Abstract

It is clear that the thermophysical properties of materials, occupancy patterns and internal gains represent some of the most important sources of uncertainty in the field of building simulation. Uncertainty and sensibility analysis deals with this situation, since it can generate a great range of forecast values based on the distribution of the input variables. At the same time, these techniques allow to determine as each variable contribute to the total variance of output results. However, most of the building energy simulation programs are deterministic, rather than probabilistic and consequently their results frequently are not expressed in terms of probabilities. On the contrary, the probabilistic approach requires a more complex process, since parameters quantification requires not only an assessment of the point estimate, but also an assessment of the uncertainty. This research aims to define the uncertainty of the predicted energy performance by means of the comparison between factorial design and Monte Carlo Analysis for a sample of 7776 cases that belong to the real estate market of apartments in Santiago de Chile. A total of 9 input parameters constitute the basis for these analyses using the standard EN ISO 13790 as calculation algorithm for estimating the annual heating demand.