Parametric Optimization Approach to Evaluate Dynamic Shading Within Double-Skin Insulated Glazed Units for Multi-Criteria Daylighting Performance in Tropics

Ali Ahmed Bahdad; Nooriati Taib; Fahad Saud Allahaim; Ali Mohammed Ajlan

doi:10.15627/jd.2024.24

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Parametric Optimization Approach to Evaluate Dynamic Shading Within Double-Skin Insulated Glazed Units for Multi-Criteria Daylighting Performance in Tropics

Author(s)

Ali Ahmed Bahdad School of Housing,Building and Planning, Universiti Sains Malaysia, 11800, Penang,Malaysia

Nooriati Taib School of Housing,Building and Planning, Universiti Sains Malaysia, 11800, Penang,Malaysia

Fahad Saud Allahaim Department of Architecture and Building Science, College of Architecture and Planning, King Saud University,Riyadh 11421,Saudi Arabia

Ali Mohammed Ajlan Department of Architecture and Building Science, College of Architecture and Planning, King Saud University,Riyadh 11421,Saudi Arabia

Abstract

This research aims to support the choice of an appropriate dynamic louver shading system (DL-SS) within double-skin facade insulated glazed units (DSF-IGUs) as a high-performance integrated window system (DSF-IGUs/DL-SS) that meets both thermal and energy performance via daylight availability under a tropical climate. The research framework has developed a multi-objective optimization method to achieve research objectives via optimizing two different scenarios of the proposed system. The first scenario was optimized for daylighting availability, meanwhile, the second scenario was optimized for energy and thermal performance. For each scenario, the best solutions are selected from respective Pareto fronts according to energy efficiency criteria, thermal comfort via enhancing daylighting availability. Based on the best options resulting from both optimizations, the final step involved comparing the results of all performance indicators in the best cases to select the best solution. Overall, based on the optimizing objectives, the ranking of the best cases varied based on giving priority to the improvement objective in the optimization process. For each scenario, the best solutions are selected from the respective Pareto fronts. Overall, ranking of the best cases varied based on giving priority to the improvement objectives. Optimizing DL-SS within DSF-IGUs while giving priority to improving energy and thermal comfort while maintaining daylighting at acceptable levels is more reasonable. Thus, the DSF-IGUs/DL-SS best-case resulting from the second optimization scenario was overcome all best cases and ranked first in energy and thermal comfort. Compared to the base case, the differences of total Predicted mean vote and percentage of dissatisfied for better thermal comfort achieved were -0.35% and -1.48% with an average decreased by 22.99% and 28.72%, respectively. The differences of total energy and cooling load for better energy performance reduced by -96.84 kwh/m2. and -86.88 kwh with an average decreased by 25.33% and 26.20%, respectively. Meanwhile, the total satisfied of spatial Daylight Autonomy for better daylighting distribution and better daylighting availability of useful daylighting illuminance improvement were improved by -5.54% and +24.76% with an average percentage variation increased by 6.25% and 36.87%, respectively.

Publication Details

Page(s) 349-371

DOI 10.15627/jd.2024.24

Published Journal: Journal of Daylighting, Volume: 11, Issue: 2, Year: 2024

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Keywords

Genetic algorithms, Thermal comfort, Dynamic shading, IGUs glazing

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