Abstract
Background and purpose: Architects are increasingly exploring methods to enhance occupants' comfort within buildings by optimizing natural daylight levels while simultaneously improving energy efficiency. The incorporation of dynamic elements in building facades, however, remains relatively uncommon. The inherent dynamic nature of daylight, coupled with the static nature of conventional facades, often hinders the optimal utilization of natural light. Consequently, sustainable architecture strives to develop strategies that maximize the effective use of daylight throughout the day as well as achieve enhanced energy performance. Therefore, this study investigates the application of adaptive shading devices to optimize both daylighting and energy efficiency. Specifically, this is achieved by optimizing daylight utilization while considering the most effective variables influencing the performance of adaptive shading devices on the southern facade of an office building in Isfahan, Iran.
Methodology: This study adopts a rationalist approach, employing a quantitative, experimental methodology based on computer simulations to achieve its applied objective. It aims to investigate the causal relationships between independent variables (the design parameters of adaptive shading devices) and dependent variables (daylighting and energy efficiency optimization) within the context of south-facing facades of office buildings in Isfahan's hot and dry climate. The simulations were conducted using a parametric modeling workflow. The initial model was developed in Rhino software using the Grasshopper environment. Daylight and energy performance were simulated using the Ladybug Tools plugin. A genetic algorithm, specifically the NSGA-II algorithm, was employed for multi-objective optimization using the Wallace plugin. The base model, representing a square-shaped office space on the third floor of a building in Isfahan, was analyzed with two types of adaptive shading devices: peripheral and retractable. Each shading type was evaluated across 100 variations, totaling 200 simulations. Building performance indices, namely Useful Daylight Illuminance (UDI) and Energy Use Intensity (EUI), were analyzed both simultaneously and individually for each of the four seasons and annually to identify the optimal configurations. Given the conflicting nature of the two objectives (maximizing UDI and minimizing EUI), a multi-objective optimization approach was employed, allowing for the ranking and comparison of optimal solutions based on their performance across both indicators.
Findings and discussion: Based on the defined fitness function, the optimal design alternatives were identified. Regarding the peripheral adaptive shading system, the multi-objective optimization process showed that, across the 100 evaluated configurations, the best performance was achieved with a shading depth of 100 cm during spring, summer, and autumn, and a depth of 29 cm during winter. This configuration resulted in a 20 % increase in UDI and a 21 % reduction in EUI compared to the base case. Similarly, for the retractable adaptive shading system, a consistent depth of 100 cm across all four seasons yielded the most favorable results, leading to a 26 % increase in UDI and a substantial 48 % decrease in EUI.
Conclusion: The findings demonstrate that implementing either peripheral or retractable adaptive shading systems in office buildings in Isfahan can effectively optimize both daylighting performance and energy efficiency concurrently, despite the challenges posed by the region's hot and dry climate, particularly the intensely hot summers.
Keywords
Main Subjects
)