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Spatial estimation of global solar radiation using geostatistics

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  • Rehman, Shafiqur
  • Ghori, Saleem G

Abstract

The number of radiation data collection stations is limited due to economic reasons. Hence, there is a need for the spatially continuous mapping of solar radiation by estimation. This paper utilizes a geostatistical technique for the estimation of solar radiation in Saudi Arabia. This technique includes five steps: (i) data collection, (ii) univariate analysis, (iii) experimental variogram calculations and model fitting, (iv) estimation using kriging, and (v) plotting contour maps. Variogram models are fitted to measured variograms for each month of the year. Estimates were obtained at 1500 grid points (30 × 50) between a longitude of 36.58°E and 50.00°E, and latitude of 17.17°N and 31.33°N for a grid resolution of 55 × 33 km. These values were used to plot the contour maps of solar radiation for each month of the year. To test the performance of the technique, estimates were obtained at the 41 known locations by systematically excluding one of these points from the known data. The error analysis showed a maximum mean deviation between measured and estimated values of 0.0037 (January) and a minimum of 0.0013 (March and October). The mean percent errors were found to vary between a minimum of 0.5% and a maximum of 1.7%. This technique may be expanded for the spatial estimation of solar radiation on regional and continental scales.

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  • Rehman, Shafiqur & Ghori, Saleem G, 2000. "Spatial estimation of global solar radiation using geostatistics," Renewable Energy, Elsevier, vol. 21(3), pages 583-605.
    • Handle: RePEc:eee:renene:v:21:y:2000:i:3:p:583-605
    DOI: 10.1016/S0960-1481(00)00078-1
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    2. Jeong, D.I. & St-Hilaire, A. & Gratton, Y. & Bélanger, C. & Saad, C., 2017. "A guideline to select an estimation model of daily global solar radiation between geostatistical interpolation and stochastic simulation approaches," Renewable Energy, Elsevier, vol. 103(C), pages 70-80.
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    5. Bessafi, Miloud & Oree, Vishwamitra & Khoodaruth, Abdel & Chabriat, Jean-Pierre, 2020. "Impact of decomposition and kriging models on the solar irradiance downscaling accuracy in regions with complex topography," Renewable Energy, Elsevier, vol. 162(C), pages 1992-2003.
    6. Hepbasli, Arif & Alsuhaibani, Zeyad, 2011. "A key review on present status and future directions of solar energy studies and applications in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 5021-5050.
    7. Yang, Dazhi & Gu, Chaojun & Dong, Zibo & Jirutitijaroen, Panida & Chen, Nan & Walsh, Wilfred M., 2013. "Solar irradiance forecasting using spatial-temporal covariance structures and time-forward kriging," Renewable Energy, Elsevier, vol. 60(C), pages 235-245.
    8. Antonanzas-Torres, F. & Cañizares, F. & Perpiñán, O., 2013. "Comparative assessment of global irradiation from a satellite estimate model (CM SAF) and on-ground measurements (SIAR): A Spanish case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 248-261.
    9. Soulis, Konstantinos X. & Manolakos, Dimitris & Ntavou, Erika & Kosmadakis, George, 2022. "A geospatial analysis approach for the operational assessment of solar ORC systems. Case study: Performance evaluation of a two-stage solar ORC engine in Greece," Renewable Energy, Elsevier, vol. 181(C), pages 116-128.
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    11. Jing, Yifan & Zhu, Li & Yin, Baoquan & Li, Fangfang, 2023. "Evaluating the PV system expansion potential of existing integrated energy parks: A case study in North China," Applied Energy, Elsevier, vol. 330(PA).
    12. Walch, Alina & Castello, Roberto & Mohajeri, Nahid & Scartezzini, Jean-Louis, 2020. "Big data mining for the estimation of hourly rooftop photovoltaic potential and its uncertainty," Applied Energy, Elsevier, vol. 262(C).
    13. Sarmiento, Nilsa & Belmonte, Silvina & Dellicompagni, Pablo & Franco, Judith & Escalante, Karina & Sarmiento, Joaquín, 2019. "A solar irradiation GIS as decision support tool for the Province of Salta, Argentina," Renewable Energy, Elsevier, vol. 132(C), pages 68-80.
    14. Zagouras, Athanassios & Kolovos, Alexander & Coimbra, Carlos F.M., 2015. "Objective framework for optimal distribution of solar irradiance monitoring networks," Renewable Energy, Elsevier, vol. 80(C), pages 153-165.
    15. Pelosi, A. & Chirico, G.B., 2021. "Regional assessment of daily reference evapotranspiration: Can ground observations be replaced by blending ERA5-Land meteorological reanalysis and CM-SAF satellite-based radiation data?," Agricultural Water Management, Elsevier, vol. 258(C).
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