Towards a methodology to include building energy simulation uncertainty in the Life Cycle Cost analysis of rehabilitation alternatives

Abstract The selection of the best alternative for building rehabilitation should involve LCC analysis to account for all the costs involved. A significant part of those costs relates to energy consumption, which can only be assessed with an intrinsic level of uncertainty. This work proposes an integrated methodology that can quantify and integrate that uncertainty in LCC estimation. The methodology relies on Monte Carlo simulation to calculate statistical distributions of energy demand. The associated costs can then be introduced in an LCC analysis and provide decision makers with a measure of rehabilitation alternatives economic impact uncertainty. The paper describes the methodology and applies it to an example case. The results are mainly intended to illustrate the methodology application and pinpoint key aspects such as input data pre-processing, convergence analysis, and adequate economic measures. The methodology is not ready for a generalized application as reliable stochastic input data are not frequently available yet. Nevertheless, the results found in this work showed how this approach can influence decisions if the robustness of each alternative is known.

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