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A network of sky imagers for spatial solar irradiance assessment

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  • Chu, Yinghao
  • Li, Mengying
  • Pedro, Hugo T.C.
  • Coimbra, Carlos F.M.

Abstract

A network of seven low-cost hemispheric sky-imaging cameras has been installed in the Los Angeles basin. This network of cameras provides wide sky coverage to perform spatial solar irradiance assessments. An Image to Irradiance algorithm (I2I) is proposed to simultaneously derive high-resolution diffuse, direct and global solar irradiance from sky images. Spatial interpolation using the Kriging method is used to derive the irradiance field for the whole basin area. The relatively inexpensive network of cameras can provide spatially resolved GHI that is more accurate than GHI derived from GOES-west satellite images provided by the Cooperative Institute for Meteorological Satellite Studies (CIMSS) when the distance to the nearest site is less than 40 km. This work successfully demonstrates that, with minor trade-off in accuracy, solar irradiance monitoring can be achieved using off-the-shelf cameras in the absence of radiometers.

Suggested Citation

  • Chu, Yinghao & Li, Mengying & Pedro, Hugo T.C. & Coimbra, Carlos F.M., 2022. "A network of sky imagers for spatial solar irradiance assessment," Renewable Energy, Elsevier, vol. 187(C), pages 1009-1019.
    • Handle: RePEc:eee:renene:v:187:y:2022:i:c:p:1009-1019
    DOI: 10.1016/j.renene.2022.01.032
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    References listed on IDEAS

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    1. Chu, Yinghao & Li, Mengying & Coimbra, Carlos F.M., 2016. "Sun-tracking imaging system for intra-hour DNI forecasts," Renewable Energy, Elsevier, vol. 96(PA), pages 792-799.
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    10. García-Domingo, B. & Piliougine, M. & Elizondo, D. & Aguilera, J., 2015. "CPV module electric characterisation by artificial neural networks," Renewable Energy, Elsevier, vol. 78(C), pages 173-181.
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    Cited by:

    1. Zhang, Liwenbo & Wilson, Robin & Sumner, Mark & Wu, Yupeng, 2023. "Advanced multimodal fusion method for very short-term solar irradiance forecasting using sky images and meteorological data: A gate and transformer mechanism approach," Renewable Energy, Elsevier, vol. 216(C).
    2. Chu, Yinghao & Wang, Yiling & Yang, Dazhi & Chen, Shanlin & Li, Mengying, 2024. "A review of distributed solar forecasting with remote sensing and deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 198(C).
    3. Mercier, Thomas M. & Sabet, Amin & Rahman, Tasmiat, 2024. "Vision transformer models to measure solar irradiance using sky images in temperate climates," Applied Energy, Elsevier, vol. 362(C).

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