Open AccessProbabilistic LCA and LCC to identify robust and reliable renovation strategies
Author(s) -
Alina Galimshina,
Alexander Hollberg,
Maliki Moustapha,
Bruno Sudret,
Didier Favre,
Pierryves Padey,
Sébastien Lasvaux,
Guillaume Habert
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/323/1/012058
Subject(s) - retrofitting , probabilistic logic , greenhouse gas , sobol sequence , computer science , architectural engineering , environmental economics , risk analysis (engineering) , engineering , business , economics , sensitivity (control systems) , ecology , structural engineering , artificial intelligence , electronic engineering , biology
Buildings are one of the largest energy consumers and greenhouse gas emitters in the world. As the largest part of the energy consumed by the existing non-insulated buildings occurs during the operation stage, retrofitting the building stock is crucial to reduce the environmental impact. To guarantee that the retrofit measures provide economic and environmental benefits, the whole life cycle should be assessed. However, the identification of environmental and at the same time cost-effective solutions is difficult due to the complexity and the uncertainty involved. Currently, simplified approaches based on limited assumptions are used that can lead to inaccurate results. This paper proposes a method for identifying robust renovation scenarios for residential buildings in Switzerland. The method and the developed tool use 47 uncertain parameters and Sobol’ indices to identify the most influential parameters. As such, robust renovation strategies can be identified in the early design stage.