Sensitivity Analysis and Multi-Objective Optimization of Skylight Design in the Early Design Stage

Abstract

Building geometry design decisions are important for energy efficiency and daylight performance. Sensitivity analysis, coupled with optimization, is an important approach to investigate and optimize building geometry in the early design stage. Incorporating skylights is an important daylighting strategy in commercial buildings; however, skylight-to-floor ratio (SFR) is often the only design variable evaluated in precedent studies. More design variables related to skylight geometry, clerestory geometry, skylight material, and building geometry need to be evaluated. This study investigates the skylight design of a 2000-square-meter commercial building. Eighteen design variables are evaluated according to their influence on building energy and daylight performance. One-at-a-time (OAT), linear regression, and Morris sensitivity analysis approaches are utilized to identify the most influential variables. Seven of the twelve building geometry variables and two of the six building material variables are considered as important. Then, a multi-objective optimization with genetic algorithms is processed to find out the optimal design solution. The three objectives are energy use intensity (EUI), daylight autonomy (DA), and daylight uniformity (DU). After the optimization, five candidate design options are picked from the Pareto front. Discussions are made on the features of these designs, and one design is selected as the optimal solution.