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Short term cloud nowcasting for a solar power plant based on irradiance historical Data

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Caballero Roldán, Rafael and Zarzalejo Tirado, Luis Fernando and Otero Martín, Álvaro and Piñuel Moreno, Luis and Wilbert, Stefan (2018) Short term cloud nowcasting for a solar power plant based on irradiance historical Data. Journal of computer science & technology, 18 (3). pp. 186-192. ISSN 1666-6046

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Official URL: http://dx.doi.org/10.24215/16666038.18.e21




Abstract

This work considers the problem of forecasting the normal solar irradiance with high spatial and temporal resolution (5 minutes). The forecasting is based on a dataset registered during one year from the high resolution radiometric network at a operational solar power plan at Almeria, Spain. In particular, we show a technique for forecasting the irradiance in the next few minutes from the irradiance values obtained on the previous hour. Our proposal employs a type of recurrent neural network known as LSTM, which can learn complex patterns and that has proven its usability for forecasting temporal series. The results show a reasonable improvement with respect to other prediction methods typically employed in the studies of temporal series.


Item Type:Article
Additional Information:

© 2018 Universidad Nacional de La PLata
This work has been partially supported by the Spanish MINECO project TIN2015-66471, and by the Santander-UCM project PR26/16-21B-1.

Uncontrolled Keywords:Time-series; Radiation; Cloud nowcasting; GHI; LSTM; Supervised machine learning; Computer Science; Artificial Intelligence
Subjects:Sciences > Computer science > Artificial intelligence
ID Code:50740
Deposited On:17 Jan 2019 15:55
Last Modified:17 Jan 2019 15:55

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