Load shifting and energy conservation using smart thermostats in contemporary high-rise residential buildings: Estimation of runtime changes using field data

As the proportion of the population who resides in urban centers grows, the number of dwellings in highrise residential buildings is also increasing. In Canada, heating, ventilation, and air conditioning (HVAC) typically accounts for over half of all energy use in this building type and, as such, consideration of these loads is key to effective energy demand-side management. Smart thermostats present a new opportunity conserve energy and shift electricity load to off-peak periods in these buildings through modifications to HVAC control strategies. In this study, three thermostat control strategies were tested in 49 suites across two contemporary high-rise residential buildings: 1) baseline operation (thermostat operating as a standard programmable thermostat); 2) occupancy-based control (thermostat operating using an occupancy reactive control strategy); 3) load shifting control (thermostat operating using a pre-conditioning strategy). HVAC runtime data was collected from smart thermostats installed in the suites and was used to develop data-driven regression models to estimate baseline suite HVAC runtime based on weather conditions and suite characteristics. Thermostat-measured HVAC runtime data for periods in which occupancy-based or load shifting control strategies were in use in the suite was then compared with estimated baseline runtime for similar outdoor conditions. Occupancy-based control was found to reduce HVAC system runtime during the cooling seasonby 5.9% +/- 46% on average. On aggregate, the load shifting control strategy was not effective at reducing peak period HVAC load during the cooling season. The strategy was able to reduce peak period loads in a subset of suites substantially, which may be leveraged to reduce electricity demand during capacity-constrained periods of grid operation, however, based on marginal emissions factors for Ontario's electricity grid, even in these suites, the strategy was not effective in reducing GHG emissions overall. (c) 2021 Elsevier B.V. All rights reserved.