Aggregating set-point temperature profiles for archetype-based: simulations of the space heat demand within residential districts

Abstract

ABSTRACTWith the increasing integration of multiple energy carriers in district energy systems, an accurate simulation of the district energy demand becomes more crucial. To reduce the required computational power, the district energy demand is often quantified through a limited set of archetype buildings, representing the whole district. As the temporal behaviour is important to assess district energy systems, stochastic occupant models should be included in the simulation. However, obtaining representative set-point temperature profiles for archetype buildings is not straightforward, as all buildings respond differently to their demanded set-point temperature due to their thermal inertia. Hence, this paper proposes and compares three techniques to obtain the representative occupant behaviour for the archetype building, by focussing on 847 single-family dwellings. Including a smart occupant aggregation method allows to decrease the percentage error in annual energy demand for space heating between the full and the archetype simulation from around 7.5% to around 2%, depending on the building model and evaluation method.