IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v66y2014icp111-117.html
   My bibliography  Save this article

Modeling the luminous efficacy of direct and diffuse solar radiation using information on cloud, aerosol and water vapor in the tropics

Author

Listed:
  • Janjai, S.
  • Prathumsit, J.
  • Buntoung, S.
  • Wattan, R.
  • Pattarapanitchai, S.
  • Masiri, I.

Abstract

This paper presents luminous efficacy models for direct and diffuse solar irradiance using information on cloud, aerosol and water vapor in the tropics. The model is based on five years (2007–2011) of diffuse illuminance and irradiance measurements and two years of direct illuminance and irradiance measurements, April 2010–March 2012. Data are taken at four solar radiation monitoring stations in Thailand, specifically Chiang Mai (18.78 °N, 98.98 °E) in the Northern region, Ubon Ratchathani (15.25 °N, 104.87 °E) in the Northeastern region, Nakhon Pathom (13.82 °N, 100.04 °E) in the Central region and Songkhla (7.20 °N, 100.60 °E) in the Southern region. The models express luminous efficacy as functions of the aerosol optical depth and precipitable water, obtained from the AERONET network, and a cloud index for hourly time scales derived from the MTSAT-1R satellite. The model performance is good when validated against independent data from these stations. Root mean square differences (RMSD) of 9.7% and 6.8% for direct normal efficacy and diffuse efficacy, respectively are obtained. The models compared favorably with most existing models when tested against these independent data.

Suggested Citation

  • Janjai, S. & Prathumsit, J. & Buntoung, S. & Wattan, R. & Pattarapanitchai, S. & Masiri, I., 2014. "Modeling the luminous efficacy of direct and diffuse solar radiation using information on cloud, aerosol and water vapor in the tropics," Renewable Energy, Elsevier, vol. 66(C), pages 111-117.
    • Handle: RePEc:eee:renene:v:66:y:2014:i:c:p:111-117
    DOI: 10.1016/j.renene.2013.11.070
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148113006587
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2013.11.070?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Robledo, Luis & Soler, Alfonso, 2001. "Luminous efficacy of direct solar radiation for all sky types," Energy, Elsevier, vol. 26(7), pages 669-677.
    2. Li, Danny H.W., 2010. "A review of daylight illuminance determinations and energy implications," Applied Energy, Elsevier, vol. 87(7), pages 2109-2118, July.
    3. Singh, M.C. & Garg, S.N., 2010. "Illuminance estimation and daylighting energy savings for Indian regions," Renewable Energy, Elsevier, vol. 35(3), pages 703-711.
    4. Tsikaloudaki, Katerina, 2005. "A study on luminous efficacy of global radiation under clear sky conditions in Athens, Greece," Renewable Energy, Elsevier, vol. 30(4), pages 551-563.
    5. Greenup, P & Bell, J.M & Moore, I, 2001. "The importance of interior daylight distribution in buildings on overall energy performance," Renewable Energy, Elsevier, vol. 22(1), pages 45-52.
    6. Cucumo, M. & De Rosa, A. & Ferraro, V. & Kaliakatsos, D. & Marinelli, V., 2008. "Correlations of global and diffuse solar luminous efficacy for all sky conditions and comparisons with experimental data of five localities," Renewable Energy, Elsevier, vol. 33(9), pages 2036-2047.
    7. Robledo, Luis & Soler, Alfonso, 2000. "Luminous efficacy of direct solar radiation for clear skies," Energy, Elsevier, vol. 25(8), pages 689-701.
    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.
    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. Ramedani, Zeynab & Omid, Mahmoud & Keyhani, Alireza & Shamshirband, Shahaboddin & Khoshnevisan, Benyamin, 2014. "Potential of radial basis function based support vector regression for global solar radiation prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 1005-1011.
    2. Purohit, Ishan & Purohit, Pallav, 2015. "Inter-comparability of solar radiation databases in Indian context," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 735-747.
    3. Li, Danny H.W. & Aghimien, Emmanuel I. & Tsang, Ernest K.W., 2022. "Application of artificial neural networks in horizontal luminous efficacy modeling," Renewable Energy, Elsevier, vol. 197(C), pages 864-878.
    4. Cheng, Xinghong & Ye, Dong & Shen, Yanbo & Li, Deping & Feng, Jinming, 2022. "Studies on the improvement of modelled solar radiation and the attenuation effect of aerosol using the WRF-Solar model with satellite-based AOD data over north China," Renewable Energy, Elsevier, vol. 196(C), pages 358-365.
    5. Wang, Lunche & Lu, Yunbo & Zou, Ling & Feng, Lan & Wei, Jing & Qin, Wenmin & Niu, Zigeng, 2019. "Prediction of diffuse solar radiation based on multiple variables in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 151-216.

