The temperature setpoint schedules used to control building temperatures often vary from one building to another. Researchers developed a method to systematically generate a distribution of these schedules that reflects this diversity but remains constrained to producing practical results. They added the stochastically generated temperature setpoint schedules to building energy models. They then incorporated the schedules into a building performance simulation engine that computes hourly electricity consumption over the entire year. Finally, they used the results to understand how schedule changes impact tradeoffs between total electricity consumption, peak consumption, and thermal comfort.
The proposed methodology has implications for the field of building energy modeling. Planning and installing energy systems at grid-scale requires understanding diurnal patterns in electricity consumption and necessitates large-scale building energy modeling. Current practice uses a limited set of prototype models to represent a large set of buildings at urban, regional, or national scales, but includes limited variation in temperature setpoint operation. Thus, the proposed methodology allows for a more accurate representation of diversity in heating and cooling operations.
Currently, there is no survey data on temperature setpoints across the U.S. building stock. This research develops a methodology to stochastically generate feasible temperature setpoint schedules for commercial buildings. The methodology details a way to quantitatively represent both (i) schedules with constant temperature throughout the day and (ii) setback schedules, in which nighttime schedules differ from daytime schedules to reduce energy consumption. This methodology starts with a base schedule and defines a limited set of clearly defined parameters to generate no-setback and setback schedules.
To demonstrate how this methodology supports parametric analysis, researchers performed multiple case studies to determine how a specific change to setpoint schedules can affect outputs of interest like total electricity consumption, maximum hourly electricity consumption per day, and thermal comfort. They simulated the energy consumption of a small office model building with different distributions of heating and cooling setpoint schedules. The results show that a given change to a setpoint schedule can cause tradeoffs between the outputs of interest and that the nature of these tradeoffs varies based on the time of the year.