Utilizing Pareto Optimality to Identify Multiobjective Optimized Multi-Unit Residential Building Unit Design with Respect to Daylighting and Energy Consumption

Read the full Master Research Paper HERE.

Canadians spend most of their time in their dwelling. Meanwhile, the densification of cities has trended toward multi-unit residential buildings (MURB) becoming the dominant residential building type, yet their study has been neglected despite their prevalence throughout Canada. This building typology is known to provide poor visual comfort and can also be typically characterized by poor energy performance. These issues of inadequate daylighting and poor energy performance form a complex relationship and are often juxtaposed in regard to passive building design – design that benefits one of these aspects likely will hamper the other. Despite this, they have rarely been studied together, particularly in the MURB setting. This study investigated the complex relationship between these two variables within parameterized MURB units utilizing the novel climate-based daylight modelling (CBDM) and energy modelling tool, ClimateStudio. The results were analyzed through the lens of a Pareto optimality analysis, a multiobjective optimization method that generates a series of optimized solutions. Due to the lack of consensus in the daylighting field, other daylighting variables were investigated, including daylight schedules, various dynamic daylighting metrics, and proximity to a neighbouring building. The main results revealed which model iterations were deemed optimal based on the Pareto front generated in the analysis. These multiobjective optimized units and the trends between them were discussed to determine what can be utilized to guide future MURB design, such as maximizing north and south facades while minimizing east and west facades, designing balanced aspect ratios, and more.

Ryerson Department of  Architectural Science Toronto, CA.