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Evaluation of High-Resolution Satellite-Derived Solar Radiation Data for PV Performance Simulation in East Africa

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  • Diane Palmer

    (Centre for Renewable Energy Systems Technology, Loughborough University, Loughborough LE11 3TU, UK)

  • Richard Blanchard

    (Centre for Renewable Energy Systems Technology, Loughborough University, Loughborough LE11 3TU, UK)

Abstract

Access to reliable, clean, modern cooking enhances life chances. One option is photovoltaic cooking systems. Accurate solar data are needed to ascertain to what extent these can satisfy the needs of local people. In this paper, we investigate how to choose the most accurate satellite-derived solar irradiance database for use in Africa. This is necessary because there is a general shortage of ground measurements for Africa. The solar data are needed to model the output of solar cooking systems, such as a solar panel, battery and electric pressure cooker. Four easily accessible global horizontal irradiation (GHI) satellite databases are validated against ground measurements using a range of statistical tests. The results demonstrate the impact of the mathematical measure used and the phenomenon of balancing errors. Fitting of the satellite model to the appropriate climate zone and/or nearby measurements improves accuracy, as does higher spatial and temporal resolution of input parameters. That said, all the four databases reviewed were found to be suitable for simulating PV yield in East Africa.

Suggested Citation

  • Diane Palmer & Richard Blanchard, 2021. "Evaluation of High-Resolution Satellite-Derived Solar Radiation Data for PV Performance Simulation in East Africa," Sustainability, MDPI, vol. 13(21), pages 1-24, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11852-:d:665547
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    References listed on IDEAS

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    1. Sun, Xixi & Bright, Jamie M. & Gueymard, Christian A. & Acord, Brendan & Wang, Peng & Engerer, Nicholas A., 2019. "Worldwide performance assessment of 75 global clear-sky irradiance models using Principal Component Analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 550-570.
    2. Gandoman, Foad H. & Abdel Aleem, Shady H.E. & Omar, Noshin & Ahmadi, Abdollah & Alenezi, Faisal Q., 2018. "Short-term solar power forecasting considering cloud coverage and ambient temperature variation effects," Renewable Energy, Elsevier, vol. 123(C), pages 793-805.
    3. Sun, Xixi & Bright, Jamie M. & Gueymard, Christian A. & Bai, Xinyu & Acord, Brendan & Wang, Peng, 2021. "Worldwide performance assessment of 95 direct and diffuse clear-sky irradiance models using principal component analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    4. Polo, J. & Antonanzas-Torres, F. & Vindel, J.M. & Ramirez, L., 2014. "Sensitivity of satellite-based methods for deriving solar radiation to different choice of aerosol input and models," Renewable Energy, Elsevier, vol. 68(C), pages 785-792.
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    Cited by:

    1. Mukelabai, Mulako Dean & Wijayantha, Upul K.G. & Blanchard, Richard E., 2022. "Renewable hydrogen economy outlook in Africa," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).

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