The sensitivity of building performance simulation results to the choice of occupants’ presence models: a case study

Abstract

The considerable performance implications of occupants’ presence and behaviour in buildings render the inclusion of corresponding models in simulation applications both necessary and critical. In this context, an important question concerns the implications of different occupancy modelling approaches for simulation results. The present contribution addresses this issue by modelling an office building to obtain heating and cooling demands and peak loads. To represent occupants’ presence patterns in the model, standard-based and observed diversity profiles, stochastic realizations of these profiles, and the full-year observational occupancy data are deployed. Subsequently, a sequence of simulation runs – involving Monte-Carlo simulations of models with stochastic profiles – provides the distributions of results. The study suggests that the viability of simulation results regarding building-level annual heating and cooling demands and peak heating and cooling loads is primarily dependent on the availability of reliable estimations of actual occupancy, rather than stochastic or non-stochastic representation of presence patterns.