Multi-objective optimization of window-to-wall ratio and shading devices for energy-efficient daylighting in Saudi residential villas

Enhancing energy efficiency while preserving sufficient daylight represents a significant challenge for residential buildings situated in hot, arid, and semi-arid climates, where cooling requirements constitute the primary component of annual energy consumption. This research introduces a parametric, multi-objective genetic algorithm (GA) workflow designed to investigate the combined impacts of window-to-wall ratio (WWR) and horizontal shading devices (HSDs) on annual energy use intensity (EUI) and useful daylight illuminance (UDI, 100–2000 lx) within a multi-story residential villa located in Al-Baha, Saudi Arabia. A baseline model was constructed in Rhino/Grasshopper and simulated utilizing Climate Studio, while Octopus was employed to produce Pareto-optimal solutions through SPEA-II and HypE across multiple generations. The optimisation targeted locations lacking daylight, with performance evaluations carried out at the home level to include extensive building trade-offs. The Pareto analysis demonstrates that the integration of controlled apertures with external shade can substantially enhance daylight access in previously poorly lit sections, with minimal alterations to the total building Energy Use Intensity (EUI). For the chosen compromise solution, the annual EUI decreases by approximately 1% compared to the baseline; however, the whole-building UDI declines, indicating that enhancing daylight in specific zones may diminish daylight availability in other areas if minimum daylight constraints are not enforced. The study illustrates a reproducible early-stage workflow and emphasizes the importance of establishing objectives and constraints that preserve daylight in habitable spaces while balancing energy efficiency and daylight performance in dwellings located in desiccated climates.