Daylightoptimized

Daylightoptimized is a design methodology and software framework dedicated to optimizing daylight usage in buildings. It aims to maximize the amount of useful daylight reaching interior spaces while minimizing glare, overheating, and energy use, through coordinated adjustments to façade geometry, shading devices, interior layouts, and surface properties.

It uses a data-driven workflow combining climate data, site constraints, occupancy assumptions, and daylight metrics such as daylight autonomy and glare probability. An optimization engine explores design variants and evaluates them against multiple objectives, often employing gradient-based, evolutionary, or Bayesian methods to propose configurations for window sizes and placements, shading strategies, and interior layouts or materials.

Implementation typically involves integration with established simulation tools such as Radiance for daylight modeling, Daysim for daylight autonomy, and energy simulation engines like EnergyPlus. The framework is used in early design phases and retrofit studies to produce a set of recommended options and sensitivity analyses, supporting informed tradeoffs between daylight quality and energy performance.

Limitations include dependency on representative climate data and occupancy patterns, potential computational cost, and the need for design judgment to balance qualitative comfort with quantitative metrics. As a developing area, daylightoptimized emphasizes transparent reporting of assumptions and uncertainty to support collaborative decision making.