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http://hdl.handle.net/10174/24098
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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: | Grand Renewable Energy 2018 - International Conference and Exhibition |
Citation: | Sara Pereira, Paulo Canhoto, Rui Salgado, Maria João Costa, Study and development of a solar radiation predicting algorithm based on ECMWF's forecasts and ANNs. Grand Renewable Energy 2018 - International Conference and Exhibition, 17 - 22 June, 2018, Pacifico Yokohama, Japan |
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/10174/24098 |
Type: | lecture |
Appears in Collections: | CGE - Comunicações - Em Congressos Científicos Internacionais
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