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An Improved Method for Obtaining Solar Irradiation Data at Temporal High-Resolution

Author

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  • Leocadio Hontoria

    (Department of Electronic and Automatic Engineering, University of Jaen, 23071 Jaen, Spain)

  • Catalina Rus-Casas

    (Department of Electronic and Automatic Engineering, University of Jaen, 23071 Jaen, Spain)

  • Juan Domingo Aguilar

    (Department of Electronic and Automatic Engineering, University of Jaen, 23071 Jaen, Spain)

  • Jesús C. Hernandez

    (Department of Electrical Engineering, University of Jaen, 23071 Jaen, Spain)

Abstract

Solar irradiation that is received on a terrestrial surface at minor scale of an hour does not have many records, since the current solar irradiation databases generally only have data recorded on a daily (most) and hourly (some less) scale. For places where there are no records of solar irradiation, there are a lot of methods that are used to synthetically or artificially generate these data, and again they are usually methods that generate data on a daily or hourly scale. Currently, for all types of applications, especially in the field of photovoltaic solar energy, irradiation data are needed at minor scale of an hour. In this case, there are very few methods to generate such data. For this purpose, a new methodology to generate series of solar irradiation at temporal high-resolution. In this paper, it is presented on a 10-min basis. A comparative study with real data has been done and the conclusion, as it will be explained is that the proposed methodology provides very good results.

Suggested Citation

  • Leocadio Hontoria & Catalina Rus-Casas & Juan Domingo Aguilar & Jesús C. Hernandez, 2019. "An Improved Method for Obtaining Solar Irradiation Data at Temporal High-Resolution," Sustainability, MDPI, vol. 11(19), pages 1-15, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5233-:d:270234
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    Cited by:

    1. Ajith, Meenu & Martínez-Ramón, Manel, 2021. "Deep learning based solar radiation micro forecast by fusion of infrared cloud images and radiation data," Applied Energy, Elsevier, vol. 294(C).
    2. Rafael Sánchez-Durán & Julio Barbancho & Joaquín Luque, 2019. "Solar Energy Production for a Decarbonization Scenario in Spain," Sustainability, MDPI, vol. 11(24), pages 1-29, December.
    3. Sun, Mucun & Feng, Cong & Zhang, Jie, 2020. "Probabilistic solar power forecasting based on weather scenario generation," Applied Energy, Elsevier, vol. 266(C).
    4. Arumugham, Dinesh Rajan & Rajendran, Parvathy, 2021. "Modelling global solar irradiance for any location on earth through regression analysis using high-resolution data," Renewable Energy, Elsevier, vol. 180(C), pages 1114-1123.

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