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Cloud classification in a mediterranean location using radiation data and sky images

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  • Martínez-Chico, M.
  • Batlles, F.J.
  • Bosch, J.L.

Abstract

Knowledge regarding the solar radiation reaching the earth’s surface and its geographical distribution is very important for the use of solar energy as a resource to produce electricity. Therefore, a proper assessment of available solar resource is particularly important to determine the placement and operation of solar thermal power plants. To perform this analysis correctly, it is necessary to determine the main factors influencing the radiation reaching the earth’s surface, such as the earth’s geometry, terrain, and atmospheric attenuation by gases, particles and clouds. Among these factors, it is important to emphasise the role of clouds as the main attenuating factor of radiation. Information about the amount and type of clouds present in the sky is therefore necessary to analyse both their attenuation levels and the prevalence of different sky conditions. Cloud cover is characterised according to attenuation levels, using the beam transmittance (kb, ratio of direct radiation incident on the surface to the extraterrestrial solar radiation) and hemispherical sky images. An analysis of the frequency and duration of each type of cloud cover blocking the sun’s disk is also performed. Results show prevailing sky situations that make the studied area very suitable for the use of solar energy systems.

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  • 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.
  • Handle: RePEc:eee:energy:v:36:y:2011:i:7:p:4055-4062
    DOI: 10.1016/j.energy.2011.04.043
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    References listed on IDEAS

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    1. Zarzalejo, Luis F. & Ramirez, Lourdes & Polo, Jesus, 2005. "Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index," Energy, Elsevier, vol. 30(9), pages 1685-1697.
    2. Olmo, F.J & Vida, J & Foyo, I & Castro-Diez, Y & Alados-Arboledas, L, 1999. "Prediction of global irradiance on inclined surfaces from horizontal global irradiance," Energy, Elsevier, vol. 24(8), pages 689-704.
    3. Sabziparvar, Ali A. & Shetaee, H., 2007. "Estimation of global solar radiation in arid and semi-arid climates of East and West Iran," Energy, Elsevier, vol. 32(5), pages 649-655.
    4. Bosch, J.L. & Batlles, F.J. & Zarzalejo, L.F. & López, G., 2010. "Solar resources estimation combining digital terrain models and satellite images techniques," Renewable Energy, Elsevier, vol. 35(12), pages 2853-2861.
    5. Tovar, J & Olmo, F.J & Batlles, F.J & Alados-Arboledas, L, 2001. "Dependence of one-minute global irradiance probability density distributions on hourly irradiation," Energy, Elsevier, vol. 26(7), pages 659-668.
    6. Markou, M.T. & Kambezidis, H.D. & Bartzokas, A. & Katsoulis, B.D. & Muneer, T., 2005. "Sky type classification in Central England during winter," Energy, Elsevier, vol. 30(9), pages 1667-1674.
    7. Fricker, H.W., 2004. "Regenerative thermal storage in atmospheric air system solar power plants," Energy, Elsevier, vol. 29(5), pages 871-881.
    8. Robaa, S.M., 2008. "Evaluation of sunshine duration from cloud data in Egypt," Energy, Elsevier, vol. 33(5), pages 785-795.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

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    10. Alonso-Montesinos, J. & Batlles, F.J., 2015. "Solar radiation forecasting in the short- and medium-term under all sky conditions," Energy, Elsevier, vol. 83(C), pages 387-393.
    11. Dong, Zibo & Yang, Dazhi & Reindl, Thomas & Walsh, Wilfred M., 2013. "Short-term solar irradiance forecasting using exponential smoothing state space model," Energy, Elsevier, vol. 55(C), pages 1104-1113.
    12. 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.
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    15. Trigo-González, Mauricio & Cortés-Carmona, Marcelo & Marzo, Aitor & Alonso-Montesinos, Joaquín & Martínez-Durbán, Mercedes & López, Gabriel & Portillo, Carlos & Batlles, Francisco Javier, 2023. "Photovoltaic power electricity generation nowcasting combining sky camera images and learning supervised algorithms in the Southern Spain," Renewable Energy, Elsevier, vol. 206(C), pages 251-262.
    16. Tingzhen Ming & Shengnan Lian & Yongjia Wu & Tianhao Shi & Chong Peng & Yueping Fang & Renaud de Richter & Nyuk Hien Wong, 2021. "Numerical Investigation on the Urban Heat Island Effect by Using a Porous Media Model," Energies, MDPI, vol. 14(15), pages 1-23, August.
    17. Alonso, J. & Batlles, F.J. & López, G. & Ternero, A., 2014. "Sky camera imagery processing based on a sky classification using radiometric data," Energy, Elsevier, vol. 68(C), pages 599-608.
    18. Alonso-Montesinos, J. & Martínez-Durbán, M. & del Sagrado, J. & del Águila, I.M. & Batlles, F.J., 2016. "The application of Bayesian network classifiers to cloud classification in satellite images," Renewable Energy, Elsevier, vol. 97(C), pages 155-161.
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