A Two-Stage Optimization-Assessment Framework for Climate-Based Glazing Performance Considering Energy Use, Thermal Comfort, and Daylight Glare

Abstract

Window glazing systems play a critical role in building energy performance, particularly in office buildings with large window-to-wall ratios, which introduce complex trade-offs between energy consumption, thermal comfort, and visual comfort. This study develops a two-stage optimization-assessment framework to assess glazing performance across six climate regions defined by the TS 825 standard in T & uuml;rkiye. In the first stage, a genetic algorithm-based multi-objective optimization approach was employed to minimize annual energy consumption (heating, cooling, and daylight-linked lighting) and thermal discomfort hours. In the second stage, the resulting Pareto-optimal solutions were further evaluated and ranked according to spatial disturbing glare (sDG) performance using annual glare simulations. The results show that energy-optimal solutions are not necessarily visually acceptable, highlighting the limitations of single-criterion approaches. While static low-e glazing provides competitive energy performance under several climate conditions, it may lead to increased glare risk, particularly at high window-to-wall ratios and in sun-exposed orientations. Dynamic glazing systems, although not consistently superior in energy terms, offer a more balanced performance when glare is considered, especially in colder climates. These findings emphasize the need for a climate-based, multi-criteria, and integrated approach to glazing selection.