Estimation of Monthly Average Daily Global Solar Radiation Using Meteorological-Based Models in Adrar, Algeria

Almorox Alonso, Javier ORCID: https://orcid.org/0000-0003-1523-0979, Bouchouicha, Kada ORCID: https://orcid.org/0000-0001-8112-7545, Bailek, Nadjem ORCID: https://orcid.org/0000-0001-9051-8548, Mahmoud, Mohamed El-Shimy, Slimani, Abdeldjalil ORCID: https://orcid.org/0000-0001-8345-8321 and Djaafari, Abdallah (2018). Estimation of Monthly Average Daily Global Solar Radiation Using Meteorological-Based Models in Adrar, Algeria. "Applied Solar Energy", v. 54 (n. 6); pp. 448-455. ISSN 0003701X. https://doi.org/10.3103/S0003701X1806004X.

Descripción

Título: Estimation of Monthly Average Daily Global Solar Radiation Using Meteorological-Based Models in Adrar, Algeria
Autor/es:
Tipo de Documento: Artículo
Título de Revista/Publicación: Applied Solar Energy
Fecha: 1 Diciembre 2018
ISSN: 0003701X
Volumen: 54
Número: 6
Materias:
Palabras Clave Informales: Global solar radiation; Meteorological parameters; model estimation; Statistical Analysis
Escuela: E.T.S. de Ingeniería Agronómica, Alimentaria y de Biosistemas (UPM)
Departamento: Producción Agraria
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

© 2018, Allerton Press, Inc. Abstract: This paper presents a systematic approach to empirical model selection for the global solar radiation (GSR) estimation considering the Algerian town of Adrar. The approach is based on various meteorological variables. The accuracy of the selected model is validated using GSR measurements in the considered location (i.e. Adrar) through eight statistical indicators. Long-term six-parameter data measurements are collected. The collected measurements are divided into two subsets; the first subset (from year 2009 to 2013) is used for the modeling purpose, while the second subset (years 2014–2016) is used for the model evaluation purpose. The results show that the statistical performance of the traditional Angström formula for GSR estimation can be significantly improved by including the effect of the maximum and minimum temperatures in the GSR empirical models. In addition, the results show that excluding the cloud cover from the empirical models significantly reduces the statistical performance of these models.

Más información

ID de Registro: 91748
Identificador DC: https://oa.upm.es/91748/
Identificador OAI: oai:oa.upm.es:91748
URL Portal Científico: https://portalcientifico.upm.es/es/ipublic/item/5658384
Identificador DOI: 10.3103/S0003701X1806004X
URL Oficial: https://link.springer.com/article/10.3103/S0003701...
Depositado por: iMarina Portal Científico
Depositado el: 04 Nov 2025 09:25
Ultima Modificación: 04 Nov 2025 09:25