10:40 am - 12:00 pm | Room: Sinatra | Session Chair: Helen Stopps

MURBs

Cooling In High-Rise Residential Buildings

Space cooling demand is expected to increase due to climate change. To plan for future electric grid demand and meet GHG reduction targets, accurate forecasting of future space cooling energy use is needed. High-rise residential buildings account for a significant portion of space cooling demand and, as such, are the focus of this analysis. Field data from a high-rise residential building in Toronto, Canada, were used to characterize chiller plant operation and develop regression models to forecast average and peak cooling electricity demand. These models were used to evaluate the impact of reducing building space cooling demand on chiller plant electricity use and to forecast electricity use for a projected typical meteorological year (TMY) in the 2040s. When modelled chilled water demand reductions increased, marginal reductions in chiller plant electricity use exhibited diminishing returns. Based on the 2040s TMY projection, space cooling demand in the study building is projected to increase by 21% as compared to 2020. The data-driven modelling method used in this paper can be extended for use on larger datasets, including chiller or whole building electricity consumption from multiple buildings. To do so, data collection challenges in many jurisdictions must first be resolved.

Helen Stopps, Toronto Metropolitan University

Dr. Helen Stopps is an Assistant Professor in Building Science at Toronto Metropolitan University.  Her research focuses on the intersection between the political, social, and technical factors that determine building performance. Her work leverages data-driven methods from the natural sciences and engineering in combination with methods from the social sciences to understand how well buildings perform, identify barriers to the adoption of best practice, and to enable data-informed building codes and policy.