Computational analysis French house-Preprint.pdf (9 MB)
Download fileComputational analysis of energy and cost efficient retrofitting measures for the French house
journal contribution
posted on 2020-04-20, 13:27 authored by Ehab Foda, Ashraf El-HamalawiAshraf El-Hamalawi, Jérôme Le DréauEnergy-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 to 290 €/m2 for Nice and Paris, respectively.
History
School
- Architecture, Building and Civil Engineering
Published in
Building and EnvironmentVolume
175Publisher
ElsevierVersion
- AM (Accepted Manuscript)
Rights holder
© Elsevier LtdPublisher statement
This paper was accepted for publication in the journal Building and Environment and the definitive published version is available at https://doi.org/10.1016/j.buildenv.2020.106792.Acceptance date
2020-03-04Publication date
2020-03-13Copyright date
2020ISSN
0360-1323Publisher version
Language
- en