Ultraviolet Erythemal Irradiance (UVER) under Different Sky Conditions in Burgos, Spain: Multilinear Regression and Artificial Neural Network Models
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Published:2023-10-05
Issue:19
Volume:13
Page:10979
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ISSN:2076-3417
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Container-title:Applied Sciences
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language:en
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Short-container-title:Applied Sciences
Author:
García-Rodríguez S.1ORCID, García-Rodríguez A.1ORCID, Granados-López D.1ORCID, García I.12ORCID, Alonso-Tristán C.1ORCID
Affiliation:
1. Research Group Solar and Wind Feasibility Technologies (SWIFT), Electromechanical Engineering Department, Universidad de Burgos, Escuela Politécnica Superior, 09006 Burgos, Spain 2. Institute of Smart Cities (ISC), Engineering Department, Universidad Pública de Navarra, Campus Arrosadía, Pamplona 31006, Spain
Abstract
Different strategies for modeling Global Horizontal UltraViolet Erythemal irradiance (GHUVE) based on meteorological parameters measured in Burgos (Spain) have been developed. The experimental campaign ran from September 2020 to June 2022. The selection of relevant variables for modeling was based on Pearson’s correlation coefficient. Multilinear Regression Model (MLR) and artificial neural network (ANN) techniques were employed to model GHUVE under different sky conditions (all skies, overcast, intermediate, and clear skies), classified according to the CIE standard on a 10 min basis. ANN models of GHUVE outperform those based on MLR according to the traditional statistical indices used in this study (R2, MBE, and nRMSE). Moreover, the work proposes a simple all-sky ANN model of GHUVE based on usually recorded variables at ground meteorological stations.
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
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