Multi-objective optimization of building life cycle performance. A housing renovation case study in Northern Europe

Francesco Montana, Kai Kanafani, Kim B. Wittchen, Harpa Birgisdottir, Sonia Longo, Maurizio Callura, Eleonora Riva Sanserverino

Research output: Contribution to journalJournal articleResearchpeer-review

1 Citation (Scopus)
13 Downloads (Pure)

Abstract

While the operational energy use of buildings is often regulated in current energy saving policies, their embodied greenhouse gas emissions still have a considerable mitigation potential. The study aims at developing a multi-objective optimization method for design and renovation of buildings incorporating the operational and embodied energy demands, global warming potential, and costs as objective functions. The optimization method was tested on the renovation of an apartment building in Denmark, mainly focusing envelope improvements as roof and exterior wall insulation and windows. Cellulose insulation has been the predominant result, together with fiber cement or aluminum-based cladding and 2-layered glazing. The annual energy demand has been reduced from 166.4 to a range between 76.5 and 83.7 kWh/(m2 y) in the optimal solutions. The fact that the legal requirements of 70 kWh/(m2 y) are nearly met without building service improvements indicates that energy requirements can be fulfilled without compromising greenhouse gas emissions and cost. Since the method relies on standard national performance reporting tools, the authors believe that this study is a preliminary step towards more cost-efficient and low-carbon building renovations by utilizing multi-optimization techniques.

Original languageEnglish
Article number7807
JournalSustainability
Volume12
Issue number18
ISSN2071-1050
DOIs
Publication statusPublished - 22 Sep 2020

Bibliographical note

This article belongs to the Special Issue Sustainability Assessment of Architecture, Construction, Refurbishment and Restauration.

Keywords

  • Building renovation
  • Embodied
  • Life cycle assessment
  • Low-energy buildings
  • Multi-objective optimization

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