Uncertainty in model prediction of energy savings in building retrofits: Case of thermal transmittance of windows

K.E. Anders Ohlsson, Gireesh Nair and Thomas Olofsson

Renewable and Sustainable Energy Reviews, 2022, vol. 168, issue C

Abstract: Energy saving in buildings is an important measure for mitigation of climate change. There exists a large potential for energy saving in buildings by improving the thermal performance of windows. For decisions on energy saving window retrofits, accurate estimation of the energy saved and its uncertainty is of importance. The ISO 15099 standard, which is normative for thermal modelling of windows within the building sector, does not give uncertainty estimates. The main novelty of this study was to provide uncertainty analysis for model prediction of the thermal transmittance of windows, in the perspective of decisions on window retrofits. For this purpose, we proposed a new simplified model, which facilitated uncertainty analysis, and still was similar to the ISO 15099 window model. The model was validated by application of a benchmark validation procedure to a set of previously performed validation experiments. Main conclusions were: (i) The model was accurate within a prediction uncertainty equal to 0.20 Wm−2K−1; (ii) The domain where the model is valid was described using existing well-documented validation experiments. This domain was restricted to windows with glazing thermal transmittance corresponding to 2-layer glazing, and to windows where the frame area is a minor part of the total window area. (iii) The prediction uncertainty was mainly determined by the measurement uncertainty in the validation experiments; (iv) If a window retrofit is based on reduction of window thermal transmittance, then this reduction has to be larger than 0.56 Wm−2K−1 in order to yield energy savings above the uncertainty limit.

Keywords: Model validation; Uncertainty analysis; Window thermal transmittance; Energy saving measure; Mitigation of climate change; Benchmarking energy models (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1016/j.rser.2022.112748

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