Multi-objective optimization of horizontal louver systems with flat, single-curvature, and double-curvature profiles to enhance daylighting, glare control, and energy consumption in office buildings

Identifying the most optimal slat shape significantly influences the performance of louver systems in terms of daylighting, glare control, and energy consumption. This is particularly crucial in climates with high levels of solar irradiance, where thermal gain and daylight illumination highly affect buildings and occupants. This study aims to identify the optimal slat shapes for various profile types—flat, single-curvature, and double-curvature—that simultaneously reduce annual energy consumption and enhance annual daylighting and visual comfort performance in fully glazed office buildings. This goal is achieved by employing a multi-objective optimization (MOO) algorithm, NSGA-II, applied to a control-point-based algorithm designed to generate diverse slat shapes for each profile type. The main objective functions include the maximization of spatial useful daylight illuminance (sUDI) and spatial glare autonomy (sGA), as well as the minimization of energy use intensity (EUI). The MOO process results in a diverse set of Pareto optimal slat shapes for each profile type, which are subsequently ranked by a fitness function. Findings suggest that the Pareto optimal solutions within each type significantly improve the overall performance of the space compared to the base case. Specifically, among these solutions, flat profiles with the highest fitness scores enhance daylighting levels of the space to a greater extent (9.028% to 14.583%) compared to single (−2.778% to 12.5%) and double-curvature profiles (−5.556% to 9.722%) with the highest scores. Regarding glare, double-curvature profiles with the highest fitness scores provide a more visually comfortable environment for users by improving the sGA value by 19.879% to 33.247% compared to the base case. However, those with a concave-convex shape produce excessive illumination in the perimeter zone, whereas those with a convex-concave shape present challenges in providing sufficient daylight in the rear zone of the space. Additionally, applying any of the Pareto optimal solutions to the louver system reduces the annual energy consumption of the office space compared to the base model. While the improvements are almost comparable, flat profiles with the highest fitness scores marginally reduces energy consumption to a greater extent (62.906% to 68.161%).