Building energy consumption under occupants’ behavior uncertainty in pre and post-renovation scenarios: a case study in Italy

In Europe, the energy renovation of the existing building stock is a greatopportunity to significantly reduce energy consumption and greenhousegas (GHG) emissions and reach the European sustainability targets. Inthis framework, building energy simulations (BES) tools are very usefulin verifying energy retrofit measures’ effectiveness and compliancewith national standards. However, an inaccurate numerical prediction,the so-called “performance gap” between measured and numerical performance,is often obtained, mainly due to the inherent uncertainty ofmodel input. Due to its stochastic nature, the occupants’ behavior (OB)is considered among the key contributors to this gap. However, the mostrecent Building Energy Model (BEM) approaches adopt deterministichourly-defined profiles for characterizing OB, thus neglecting the relateduncertainty. In this work, the impact of OB uncertainties on energy consumption(EC) prediction is evaluated by adopting a Karhunen-LoèveExpansion sampling technique, used to randomly perturb OB profilessuch as heating setpoint (HS), internal thermal loads (IL), and windowsopening (NV). Two BEMs of a typical Italian residential building inpre- and post-renovation scenarios are considered and calibrated on realEC data. The results demonstrated that HS uncertainty has the highestimpact on EC in all scenarios. Moreover, the higher the energy performanceof the building, the higher the impact of OB, especially for IL andNV patterns.