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Coupling satellite images with surface measurements of bright sunshine hours to estimate daily solar irradiation on horizontal surface

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  • Rusen, Selmin Ener
  • Hammer, Annette
  • Akinoglu, Bulent G.

Abstract

Satellite images are heavily used for the estimation of solar irradiation at the Earth's surface. The accuracy yet should be improved to attain more reliable input values for the use of all types of solar energy systems. This paper presents two new alternative approaches to increase the estimation accuracy of daily solar irradiation by coupling the satellite images with surface bright sunshine hour measurements. Two different approaches are described for the estimation of global solar irradiation on daily base, by using the data for some locations in Turkey and Germany. These approaches are compared with the estimation of a satellite model (HELIOSAT), Angstrom models and ground measured daily global solar irradiation by using regressions and error analyses. For nine out of ten stations the relative RMSE values of the proposed models slightly decrease in the range of only 2% in comparison with the direct satellite model for the daily global solar irradiation. The results obtained for the new approaches did not considerably improve the performance of the satellite model. However, it is possible to recommend new coupled approaches to estimate daily global solar irradiation because of their simpler calculation procedure. The results are encouraging for the future works to use long and short-term satellite image data together with the surface measured data to estimate the solar irradiation values.

Suggested Citation

  • Rusen, Selmin Ener & Hammer, Annette & Akinoglu, Bulent G., 2013. "Coupling satellite images with surface measurements of bright sunshine hours to estimate daily solar irradiation on horizontal surface," Renewable Energy, Elsevier, vol. 55(C), pages 212-219.
    • Handle: RePEc:eee:renene:v:55:y:2013:i:c:p:212-219
    DOI: 10.1016/j.renene.2012.12.019
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    References listed on IDEAS

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    1. Akinoǧlu, B.G., 1991. "A review of sunshine-based models used to estimate monthly average global solar radiation," Renewable Energy, Elsevier, vol. 1(3), pages 479-497.
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    1. Yıldırım, H. Başak & Teke, Ahmet & Antonanzas-Torres, Fernando, 2018. "Evaluation of classical parametric models for estimating solar radiation in the Eastern Mediterranean region of Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2053-2065.
    2. Liu, Yujun & Yao, Ling & Jiang, Hou & Lu, Ning & Qin, Jun & Liu, Tang & Zhou, Chenghu, 2022. "Spatial estimation of the optimum PV tilt angles in China by incorporating ground with satellite data," Renewable Energy, Elsevier, vol. 189(C), pages 1249-1258.
    3. Yao, Wanxiang & Zhang, Chunxiao & Hao, Haodong & Wang, Xiao & Li, Xianli, 2018. "A support vector machine approach to estimate global solar radiation with the influence of fog and haze," Renewable Energy, Elsevier, vol. 128(PA), pages 155-162.
    4. Paulescu, Marius & Paulescu, Eugenia, 2019. "Short-term forecasting of solar irradiance," Renewable Energy, Elsevier, vol. 143(C), pages 985-994.
    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. Ener Rusen, Selmin & Hammer, Annette & Akinoglu, Bulent G., 2013. "Estimation of daily global solar irradiation by coupling ground measurements of bright sunshine hours to satellite imagery," Energy, Elsevier, vol. 58(C), pages 417-425.
    7. Teke, Ahmet & Yıldırım, H. Başak & Çelik, Özgür, 2015. "Evaluation and performance comparison of different models for the estimation of solar radiation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1097-1107.
    8. Liu, Hongda & Li, Lun & Han, Yang & Lu, Fang, 2019. "Method of identifying the lengths of equivalent clear-sky periods in the time series of DNI measurements based on generalized atmospheric turbidity," Renewable Energy, Elsevier, vol. 136(C), pages 179-192.
    9. 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).
    10. 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.
    11. 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.

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