The COVID-19 pandemic changed the world in 2020 and 2021, including how buildings were used. This was particularly true for university buildings which were potentially impacted as classes moved online, students left residence halls, and building occupancy was abnormally low in many cases. Then, as students, faculty, and staff returned to campus, universities took energy-consuming actions to reduce COVID-19 transmission (e.g., increased ventilation). These changes potentially make 2020 and 2021 building energy consumption patterns unrepresentative of typical consumption in university buildings (Gui et al. 2021; Gaspar et al. 2022; Chihib et al. 2021).

These building energy consumption changes due to COVID-19 may also have impacted the reliability of energy models. Energy models rely on expected conditions and responses to accurately assess potential savings from energy conservation measures (ASHRAE 2014). These models are created using data from a baseline period (of a few months to several years) that ASHRAE (2014) describes as “[a] period of time selected as representative of facility operations before retrofit.” COVID-19 complicates model creation, either in collecting data for a reliable baseline or via energy-consuming interventions to reduce COVID-19 risks. In this work, we explore how model baselines developed with pre-COVID-19 data perform in post-COVID-19 conditions to understand the potential need to recreate our models for post-COVID-19 buildings.