    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. Pattarapanitchai, S. & Janjai, S. & Tohsing, K. & Prathumsit, J., 2015. "A technique to map monthly average global illuminance from satellite data in the tropics using a simple semi-empirical model," Renewable Energy, Elsevier, vol. 74(C), pages 170-175.
    2. Barbón, A. & Sánchez-Rodríguez, J.A. & Bayón, L. & Barbón, N., 2018. "Development of a fiber daylighting system based on a small scale linear Fresnel reflector: Theoretical elements," Applied Energy, Elsevier, vol. 212(C), pages 733-745.
    3. Li, Danny H.W. & Lam, Tony N.T. & Cheung, K.L. & Tang, H.L., 2008. "An analysis of luminous efficacies under the CIE standard skies," Renewable Energy, Elsevier, vol. 33(11), pages 2357-2365.
    4. Li, Danny H.W. & Lou, Siwei, 2018. "Review of solar irradiance and daylight illuminance modeling and sky classification," Renewable Energy, Elsevier, vol. 126(C), pages 445-453.
    5. Robledo, L. & Soler, A., 2002. "A simple clear skies model for the luminous efficacy of diffuse solar radiation on inclined surfaces," Renewable Energy, Elsevier, vol. 26(2), pages 169-176.
    6. 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.
    7. Alrubaih, M.S. & Zain, M.F.M. & Alghoul, M.A. & Ibrahim, N.L.N. & Shameri, M.A. & Elayeb, Omkalthum, 2013. "Research and development on aspects of daylighting fundamentals," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 494-505.
    8. Das, Aparna & Paul, Saikat Kumar, 2015. "Artificial illumination during daytime in residential buildings: Factors, energy implications and future predictions," Applied Energy, Elsevier, vol. 158(C), pages 65-85.
    9. Li, Danny H.W., 2010. "A review of daylight illuminance determinations and energy implications," Applied Energy, Elsevier, vol. 87(7), pages 2109-2118, July.
    10. Acosta, Ignacio & Munoz, Carmen & Campano, Miguel Angel & Navarro, Jaime, 2015. "Analysis of daylight factors and energy saving allowed by windows under overcast sky conditions," Renewable Energy, Elsevier, vol. 77(C), pages 194-207.
    11. Chi, Fang'ai & Zhang, Jianxun & Li, Gaomei & Zhu, Zongzhou & Bart, Dewancker, 2019. "An investigation of the impact of Building Azimuth on energy consumption in sizhai traditional dwellings," Energy, Elsevier, vol. 180(C), pages 594-614.
    12. Nataša Šprah & Mitja Košir, 2019. "Daylight Provision Requirements According to EN 17037 as a Restriction for Sustainable Urban Planning of Residential Developments," Sustainability, MDPI, vol. 12(1), pages 1-22, December.
    13. Aniela Kaminska, 2020. "Impact of Building Orientation on Daylight Availability and Energy Savings Potential in an Academic Classroom," Energies, MDPI, vol. 13(18), pages 1-17, September.
    14. Sun, Yanyi & Liang, Runqi & Wu, Yupeng & Wilson, Robin & Rutherford, Peter, 2017. "Development of a comprehensive method to analyse glazing systems with Parallel Slat Transparent Insulation material (PS-TIM)," Applied Energy, Elsevier, vol. 205(C), pages 951-963.
    15. Soler, A & Gopinathan, K.K & Claros, S.T, 2001. "A study on zenith luminance on Madrid overcast skies," Renewable Energy, Elsevier, vol. 23(1), pages 49-55.
    16. Jenkins, David & Newborough, Marcus, 2007. "An approach for estimating the carbon emissions associated with office lighting with a daylight contribution," Applied Energy, Elsevier, vol. 84(6), pages 608-622, June.
    17. Chel, Arvind & Tiwari, G.N. & Chandra, Avinash, 2009. "A model for estimation of daylight factor for skylight: An experimental validation using pyramid shape skylight over vault roof mud-house in New Delhi (India)," Applied Energy, Elsevier, vol. 86(11), pages 2507-2519, November.
    18. Janjai, S. & Sricharoen, K. & Pattarapanitchai, S., 2011. "Semi-empirical models for the estimation of clear sky solar global and direct normal irradiances in the tropics," Applied Energy, Elsevier, vol. 88(12), pages 4749-4755.
    19. Aniela Kaminska & Andrzej Ożadowicz, 2018. "Lighting Control Including Daylight and Energy Efficiency Improvements Analysis," Energies, MDPI, vol. 11(8), pages 1-18, August.
    20. Suk-jin Jung & Seong-hwan Yoon, 2018. "Study on the Prediction and Improvement of Indoor Natural Light and Outdoor Comfort in Apartment Complexes Using Daylight Factor and Physiologically Equivalent Temperature Indices," Energies, MDPI, vol. 11(7), pages 1-19, July.

    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:eee:renene:v:66:y:2014:i:c:p:111-117. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.