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Identifying overcast, partly cloudy and clear skies by illuminance fluctuations

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  • Lou, Siwei
  • Li, Danny.H.W.
  • Chen, Wenqiang

Abstract

The overcast, partly cloudy and clear sky conditions can determine the diffuse sky radiance and luminance distributions over the sky dome, and thus are crucial for evaluating the solar energy and daylight on and through building envelopes. It is preferable to properly identify the sky condition and determining its diffuse radiance and luminance distribution patterns by the readily available data. In this work, we propose a new approach to identifying the sky conditions, especially the cloudy and clear skies mainly by the horizontal illuminance fluctuation frequency. Illuminance on ground level may fluctuate at high frequency under cloudy skies due to the broken cloud, while vary smoothly under clear skies with few cloud blockages. For input data, the proposed approach needs the horizontal global illuminance that can be readily accessible for many places instead of the “uncommon” measurements on vertical planes or in sky zenith. The fluctuation frequency factor we propose can reduce the misclassification rate for daily and half-day representative sky conditions by 5.7% and 11.5%, respectively, compared to the classifications using the clearness index only.

Suggested Citation

  • Lou, Siwei & Li, Danny.H.W. & Chen, Wenqiang, 2019. "Identifying overcast, partly cloudy and clear skies by illuminance fluctuations," Renewable Energy, Elsevier, vol. 138(C), pages 198-211.
    • Handle: RePEc:eee:renene:v:138:y:2019:i:c:p:198-211
    DOI: 10.1016/j.renene.2019.01.080
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    References listed on IDEAS

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    1. Li, Danny H.W. & Chau, T.C. & Wan, Kevin K.W., 2014. "A review of the CIE general sky classification approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 563-574.
    2. Reno, Matthew J. & Hansen, Clifford W., 2016. "Identification of periods of clear sky irradiance in time series of GHI measurements," Renewable Energy, Elsevier, vol. 90(C), pages 520-531.
    3. Orehounig, Kristina & Dervishi, Sokol & Mahdavi, Ardeshir, 2014. "Computational derivation of irradiance on building surfaces: An empirically-based model comparison," Renewable Energy, Elsevier, vol. 71(C), pages 185-192.
    4. Larrañeta, M. & Reno, M.J. & Lillo-Bravo, I. & Silva-Pérez, M.A., 2017. "Identifying periods of clear sky direct normal irradiance," Renewable Energy, Elsevier, vol. 113(C), pages 756-763.
    5. Lou, Siwei & Li, Danny H.W. & Lam, Joseph C., 2017. "CIE Standard Sky classification by accessible climatic indices," Renewable Energy, Elsevier, vol. 113(C), pages 347-356.
    6. Li, Danny H.W. & Cheung, Gary H.W., 2005. "Study of models for predicting the diffuse irradiance on inclined surfaces," Applied Energy, Elsevier, vol. 81(2), pages 170-186, June.
    7. Sun, Yanyi & Wilson, Robin & Wu, Yupeng, 2018. "A Review of Transparent Insulation Material (TIM) for building energy saving and daylight comfort," Applied Energy, Elsevier, vol. 226(C), pages 713-729.
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    Cited by:

    1. Lou, Siwei & Huang, Yu & Li, Danny H.W. & Xia, Dawei & Zhou, Xiaoqing & Zhao, Yang, 2020. "A novel method for fast sky conditions identification from global solar radiation measurements," Renewable Energy, Elsevier, vol. 161(C), pages 77-90.
    2. Lou, Siwei & Li, Danny H.W. & Alshaibani, Khalid A. & Xing, Haowei & Li, Zhengrong & Huang, Yu & Xia, Dawei, 2022. "An all-sky luminance and radiance distribution model for built environment studies," Renewable Energy, Elsevier, vol. 190(C), pages 822-835.
    3. Lillo-Bravo, I. & Larrañeta, M. & Núñez-Ortega, E. & González-Galván, R., 2020. "Simplified model to correct thermopile pyranometer solar radiation measurements for photovoltaic module yield estimation," Renewable Energy, Elsevier, vol. 146(C), pages 1486-1497.

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