Abstract
In this study, we describe a novel method for evaluating building heating demand based on a statistical approach. Our aim is to support integrated building design by providing fast modeling with accuracy close to that of dynamic simulations. A general parametric model encompassing overall building design is proposed based on the analysis of heat transfer. The method is subsequently applied to evaluate the heating demand of a single-family house in a cold French climate. Several polynomial functions are derived from the general model as functions of the amounts of heat transferred by different mechanisms and the physical and geometric building parameters. The model is identified with a small number of dynamic simulations using the design of experiments. The model illustrates how the weighting factors for the various amounts of heat are much higher in cold climates than in hot ones. We demonstrate that building heating demand can be accurately analyzed using the design parameters of the developed model. This analysis highlights the potential of this approach for supporting building energy designers in the choice of energy-efficient solutions.
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