Abstract
Computational modelling of building energy performance can provide designers and operators with relevant information toward optimization of design quality and operational performance. However, the efficacy of sim-ulation-supported design strongly depends on the reliability and consistency of model input assumptions, such as those related to thermal zoning resolution and occupants’ behavior. Moreover, the actual impact of those input data and modelling choices can be different according, for example, to the climate, the type of HVAC system, and the set-points chosen for ensuring acceptable indoor thermal conditions. The present study deploys an energy model of a prototypical office floor together with a stochastic occupancy model to parametrically explore the implications of thermal zoning, climatic variations, and different control strategies for building energy use.