Deep learning-based forecasting of aggregated CSP production

Jorge Segarra-Tamarit, Emilio Pérez, Eric Moya, Pablo Ayuso and Hector Beltran

Mathematics and Computers in Simulation (MATCOM), 2021, vol. 184, issue C, 306-318

Abstract: This paper introduces deep learning-based forecasting models for the continuous prediction of the aggregated production generated by CSP plants in Spain. These models use as inputs the expected top of atmosphere irradiance values and available weather conditions forecasts for the locations where the main CSP power plants are installed. The performances of the forecast models are analysed and compared by means of the most extended metrics in the literature for a whole year of CSP energy production.

Keywords: Concentrated solar power; Deep learning; Neural networks; Forecasting (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:184:y:2021:i:c:p:306-318

DOI: 10.1016/j.matcom.2020.02.007

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