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Information needs for progressive BIM methodology supporting the holistic energy renovation of office buildings

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  • Stegnar, G.
  • Cerovšek, T.

Abstract

The paper presents digital methodology that can gradually and efficiently streamline the energy renovation of office buildings. Building Information Modelling (BIM) and energy simulations are widely used to facilitate informed decision-making. Significant data collections may be accrued that do not meet the information needs of energy renovation design, performance evaluation, (re)construction and operations. Ineffective managed information often leads to sub-standard project deliverables, re-work, errors, budget deficits, and delays. The progressive BIM methodology proposed suggests specifying adequate information to match the purpose of an evolving renovation design process - with emphasis on energy performance - while addressing aspects of multiple sustainability. This approach is based on firm methodological principles and validated on the actual refurbishment of office buildings. Results show that progressive BIM methodology can improve design, more accurately predict energy consumption, reduce investment costs, prevent design and planning errors, and prevent construction delays. This study is a valuable contribution to renovation design research and development, especially to practitioners (architects and engineers) in aligning client requirements and design and project outcomes, with clear profiling of the information requirements for different levels of design services in renovations.

Suggested Citation

  • Stegnar, G. & Cerovšek, T., 2019. "Information needs for progressive BIM methodology supporting the holistic energy renovation of office buildings," Energy, Elsevier, vol. 173(C), pages 317-331.
  • Handle: RePEc:eee:energy:v:173:y:2019:i:c:p:317-331
    DOI: 10.1016/j.energy.2019.02.087
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    References listed on IDEAS

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    1. Zhao, Hai-xiang & Magoulès, Frédéric, 2012. "A review on the prediction of building energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3586-3592.
    2. Amstalden, Roger W. & Kost, Michael & Nathani, Carsten & Imboden, Dieter M., 2007. "Economic potential of energy-efficient retrofitting in the Swiss residential building sector: The effects of policy instruments and energy price expectations," Energy Policy, Elsevier, vol. 35(3), pages 1819-1829, March.
    3. Tian, Wei, 2013. "A review of sensitivity analysis methods in building energy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 411-419.
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    Cited by:

    1. Xun Liu & Zhenhan Ding & Xiaobo Li & Zhiyuan Xue, 2023. "Research Progress, Hotspots, and Trends of Using BIM to Reduce Building Energy Consumption: Visual Analysis Based on WOS Database," IJERPH, MDPI, vol. 20(4), pages 1-21, February.
    2. Annamaria Ciccozzi & Tullio de Rubeis & Domenica Paoletti & Dario Ambrosini, 2023. "BIM to BEM for Building Energy Analysis: A Review of Interoperability Strategies," Energies, MDPI, vol. 16(23), pages 1-45, November.
    3. Pochwała, Sławomir & Anweiler, Stanisław & Tańczuk, Mariusz & Klementowski, Igor & Przysiężniuk, Dawid & Adrian, Łukasz & McNamara, Greg & Stevanović, Žana, 2023. "Energy source impact on the economic and environmental effects of retrofitting a heritage building with a heat pump system," Energy, Elsevier, vol. 278(PB).

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