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Identifying periods of clear sky direct normal irradiance

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  • Larrañeta, M.
  • Reno, M.J.
  • Lillo-Bravo, I.
  • Silva-Pérez, M.A.

Abstract

When modeling the effect of the cloud transients in the Direct Normal Insolation (DNI), it is particularly relevant to identify those moments in which there are no clouds between the observer and the sun. In this paper, we present a simple algorithm for offline detection of situations where the sun path to the observer is not obstructed by any cloud. The algorithm is based on the characterization of the relations between the measured and the clear sky curves. The clear sky identification module consists of three evaluation and detection metrics: hourly mean, slope, and line length criterion. All of them rely on the assessment of the measured data against the clear sky generated data. The conjunction of the fulfillment of the three criteria leads to the clear sky hour identification. We validate our algorithm by comparing our results with those obtained from a recently published clear sky detection algorithm that uses high temporal resolution Global Horizontal Irradiation (GHI) as the input. We obtain a 98% agreement when having more than 50 min identified as clear.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:113:y:2017:i:c:p:756-763
    DOI: 10.1016/j.renene.2017.06.011
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    References listed on IDEAS

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    1. Younes, S. & Muneer, T., 2007. "Clear-sky classification procedures and models using a world-wide data-base," Applied Energy, Elsevier, vol. 84(6), pages 623-645, June.
    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. Martínez-Chico, M. & Batlles, F.J. & Bosch, J.L., 2011. "Cloud classification in a mediterranean location using radiation data and sky images," Energy, Elsevier, vol. 36(7), pages 4055-4062.
    4. Gueymard, Christian A., 2005. "Importance of atmospheric turbidity and associated uncertainties in solar radiation and luminous efficacy modelling," Energy, Elsevier, vol. 30(9), pages 1603-1621.
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    Cited by:

    1. 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.
    2. 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.
    3. López-Alvarez, José A. & Larraneta, Miguel & Silva-Pérez, Manuel A. & Lillo-Bravo, Isidoro, 2020. "Impact of the variation of the receiver glass envelope transmittance as a function of the incidence angle in the performance of a linear Fresnel collector," Renewable Energy, Elsevier, vol. 150(C), pages 607-615.
    4. Gueymard, Christian A. & Bright, Jamie M. & Lingfors, David & Habte, Aron & Sengupta, Manajit, 2019. "A posteriori clear-sky identification methods in solar irradiance time series: Review and preliminary validation using sky imagers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 412-427.
    5. 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.
    6. Bright, Jamie M. & Sun, Xixi & Gueymard, Christian A. & Acord, Brendan & Wang, Peng & Engerer, Nicholas A., 2020. "Bright-Sun: A globally applicable 1-min irradiance clear-sky detection model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 121(C).
    7. 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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