This study offers deep insights into the link between climatic stress and building heating performance. Two representative Italian residential buildings – existing and newly-built, respectively – are investigated by predicting heating demand for 63 locations, covering all typical national climates. Two simulation software are used – i.e., TERMUS® and EnergyPlus –, to compare a standard semi steady-state approach with a more accurate dynamic one. The comparison enables to understand the influence of the climatic stress on different levels of building modeling/simulation. Notably, the semi steady approach can provide reliable outcomes (close to the dynamic one) for existing buildings in cold climates. Then, a sensitivity analysis is conducted to investigate the correlation between climatic parameters and yearly heating demand, showing that the heating degree day index does not provide a complete explanation of such demand. Indeed, it does not take into account latitude and/or solar radiation, whose influence is not negligible. Therefore, a novel heating stress index is proposed, including normalized heating degree day and latitude. Its expression is optimized through a Pareto approach to ensure the best fitting/regression of yearly heating demand for both building typologies. The achieved determination coefficient (R2) is 0.990 for the existing building, 0.995 for the newly-built one. Finally, climatic stress curves are achieved to predict heating demand and related running cost as a function of the proposed index, providing a user-friendly but reliable tool to forecast building heating needs.
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