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Computational analysis of energy and cost efficient retrofitting measures for the French house

Abstract : Energy-efficient housing has become a mandatory aim to address climate change. This paper presents a computational analysis taking a French single family house as a case study, and aims to investigate both energy and cost-efficiency of market available retrofit measures using dynamic thermal modelling. A parametric analysis tool was developed to run automated batch-simulations using EnergyPlus simulation engine and to calculate the cost associated with retrofit measures, at each simulation run. The automated simulations are carried out, using an exhaustive search technique, for all permutations of measures. These included different building fabrics, ventilation strategies, levels of air-tightness and 5 different heating systems for 4 main climatic regions of France (7680 variants for each of the 4 climatic region). In this analysis, an optimization problem is set to minimise the delivered energy and retrofitting investment cost subject to an energy-saving minimum limit, payback criterion, and summer overheating-risk. The results showed optimum solutions with different fabric and system retrofit combinations that varied in numbers for the different climatic zones. The upper bound of optimum investment cost varied from 80 and 290 €/m2 for Nice and Paris, respectively.
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Submitted on : Wednesday, March 18, 2020 - 9:53:07 AM
Last modification on : Friday, May 13, 2022 - 3:42:57 AM

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Ehab Foda, Ashraf El-Hamalawi, Jérôme Le Dréau. Computational analysis of energy and cost efficient retrofitting measures for the French house. Building and Environment, Elsevier, 2020, 175, pp.106792. ⟨10.1016/j.buildenv.2020.106792⟩. ⟨hal-02510701⟩



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