Abstract
In the analyses of the uncertainty propagation of buildings’ energy-demand, the Monte Carlo method is commonly used. In this study we present two alternative approaches: the stochastic perturbation method and the transformed random variable method. The energy-demand analysis is performed for the representative single-family house in Poland. The investigation is focused on two independent variables, considered as uncertain, the expanded polystyrene thermal conductivity and external temperature; however the generalization on any countable number of parameters is possible. Afterwards, the propagation of the uncertainty in the calculations of the energy consumption has been investigated using two aforementioned approaches. The stochastic perturbation method is used to determine the expected value and central moments of the energy consumption, while the transformed random variable method allows to obtain the explicit form of energy consumption probability density function and further characteristic parameters like quantiles of energy consumption. The calculated data evinces a high accordance with the results obtained by means of the Monte Carlo method. The most important conclusions are related to the computational cost reduction, simplicity of the application and the appropriateness of the proposed approaches for the buildings’ energy-demand calculations.
Highlights
The building energy demand is usually calculated based on the strictly defined values describing boundary conditions, material parameters or profiles of the occupants’ behaviour
The Monte Carlo method allows one to determine the distribution function. This manuscript is aimed at an application of two methods, which may be used for propagation of uncertainties in the buildings’ energy-demand problems, i.e. the stochastic perturbation method and the transformed random variable method
The energy consumption was calculated using the EnergyPlus software for the single uncertain parameter and for both parameters considered as uncertain
Summary
The building energy demand is usually calculated based on the strictly defined values describing boundary conditions, material parameters or profiles of the occupants’ behaviour Such a deterministic approach is often applied in the engineering calculations, in which the worst-case scenario may be considered, i.e. to determine the maximum possible demand for the heating system sizing. The Monte Carlo method allows one to determine the distribution function This manuscript is aimed at an application of two methods, which may be used for propagation of uncertainties in the buildings’ energy-demand problems, i.e. the stochastic perturbation method and the transformed random variable method. According to the Authors’ best knowledge, this method has not been previously used in the energy-demand related problems, despite the fact that its computational cost is much smaller when compared with the sampling probabilistic methods These two methods may be successfully applied in the analyses of the uncertainty distribution in the energy-demand calculations. Using them, we may obtain the probability distribution function with a lower computational cost
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