Optimizing urban morphology for enhancing outdoor thermal comfort and cooling energy use in desert climate using SPEA2 algorithm

Source abstract

Rapid urbanization and climate change have led to a reduction in outdoor thermal comfort and an increase in building cooling energy consumption, particularly in hot-arid climates. This study investigates the trade-off between them by developing a multi-objective optimization methodology to address both objectives simultaneously. The proposed methodology combines parametric urban modeling with an SPEA2 multi-objective optimization algorithm. The methodology integrates a Grasshopper parametric workflow, Dragonfly weather morphing, Honeybee-Ladybug radiant-temperature modeling, and Octopus optimization to quantify the trade-off between outdoor thermal comfort (UTCI) and annual cooling energy (EUI). This methodology is applied to the City Walk district in Dubai, UAE, representing a hot-arid urban context. Five design variables, including building height, form, orientation, space, and urban block distribution, are considered in the optimization process. After 780 optimization simulations, eight Pareto-front designs are identified, confirming a clear trade-off between UTCI and EUI, with no single optimal solution. Clustering of the Pareto front reveals three representative urban morphologies: comfort-oriented, balanced, and energy-oriented configurations. Results indicate that triangular building geometries with dense, interconnected open spaces enhance outdoor thermal comfort through increased shading but significantly increase EUI. However, compact geometries with reduced façade exposure minimize energy use while compromising outdoor comfort. The balanced design achieved a UTCI reduction of 0.6°C during the optimization period (and up to 2.7°C in shoulder seasons) and reduced EUI by approximately 35% relative to the base case. This study demonstrates the importance of finding the optimal urban design to achieve an enhanced balance between UTCI and EUI.