Optimization of Daylight Performance Based on Controllable Light-shelf Parameters using Genetic Algorithms in the Tropical Climate of Malaysia

• Main Authors: Ali Ahmed Salem Bahdad, Sharifah Fairuz Syed Fadzil, Nooriati Taib
• Format: Article
• Language: English
• Published: SolarLits 2020-06-01
• Series: Journal of Daylighting
• Subjects: daylight performance; parametric simulation tools; genetic algorithms; light-shelf
• Online Access: https://solarlits.com/jd/7-122

This study aims to achieve a balance of daylight availability in the work-plane environments of a fully glazed facade integrated with a light shelf system using an optimization procedure that can assist architects with assessing the daylighting performance of numerous design alternatives, and build-up the optimized design. The approach uses parametric design, simulation modelling, and genetic algorithms. A case study of a typical office is carried out to test and verify the effectiveness of the optimization procedure for a light shelf system. Five parameters of light shelf design are optimized in two solar solstices (June and December) and one equinox in March under the Malaysian sky conditions. The optimization results indicate that the optimal design options of light-shelf parameters have great potential for illuminance improvement. After the optimization, the daylighting performance of useful daylight illuminance compared to reference models is increased respectively with an average value of 15.6% and 4.7% on the 21st of June, and by 17.5% and 5.8% on 21st of March, and by 5.8% and 11.3% on 21st of December. Statistical analysis is achieved to investigate the relationship between the performance metric of the optimal design options and the other cases, the outcomes showed that the regression analysis indicated a high level of reliability as well as different levels of variation coefficients.