Uncertainties and sensitivity analysis in building energy simulation using macroparameters

Abstract Sensitivity analysis (SA) is usually carried out along with energy simulations to understand buildings performance and reduce their consumptions. The quality of their results mainly depends on thermal models and input data. Having accurate data about properties and operation conditions of buildings is difficult. In consequence, simulation inputs are affected by uncertainties that may have significant effects on outputs and are important to be considered. Law-driven detailed models are widely used. They ensure reliability and versatility but require a large number of input parameters. The paper addresses the difficulties of getting information from SA using detailed models with existing techniques and proposes a methodology which solves current problems. The methodology consists of using a detailed model of the building, defining and propagating uncertainties of input parameters, calculating macroparameters that characterize the building and getting sensitivity indices. The procedure is applied to the study case of a dwelling in which weather and occupancy are found out to be the strongest parameters on its annual consumption. It should be highlighted that, keeping the structure of inputs with uncertainties required by complex models that defines buildings in detail, the method eases building performance understanding.