Simulative Prediction of Solar Illuminance and Application of the Du-Sharples Model in Estimating Adapted Daylighting Metrics for an Urban Environment

Bhattacharya, Sourin; Roy, Subarna; Majumder, Sudipta; Majumder, Sanjib

doi:10.33383/2024-004

Simulative Prediction of Solar Illuminance and Application of the Du-Sharples Model in Estimating Adapted Daylighting Metrics for an Urban Environment

Journal Article · Thu Aug 01 00:00:00 EDT 2024 · Light & Engineering

DOI:https://doi.org/10.33383/2024-004· OSTI ID:2582936

Bhattacharya, Sourin ^[1]; Roy, Subarna ^[2]; Majumder, Sudipta ^[3]; Majumder, Sanjib ^[4]

Indian Science Congress Association
Bengal Institute of Technology and Management,
Institution of Engineers (India)
Indian Institute of Technology Madras

The practice of daylighting in indoor spaces can significantly reduce electricity consumption and carbon emissions, improve human productivity, and enhance mood and cognitive perception. This work discussed the recent developments in daylighting science and practice, computed the periodic variations in average diurnal daylight levels for each month, quantified in terms of global horizontal illuminance and diffuse horizontal illuminance, for Kolkata, India, a city with tropical wet and dry climate, with two empirical luminous efficacy models of estimating solar illuminance, and assessed daylighting metrics with the Du-Sharples model. A program was formulated that could compute and generate daylight data with monthly-hourly solar irradiation data and the Du-Sharples model was utilized to predict dirt-corrected daylighting metrics for three glazing transmittance values and five elemental carbon deposition levels on glazing material. The highest monthly average global horizontal illuminance is recorded in April (64.05 klx for Littlefair model and 66.82 klx for Muneer-Kinghorn model) and the highest monthly average diffuse horizontal illuminance is recorded in July (33.23 klx for Littlefair model and 30.63 klx for Muneer-Kinghorn model). Further, the computed yearly average global and diffuse horizontal illuminance levels agree well with a previous study that applied the Perez model. Yearly average horizontal work surface illuminance level remained >1.5 klx for window-towall area ratio >30 %. The approach adopted in this work and the temporal variation charts of computed exterior daylight level data may assist building service engineers, architects, and indoor lighting practitioners in making informed policy decisions at different stages of building planning.

Research Organization:: National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE

DOE Contract Number:: AC36-08GO28308

OSTI ID:: 2582936

Journal Information:: Light & Engineering, Journal Name: Light & Engineering Journal Issue: 04 Vol. 32; ISSN 0236-2945

Publisher:: Znack Publishing House

Country of Publication:: United States

Language:: English

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