Model-Based Control Strategies to Enhance Energy Flexibility in Electrically Heated School Buildings

Abstract

This paper presents a general methodology to model and activate the energy flexibility of electrically heated school buildings. The proposed methodology is based on the use of archetypes of resistance–capacitance thermal networks for representative thermal zones calibrated with measured data. Using these models, predictive control strategies are investigated with the aim of reducing peak demand in response to grid requirements and incentives. A key aim is to evaluate the potential of shifting electricity use in different archetype zones from on-peak hours to off-peak grid periods. Key performance indicators are applied to quantify the energy flexibility at the zone level and the school building level. The proposed methodology has been implemented in an electrically heated school building located in Québec, Canada. This school has several features (geothermal heat pumps, hydronic radiant floors, and energy storage) that make it ideal for the purpose of this study. The study shows that with proper control strategies through a rule-based approach with near-optimal setpoint profiles, the building’s average power demand can be reduced by 40% to 65% during on-peak hours compared to a typical profile.