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Quality control of diffuse solar radiation component with satellite-based estimation methods

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  • Ener Rusen, Selmin
  • Konuralp, Aycan

Abstract

In order to analyze solar systems, it is very important to determine the accurate solar radiation components belonging to any region. These components are defined as the beam and diffuse. The diffuse radiation component may not always be determined accurately since it is mostly affected by many geographical factors and climatic features in addition to the location parameters. Therefore, this work aims to compare and evaluate the validity of global and diffuse estimation methods for nine locations in Turkey. The satellite-based estimation methods (HELIOSAT, Meteonom, and PVGIS) mentioned in the literature were used to estimate global and diffuse radiation. These selected methods were statistically tested with accurate ground measured data. For HELIOSAT, the global radiation is varying −0.02 and 0.03, and 0.010 and 0.035, respectively, Relative MBE and Relative RMSE. Similarly, the diffuse radiation values are −0.020 and 0.025 for Relative MBE, and 0.015 and 0.030 for Relative RMSE. The goodness of the fit values for the HELIOSAT method shows a very good agreement with at least 97% confidence level of global and 91% of diffuse radiation values. Thus, HELIOSAT method shows a trustworthy alternative to the ground measurement data when reliable global and diffuse radiation data are not available.

Suggested Citation

  • Ener Rusen, Selmin & Konuralp, Aycan, 2020. "Quality control of diffuse solar radiation component with satellite-based estimation methods," Renewable Energy, Elsevier, vol. 145(C), pages 1772-1779.
    • Handle: RePEc:eee:renene:v:145:y:2020:i:c:p:1772-1779
    DOI: 10.1016/j.renene.2019.07.085
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    Cited by:

    1. Zhang, Hongjie & Yao, Runming & Luo, Qing & Wang, Wenbo, 2022. "A mathematical model for a rapid calculation of the urban canyon albedo and its applications," Renewable Energy, Elsevier, vol. 197(C), pages 836-851.
    2. Elena Esposito & Gianni Leanza & Girolamo Di Francia, 2024. "Comparative Analysis of Ground-Based Solar Irradiance Measurements and Copernicus Satellite Observations," Energies, MDPI, vol. 17(7), pages 1-21, March.
    3. Bakirci, Kadir, 2021. "Prediction of diffuse radiation in solar energy applications: Turkey case study and compare with satellite data," Energy, Elsevier, vol. 237(C).
    4. Clauzel, Léo & Anquetin, Sandrine & Lavaysse, Christophe & Tremoy, Guillaume & Raynaud, Damien, 2024. "West African operational daily solar forecast errors and their link with meteorological conditions," Renewable Energy, Elsevier, vol. 224(C).
    5. Starke, Allan R. & Lemos, Leonardo F.L. & Barni, Cristian M. & Machado, Rubinei D. & Cardemil, José M. & Boland, John & Colle, Sergio, 2021. "Assessing one-minute diffuse fraction models based on worldwide climate features," Renewable Energy, Elsevier, vol. 177(C), pages 700-714.
    6. Gao, Xiu-Yan & Huang, Chun-Lin & Zhang, Zhen-Huan & Chen, Qi-Xiang & Zheng, Yu & Fu, Di-Song & Yuan, Yuan, 2024. "Global horizontal irradiance prediction model for multi-site fusion under different aerosol types," Renewable Energy, Elsevier, vol. 227(C).
    7. Li, Peidu & Gao, Xiaoqing & Li, Zhenchao & Zhou, Xiyin, 2022. "Effect of the temperature difference between land and lake on photovoltaic power generation," Renewable Energy, Elsevier, vol. 185(C), pages 86-95.
    8. Boukelia, T.E. & Ghellab, A. & Laouafi, A. & Bouraoui, A. & Kabar, Y., 2020. "Cooling performances time series of CSP plants: Calculation and analysis using regression and ANN models," Renewable Energy, Elsevier, vol. 157(C), pages 809-827.
    9. Hassan, Muhammed A. & Akoush, Bassem M. & Abubakr, Mohamed & Campana, Pietro Elia & Khalil, Adel, 2021. "High-resolution estimates of diffuse fraction based on dynamic definitions of sky conditions," Renewable Energy, Elsevier, vol. 169(C), pages 641-659.

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