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The thermal characterisation of a building envelope is usually best performedfrom on site measurements with controlled heating power set points.Occupant-friendly measurement conditions provide on the contrary lessinformative data. Notwithstanding occupancy, the boundary conditions alonecontribute to a greater extent to the energy balance. Non intrusive conditionsquestion therefore the repeatability and relevance of such experiment.Thispaper proposes an original numerical methodology to assess the repeatabilityand accuracy of the estimation of an envelope's overall thermalresistance undervariable weather conditions. A comprehensive building energy model serves asreference model to produce multiple synthetic datasets. Each is run with adifferent weather dataset from a single location and serves for the calibrationof an appropriate model, which provides a thermal resistance estimate. Theestimate's accuracy is then assessed in the light of the particular weatherconditions that served for data generation. The originality also lies in theuse of stochastically generated weather datasets to perform an uncertaintyandglobal sensitivity analysis of all estimates with respect to 6 weathervariables.The methodology is applied on simulated data from a one-storey housecase study serving as reference model. The thermal resistance estimations areinferred from calibrated stochastic RC models. It is found that 11 days arenecessary to achieve robust estimations. The large air change rate in the casestudy explains why the outdoor temperature and the wind speed are found highlyinfluential.

Influence of weather natural variability on the thermal characterisation of a building envelope