Building heating demand vs climate: Deep insights to achieve a novel heating stress index and climatic stress curves. (10th May 2021)

• Record Type: Journal Article
• Authors: Ascione, Fabrizio; Bianco, Nicola; Mauro, Gerardo Maria; Napolitano, Davide Ferdinando; Vanoli, Giuseppe Peter
• Is Part Of: Journal of cleaner production. Volume 296(2021)
• Publication Date: 2021-05-10
• Subjects: Building simulation -- Heating demand -- Climatic stress -- Heating degree days -- Heating stress index -- Heating severity; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2021.126616
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: 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. Graphical abstract: Image 1 Highlights: Proper heating climatic stress indices support building heating demand prediction. Simulations, sensitivity/regression analysis are performed to obtain deep insights. 2 typical (existing, new) residential buildings are studied in 63 Italian locations. Degree days should consider sun-radiation/latitude to better predict heating needs. Novel reliable heating stress index & climatic stress curves are provided.