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Joint Analysis of Cost and Energy Savings for Preliminary Design Alternative Assessment

Author

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  • Carlo Iapige De Gaetani

    (Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milan, Italy)

  • Andrea Macchi

    (Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milan, Italy)

  • Pasquale Perri

    (Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milan, Italy)

Abstract

The building sector plays a central role in addressing the problem of global energy consumption. Therefore, effective design measures need to be taken to ensure efficient usage and management of new structures. The challenging task for designers is to reduce energy demands while maintaining a high-quality indoor environment and low costs of construction and operations. This study proposes a methodological framework that enables decision-makers to resolve conflicts between energy demand and life cycle costs. A case study is analyzed to validate the proposed method, adopting different solutions for walls, roofs, floors, windows, window-to-wall ratios and geographical locations. Models are created on the basis of all the possible combinations between these elements, enriched by their thermal properties and construction/management costs. After the alternative models are defined, energy analyses are carried out for an estimation of consumption. By calculating the total cost of each model as the sum of construction, energy and maintenance costs, a joint analysis is carried out for variable life cycles. The obtained results from the proposed method confirm the importance of a preliminary assessment from both energy and cost points of view, and demonstrate the impact of considering different building life cycles on the choice of design alternatives.

Suggested Citation

  • Carlo Iapige De Gaetani & Andrea Macchi & Pasquale Perri, 2020. "Joint Analysis of Cost and Energy Savings for Preliminary Design Alternative Assessment," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7507-:d:412356
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    References listed on IDEAS

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    Cited by:

    1. Mikhail Demianenko & Carlo Iapige De Gaetani, 2021. "A Procedure for Automating Energy Analyses in the BIM Context Exploiting Artificial Neural Networks and Transfer Learning Technique," Energies, MDPI, vol. 14(10), pages 1-18, May.
    2. Roman Trach & Yuliia Trach & Marzena Lendo-Siwicka, 2021. "Using ANN to Predict the Impact of Communication Factors on the Rework Cost in Construction Projects," Energies, MDPI, vol. 14(14), pages 1-15, July.
    3. Tatjana Vilutienė & Rasa Džiugaitė-Tumėnienė & Diana Kalibatienė & Darius Kalibatas, 2021. "How BIM Contributes to a Building’s Energy Efficiency throughout Its Whole Life Cycle: Systematic Mapping," Energies, MDPI, vol. 14(20), pages 1-27, October.

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