Modelling and Analysis of Retrofit Strategies for Mid-Rise Multi-Unit Residential Buildings in Toronto: Advancing Energy Efficiency, Comfort, Resilience, and Decarbonization

Abstract

Over the past century, global temperatures have risen significantly due to human activity, contributing to more frequent and intense extreme weather events such as heatwaves. This underscores the urgent need to reduce emissions from the building sector while enhancing the climate resilience of existing buildings. Most of the buildings that will be in use in Canada by 2050 have already been constructed; therefore, the existing building stock must be retrofitted to enhance energy efficiency and increase occupant safety and comfort under extreme future climate conditions. The objective of this study is to evaluate the effectiveness of various energy conservation measures (ECMs) in advancing energy efficiency and decarbonization, while enhancing thermal resilience and reducing thermal stress, for mid-rise multi-unit residential buildings (MURBs) in Toronto. The ECMs evaluated in this study included the effective thermal resistances (R-values) of the wall assembly and the roof assembly, window thermal conductance (U-factor), infiltration, roof colour, lighting power density (LPD), equipment power density (EPD) and domestic hot water (DHW) peak flow rate. Mechanical system upgrades, including the addition of cooling and ventilation, as well as the electrification of space heating and DHW, were also studied. A numerical archetype building energy model was calibrated with actual energy consumption data from an existing MURB. This baseline model was then used to (1) develop a surrogate model for predicting energy use intensity (EUI) and (2) to evaluate the effectiveness of the ECMs under current and future climate conditions. A Multilayer Perceptron (MLP, a feedforward neural network) and fourth-degree polynomial surrogate model achieved coefficient of determination (R²) values of at least 99.98% and 99.82% respectively, and normalized root mean squared errors (NRMSE) of at most 0.17% and 0.55%, respectively. The polynomial equations can easily be used to predict the EUI of similar MURBs for a variety of ECMs. The numerical and surrogate models were then used to evaluate the impact of various ECMs on reducing EUI, advancing building decarbonization and improving occupant thermal comfort. The building envelope ECMs were successful at reducing the EUI, and adding cooling and ventilation maintained safe and comfortable indoor conditions throughout the year. Electrification was an effective method for reducing operational carbon emissions due to Ontario’s low carbon electricity grid. The combination of envelope retrofits and mechanical system upgrades resulted in a 57% reduction in EUI (from 270 kWh/m²/year to 116 kWh/m²/year), a 90% reduction in operational carbon emissions (from 43 kg CO₂e/m²/yr to 4 kg CO₂e/m²/yr), maintained comfortable conditions for 97% of the year (8,481 out of 8760 hours of the year), and maintained safe conditions for all hours of the year. Under predicted future climate conditions, EUI was lower due to the lower heating demand; however, the thermal resilience metrics decreased by up to 47% highlighting the need to consider both energy efficiency and thermal resilience when retrofitting MURBs.