Abstract
A formal method has been developed for quantifying the uncertainties in degree-day-based energy estimates in buildings. Different interpretations of base temperature as a means of describing the building energy balance were investigated, with the result of an improved degree-day model that does not require the use of correction factors. This model has been tested using high-quality data from building simulations, and the outputs have been subjected to statistical uncertainty analysis. The results show that degree-day uncertainties diminish with longer time frames. The uncertainties also impact on regression techniques used in monitoring and targeting of building performance, and these uncertainties may exceed typical targets for energy efficiency improvements.
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