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Method of identifying the lengths of equivalent clear-sky periods in the time series of DNI measurements based on generalized atmospheric turbidity

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  • Liu, Hongda
  • Li, Lun
  • Han, Yang
  • Lu, Fang

Abstract

In photovoltaic (PV) power plant construction, solar resources need to be evaluated using some criteria. Besides considering the classical total amount of solar resources at the considered location, the lengths and distributions of equivalent clear-sky periods have also been taken into account in recent years to consider the stability of both the PV system output power and other connected grids. We present a method of identifying the lengths and distributions of equivalent clear-sky periods using time series of direct normal irradiance (DNI) measurements based on generalized atmospheric turbidity. This method can be employed not only to calculate the lengths and distributions of historical equivalent clear-sky periods, but also for real-time equivalent clear-sky condition detection. In this report, we demonstrate the validity our algorithm using data from the Solar Radiation Research Laboratory (39.74°N, 105.18°W) and compare our results with those obtained using the Reno and Hansen algorithm.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:renene:v:136:y:2019:i:c:p:179-192
    DOI: 10.1016/j.renene.2018.12.119
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    References listed on IDEAS

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    1. Dahmani, Kahina & Notton, Gilles & Voyant, Cyril & Dizene, Rabah & Nivet, Marie Laure & Paoli, Christophe & Tamas, Wani, 2016. "Multilayer Perceptron approach for estimating 5-min and hourly horizontal global irradiation from exogenous meteorological data in locations without solar measurements," Renewable Energy, Elsevier, vol. 90(C), pages 267-282.
    2. Rusen, Selmin Ener & Hammer, Annette & Akinoglu, Bulent G., 2013. "Coupling satellite images with surface measurements of bright sunshine hours to estimate daily solar irradiation on horizontal surface," Renewable Energy, Elsevier, vol. 55(C), pages 212-219.
    3. Brandt, Adam R., 2010. "Review of mathematical models of future oil supply: Historical overview and synthesizing critique," Energy, Elsevier, vol. 35(9), pages 3958-3974.
    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. Aguiar, L. Mazorra & Pereira, B. & Lauret, P. & Díaz, F. & David, M., 2016. "Combining solar irradiance measurements, satellite-derived data and a numerical weather prediction model to improve intra-day solar forecasting," Renewable Energy, Elsevier, vol. 97(C), pages 599-610.
    6. Doljak, Dejan & Stanojević, Gorica, 2017. "Evaluation of natural conditions for site selection of ground-mounted photovoltaic power plants in Serbia," Energy, Elsevier, vol. 127(C), pages 291-300.
    7. 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.
    8. Cucumo, M. & De Rosa, A. & Ferraro, V. & Kaliakatsos, D. & Marinelli, V., 2010. "Correlations of direct solar luminous efficacy for all sky, clear sky and intermediate sky conditions and comparisons with experimental data of five localities," Renewable Energy, Elsevier, vol. 35(10), pages 2143-2156.
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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. Ruiz-Arias, José A., 2022. "Spectral integration of clear-sky atmospheric transmittance: Review and worldwide performance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    3. Garniwa, Pranda M.P. & Lee, Hyunjin, 2023. "Intercomparison of the parameterized Linke turbidity factor in deriving global horizontal irradiance," Renewable Energy, Elsevier, vol. 212(C), pages 285-298.

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