A meta model-based methodology for an energy savings uncertainty assessment of building retrofitting

To reduce greenhouse gas emissions, energy retrofitting of building stock presents significant potential for energy savings. In the design stage, energy savings are usually assessed through Building Energy Simulation (BES). The main difficulty is to first assess the energy efficiency of the existing buildings, in other words, to calibrate the model. As calibration is an under determined problem, there is many solutions for building representation in simulation tools. In this paper, a method is proposed to assess not only energy savings but also their uncertainty. Meta models, using experimental designs, are used to identify many acceptable calibrations: sets of parameters that provide the most accurate representation of the building are retained to calculate energy savings. The method was applied on an existing office building modeled with the TRNsys BES. The meta model, using 13 parameters, is built with no more than 105 simulations. The evaluation of the meta model on thousands of new simulations gives a normalized mean bias error between the meta model and BES of