Multi-objective Optimization of Window and Shading Systems for Enhanced Office Building Performance: A Case Study in Qom, Iran

Addressing the challenges of global warming and rising energy demands, this study explores fixed shading systems as passive and sustainable solutions to improve energy efficiency, thermal comfort, and daylight performance in office buildings. Conducted in the hot desert climate of Qom, the research employs advanced simulation tools, including Rhino 8 integrated with Grasshopper, Honeybee, and Ladybug, to model and evaluate shading strategies. A multi-objective optimization (MOO) approach was applied to enhance four key metrics: Thermal Comfort Percent (TCP), Energy Use Intensity (EUI), Annual Sunlight Exposure (ASE), and Spatial Daylight Autonomy (sDA). Optimization and visualization were carried out using Colibri and Design Explorer to identify shading configurations that effectively balance energy savings, thermal comfort, and daylighting. The results highlight substantial improvements achieved through optimized shading designs. Fixed exterior shading systems reduced EUI by up to 14.95% for overhangs, with side fins, light shelves, and H-louvers achieving reductions of 7.28%, 13.45%, and 6.04%, respectively. ASE was effectively mitigated, with side fins and H-louvers achieving reductions of 36.25% and 9.38%. Optimal daylighting performance was observed, as sDA reached 100% for H-louvers, side fins, overhangs, and light shelves, and 98.25% for egg-crates and V-louvers. Regarding TCP, egg-crates exhibited the highest performance at 74.18%, followed by H-louvers at 70.21%. These findings demonstrate that integrating tailored shading systems into office buildings not only enhances occupant comfort and reduces energy consumption but also supports sustainable building practices, offering practical solutions for environmentally conscious architectural design.