Influence of input data uncertainty in school buildings energy simulation

Abstract

In developed countries, the building sector is responsible for a very significant share of the total energy consumption. A more detailed and rigorous analysis of building energy performance became possible due to the building simulation software improvement. Traditionally, buildings energy simulation requires the definition of a set of input parameters, which are usually considered as deterministic, neglecting the fact that in reality they have a stochastic nature. Hence, if one intends to evaluate the uncertainty in simulation due to the uncertainty of the input parameters, stochastic methods, such as Monte Carlo simulations should be employed. This paper presents a methodology for the stochastic simulation of school buildings for tackling input data uncertainty. The Monte Carlo method application in the evaluation of the uncertainty of the heat demand of a school building provides an example case where the opportunities and difficulties of the method are explored. The methodology includes parameter characterization, sampling procedure, simulation automatization and sensitivity analysis. Its application results in increased knowledge of the building, allowing to define targets that include the stochastic effect.