IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i20p5455-d431168.html
   My bibliography  Save this article

Sky Luminance Distribution Models: A Comparison with Measurements from a Maritime Desert Region

Author

Listed:
  • Khalid Alshaibani

    (College of Architecture and Planning, Imam Abdulrahman Bin Faisal University, Dammam 34212, Saudi Arabia)

  • Danny Li

    (Building Energy Research Group, Department of Architecture and Civil Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China)

  • Emmanuel Aghimien

    (Building Energy Research Group, Department of Architecture and Civil Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China)

Abstract

The effective use of daylight is a function of the luminance of the sky exposed to the glazing system. Therefore, accurate data about the luminance distribution of the sky are necessary for the optimum use of daylight. This paper compares seven models for estimating the angular sky luminance distribution. They were selected based on the ability to be used with all sky conditions and to determine the luminance of the sky from solar radiation. Measurements of solar radiation, sky luminance, and sky radiance were taken in a “maritime desert region” in Saudi Arabia. The results showed that the “Perez 93” model performed better than the other models tested, but there is a need for more studies to identify more accurate models for use in similar climatic conditions.

Suggested Citation

  • Khalid Alshaibani & Danny Li & Emmanuel Aghimien, 2020. "Sky Luminance Distribution Models: A Comparison with Measurements from a Maritime Desert Region," Energies, MDPI, vol. 13(20), pages 1-12, October.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:20:p:5455-:d:431168
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/20/5455/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/20/5455/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alshaibani, K.A., 2017. "Classification Standard Skies: The use of horizontal sky illuminance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 387-392.
    2. Vincenzo Costanzo & Gianpiero Evola & Luigi Marletta & Fabiana Pistone Nascone, 2018. "Application of Climate Based Daylight Modelling to the Refurbishment of a School Building in Sicily," Sustainability, MDPI, vol. 10(8), pages 1-19, July.
    3. Alshaibani, Khalid, 2001. "Potentiality of daylighting in a maritime desert climate: the Eastern coast of Saudi Arabia," Renewable Energy, Elsevier, vol. 23(2), pages 325-331.
    4. Noorian, Ali Mohammad & Moradi, Isaac & Kamali, Gholam Ali, 2008. "Evaluation of 12 models to estimate hourly diffuse irradiation on inclined surfaces," Renewable Energy, Elsevier, vol. 33(6), pages 1406-1412.
    5. 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.
    6. de Simón-Martín, Miguel & Alonso-Tristán, Cristina & Díez-Mediavilla, Montserrat, 2017. "Diffuse solar irradiance estimation on building's façades: Review, classification and benchmarking of 30 models under all sky conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 783-802.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. García, Ignacio & de Blas, Marian & Hernández, Begoña & Sáenz, Carlos & Torres, José Luis, 2021. "Diffuse irradiance on tilted planes in urban environments: Evaluation of models modified with sky and circumsolar view factors," Renewable Energy, Elsevier, vol. 180(C), pages 1194-1209.
    2. Ramírez-Faz, J. & López-Luque, R. & Casares, F.J., 2015. "Development of synthetic hemispheric projections suitable for assessing the sky view factor on vertical planes," Renewable Energy, Elsevier, vol. 74(C), pages 279-286.
    3. Mehleri, E.D. & Zervas, P.L. & Sarimveis, H. & Palyvos, J.A. & Markatos, N.C., 2010. "A new neural network model for evaluating the performance of various hourly slope irradiation models: Implementation for the region of Athens," Renewable Energy, Elsevier, vol. 35(7), pages 1357-1362.
    4. El-Sebaii, A.A. & Al-Hazmi, F.S. & Al-Ghamdi, A.A. & Yaghmour, S.J., 2010. "Global, direct and diffuse solar radiation on horizontal and tilted surfaces in Jeddah, Saudi Arabia," Applied Energy, Elsevier, vol. 87(2), pages 568-576, February.
    5. Piotr Michalak, 2021. "Modelling of Solar Irradiance Incident on Building Envelopes in Polish Climatic Conditions: The Impact on Energy Performance Indicators of Residential Buildings," Energies, MDPI, vol. 14(14), pages 1-27, July.
    6. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparison of empirical models to estimate monthly mean diffuse solar radiation from measured data: Case study for humid-subtropical climatic region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1326-1342.
    7. 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.
    8. Mostafa Sabbagh & Siraj Mandourah & Raghda Hareri, 2022. "Light Shelves Optimization for Daylight Improvement in Typical Public Classrooms in Saudi Arabia," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    9. Khalil, Samy A. & Shaffie, A.M., 2016. "Evaluation of transposition models of solar irradiance over Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 105-119.
    10. Voyant, Cyril & Muselli, Marc & Paoli, Christophe & Nivet, Marie-Laure, 2011. "Optimization of an artificial neural network dedicated to the multivariate forecasting of daily global radiation," Energy, Elsevier, vol. 36(1), pages 348-359.
    11. Cuce, Erdem & Riffat, Saffa B., 2015. "A state-of-the-art review on innovative glazing technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 695-714.
    12. Alberto Bocca & Luca Bergamasco & Matteo Fasano & Lorenzo Bottaccioli & Eliodoro Chiavazzo & Alberto Macii & Pietro Asinari, 2018. "Multiple-Regression Method for Fast Estimation of Solar Irradiation and Photovoltaic Energy Potentials over Europe and Africa," Energies, MDPI, vol. 11(12), pages 1-17, December.
    13. Jie Li & Qichao Ban & Xueming (Jimmy) Chen & Jiawei Yao, 2019. "Glazing Sizing in Large Atrium Buildings: A Perspective of Balancing Daylight Quantity and Visual Comfort," Energies, MDPI, vol. 12(4), pages 1-14, February.
    14. Antonio Peña-García, 2022. "An Approach for Lighting Calculations in Indoor Mirrored Facilities Based on Virtual Twin-Spaces," Sustainability, MDPI, vol. 14(19), pages 1-10, September.
    15. Okoye, Chiemeka Onyeka & Bahrami, Arian & Atikol, Ugur, 2018. "Evaluating the solar resource potential on different tracking surfaces in Nigeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1569-1581.
    16. Adnan Rasheed & Jong Won Lee & Hyun Woo Lee, 2018. "Development and Optimization of a Building Energy Simulation Model to Study the Effect of Greenhouse Design Parameters," Energies, MDPI, vol. 11(8), pages 1-19, August.
    17. Bayrakçı, Hilmi Cenk & Demircan, Cihan & Keçebaş, Ali, 2018. "The development of empirical models for estimating global solar radiation on horizontal surface: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2771-2782.
    18. Chinchilla, Monica & Santos-Martín, David & Carpintero-Rentería, Miguel & Lemon, Scott, 2021. "Worldwide annual optimum tilt angle model for solar collectors and photovoltaic systems in the absence of site meteorological data," Applied Energy, Elsevier, vol. 281(C).
    19. Gu, Wenbo & Li, Senji & Liu, Xing & Chen, Zhenwu & Zhang, Xiaochun & Ma, Tao, 2021. "Experimental investigation of the bifacial photovoltaic module under real conditions," Renewable Energy, Elsevier, vol. 173(C), pages 1111-1122.
    20. Iskander Tlili, 2015. "Renewable energy in Saudi Arabia: current status and future potentials," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 17(4), pages 859-886, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:20:p:5455-:d:431168. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.