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http://hdl.handle.net/10174/37234
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| Title: | Study and development of a solar radiation predicting algorithm based on ECMWF's forecasts and ANNs |
| Authors: | Pereira, Sara
Canhoto, Paulo
Salgado, Rui
Costa, Maria João |
| Keywords: | solar radiation
solar energy
solar radiation forecast
ECMWF model
artificial neural network |
| Issue Date: | 17-Jun-2018 |
| Publisher: | Japan Council for Renewable Energy |
| Citation: | Pereira, S., Canhoto, P., Salgado, R., Costa, M. J. (2018). Study and development of a solar radiation predicting algorithm based on ECMWF's forecasts and ANNs. Grand Renewable Energy Proceedings, 2018 - International Conference and Exhibition, Japan Council for Renewable Energy, Vol. 1, pp. 43-46, 17-22 June 2018, Yokohama, Japan. ISSN: 2434-0871. |
| Abstract: | This paper presents a study on the influence of Sun-Earth geometry and atmospheric variables on the predictions of solar global irradiation (GHI) obtained from the ECMWF model. It was found that the differences between predictions and measurements of GHI are correlated mainly with the clearness index, solar zenith angle, mean air temperature, relative humidity and total water column. An artificial neural network is developed to improve predictions of GHI for four locations being the base for a predicting algorithm that can be used in energy management models of solar systems thus allowing a better management of renewable energy conversion. |
| URI: | http://hdl.handle.net/10174/37234 |
| Type: | article |
| Appears in Collections: | ICT - Artigos em Livros de Actas/Proceedings
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