Sensitivity analysis and optimization of a typical passively designed residential building with hybrid ventilation in hot and humid climates

Abstract

Passive design strategies are preferable for constructing low-energy buildings given their significant influences on the building energy consumption. The building layout, envelop thermophysics, building geometry and infiltration & air-tightness are major considerations of the passive design to achieve building sustainability. In this paper, modelling experiments on a generic residential building in hot and humid climates are conducted to integrate a robust variance-based sensitivity analyses with an early-stage design optimization process. Daylight, ventilation and thermal conditions are simulated with EnergyPlus to obtain the total lighting and cooling energy consumption under the hybrid ventilation and daylight dimming control algorithm. The non-dominated sorting genetic algorithm (NSGA-II) is then coupled with the modelling experiment to obtain the Pareto frontier as well as the final optimum solution. Furthermore, different settings of NSGA-II are investigated to improve the computational efficiency of the optimization process. Findings from this study will guide decision-makers through a holistic optimization process for energy-saving targets in a passively designed green building.