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Illuminance estimation and daylighting energy savings for Indian regions

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  • Singh, M.C.
  • Garg, S.N.

Abstract

In this manuscript, potential of daylighting in reducing electrical lighting load, has been explored. The analysis has been carried out for four different types of windows and for three different climatic conditions of India. Two Perez models have been used to estimate illuminance on horizontal and for vertical surfaces as this data is not available in India. Effect of different glazed areas, that of orientation and that of climatic conditions on the reduction in lighting load, has been analysed. The daylighting software, ADELINE 3.0, has been used for computation of lighting energy savings. It has been found that for a given climate and orientation, if the window visible transmittance is low (0.07 for reflective window and 0.20 for solar control window) the energy saved due to daylighting increases with the glazed area but if window transmittance is high (0.78 for double glazed clear window and 0.73 for double glazed low-e window) it almost remains constant with glazed area. Energy saved is highly dependent on the window type, being highest for double glazed clear glass window and lowest for reflective window. By using Perez model and by associating this with average daylight factor, daylighting energy savings have also been computed and compared with the ADELINE simulated results.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:35:y:2010:i:3:p:703-711
    DOI: 10.1016/j.renene.2009.08.023
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    References listed on IDEAS

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    6. Tíba, C. & Leal, S.S., 2012. "Measuring and modelling illuminance in the semi-arid Northeast of Brazil," Renewable Energy, Elsevier, vol. 48(C), pages 464-472.
    7. 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.

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