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Development of a multicriteria tool for optimizing the renovation of buildings

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  • Chantrelle, Fanny Pernodet
  • Lahmidi, Hicham
  • Keilholz, Werner
  • Mankibi, Mohamed El
  • Michel, Pierre

Abstract

The renovation of a building involves not just the fulfilment of functional requirements, but also considerations such as energy consumption, investment costs, environmental impact and wellbeing. As things stand, new design methods and tools are needed, and the aim of the research presented in this article was to develop a multicriteria tool, MultiOpt, for the optimization of renovation operations, with an emphasis on building envelopes, heating and cooling loads and control strategies. MultiOpt is based on existing assessment software and methods: it uses a genetic algorithm (NSGA-II) coupled to TRNSYS, and economic and environmental databases. This article illustrates its utilization in the renovation of a school in the southern French city of Nice which was representative of France's building stock. The study started with the monocriterion optimization of energy consumption, cost, thermal comfort, and life-cycle environmental impact. It then moved onto multicriteria optimizations. The monocriterion analyses focussed on the building's characteristics and performance; the multicriteria analyses were concerned with the interactions between the different objectives, and with identifying their convergences and divergences. The results demonstrated that MultiOpt can be used to compare different combinations of options and constraints, thus constituting a basis for operational decision-making.

Suggested Citation

  • Chantrelle, Fanny Pernodet & Lahmidi, Hicham & Keilholz, Werner & Mankibi, Mohamed El & Michel, Pierre, 2011. "Development of a multicriteria tool for optimizing the renovation of buildings," Applied Energy, Elsevier, vol. 88(4), pages 1386-1394, April.
    • Handle: RePEc:eee:appene:v:88:y:2011:i:4:p:1386-1394
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    References listed on IDEAS

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    1. Hammache, Abdelaziz & Benali, Marzouk & Aubé, François, 2010. "Multi-objective self-adaptive algorithm for highly constrained problems: Novel method and applications," Applied Energy, Elsevier, vol. 87(8), pages 2467-2478, August.
    2. Sanaye, Sepehr & Hajabdollahi, Hassan, 2010. "Thermal-economic multi-objective optimization of plate fin heat exchanger using genetic algorithm," Applied Energy, Elsevier, vol. 87(6), pages 1893-1902, June.
    3. Kumar, Rakesh & Sinha, A.R. & Singh, B.K. & Modhukalya, U., 2008. "A design optimization tool of earth-to-air heat exchanger using a genetic algorithm," Renewable Energy, Elsevier, vol. 33(10), pages 2282-2288.
    4. Kusiak, Andrew & Li, Mingyang, 2009. "Optimal decision making in ventilation control," Energy, Elsevier, vol. 34(11), pages 1835-1845.
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