds are shifted by applying cloud motion vectors, solar radiation i<br/> calculated with SPECMAGIC NOW(Spectrally Resolved Mesoscale Atmospheric Global Irradianc<br/> Code), which computes the global irradiation spectrally resolved from satellite imagery. Due to the<br/> high spatial and temporal resolution of satellite measurements, solar radiation can be forecasted<br/> from 15 min up to 4 h or more with a spatial resolution of 0.05. An extensive validation of thi<br/> short-term forecast is presented in this study containing two different validations based on eithe<br/> area or stations. The results are very promising as the mean RMSE (Root Mean Square Error) of thi<br/> study equals 59W/m2 (absolute bias = 42W/m2) after 15 min, reaches its maximum of 142W/m<br/> (absolute bias = 97W/m2) after 165 min, and slowly decreases after that due to the setting of the sun<br/> After a brief description of the method itself and the method of the validation the results will be<br/> presented and discussed.
| MSG-SEVIRI | Solar energy |
Literature type specific fields:
Journal: Remote Sensing
Volume: 11
Issue: 21
Page Range: 2576
Metadata Provider:
Individual: Jörg Bendix
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