Statistical method to identify robust building renovation choices for environmental and economic performance

A Galimshina (1) , M Moustapha (2) , A Hollberg (3) , P Padey (4) , S Lavaux (4) , B Sudret (2, 5) , G Habert (1)

1 ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]
2 Chair of Risk, Safety and Uncertainty Quantification [ETH Zurich]
3 Chalmers University of Technology [Göteborg]
4 HES-SO - University of Applied Sciences and Arts of Western Switzerland
5 GdR MASCOT-NUM - Méthodes d'Analyse Stochastique des Codes et Traitements Numériques

Building renovation is urgently required to decrease the energy consumption of the existing building stock and reduce greenhouse gas emissions coming from the building sector. Selecting an appropriate renovation strategy is challenging due to the long building service life and consequent uncertainties. In this paper, we propose a new framework for the robust assessment of renovation strategies in terms of environmental and economic performance of the building's life cycle. First, we identify the possible renovation strategies and define the probability distributions for 74 uncertain parameters. Second, we create an integrated workflow for Life Cycle Assessment (LCA) and Life Cycle Cost analysis (LCC) and make use of Sobol’ indices to identify a prioritization strategy for the renovation. Finally, the selected renovation scenario is assessed by metamodeling techniques to calculate its robustness. The results of three case studies of residential buildings from different construction periods show that the priority in renovation should be given to the heating system replacement, which is followed by the exterior wall insulation and windows. This result is not in agreement with common renovation practices and this discrepancy is discussed at the end of the paper.

Mots clés: Life cycle assessment; Life cycle cost; Uncertainty quantification; Building renovation

Domaines: Réhabilitation; Applications [stat.AP]

A Galimshina, M Moustapha, A Hollberg, P Padey, S Lavaux, et al.. Statistical method to identify robust building renovation choices for environmental and economic performance. Building and Environment, In press, ⟨10.1016/j.buildenv.2020.107143⟩. ⟨hal-02916790⟩