Realistic glazing/window properties for minimizing building energy use through simulation-based optimization

The properties and control of fenestration systems have a significant impact on the energy and comfort performance of buildings. Technology improvements in glazing systems, spectrally selective coatings and shading control allows better balancing between energy and comfort benefits. However, the fundamental solar-optical properties of glazing systems are often not considered in the overall design optimization process. This study presents a simulation-based optimization method (by coupling EnergyPlus and a genetic algorithm) to select realistic double-glazed window solar-optical properties for different climates. A window layer-by-layer optimization approach is followed to minimize site energy use, where various fundamental glazing properties (solar and visible transmittance and reflectance, emissivity and conductivity) are the design variables constrained by a comprehensive existing glass library using tree-type design and K-means clustering. Each potential solution is a unique combination of all glazing properties used as decision variables. At the post-optimization stage, glazing properties are mapped to real products tagged with product IDs in the database using the minimum Euclidean Distance approach, and complete realistic window systems are re-generated using the Window 7.8 tool. Continuous Daylight Autonomy (cDA) is also calculated using Radiance to assist in evaluating the overall performance of optimal products under different shading operational modes, given the uncertainty in shading options at the design stage. The results show the range of optimal window system properties and their energy performance in different climatic zones, using a medium prototype office building as a case study. The findings can guide building designers and engineers in climate-based selection of energy-efficient windows and assist manufacturers in specifying properties of high-performing glazing products.