Optimization of windows in order to enhance daylight and thermal performance based on genetic algorithm Case study: A residential building with a common plan in Tabriz, Iran

In residential buildings, good daylight is critical in maintaining key aspects of our psychological and physiological health, and windows have a key role in the daylight performance. However, achieving successful window design in the term of daylight is rather problematic, it can cause thermal discomfort in summer or winter. The balancing of different interrelated window factors is particularly challenging for Tabriz climate. Fortunately, because of advancements in building optimization methods in recent years, genetic algorithms used to explore for design solutions have shown their efficiency in solving complicated architectural problems. The aim of this current study is to determine the applicability of a genetic algorithm for the optimization of windows for a typical residential building in the cold climate of Tabriz considering daylight and thermal performance. Using a parametric algorithm and evolutionary multi-objective optimization via Wallacei X plug-in for Grasshopper, various windows-to-wall ratios and sill height were combined, to find potential solutions that achieve a good performance in terms of thermal comfort and daylight. The survey has shown that in optimal conditions, the increase in useful daylight illuminance towards the base cases for south and north facade is 3.2% - 10.3% and the reduction rate of discomfort hours is 1.1%-23.8% through modification of window-to-wall ratios and still height in a residential building with a common plan in this climate.The results illustrated how an optimization methodology can be applied in the early stages of building design to understand how the windows can be tailored to ensure a good balance between daylight and thermal performance.