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Multidisciplinary Energy Assessment of Tertiary Buildings: Automated Geomatic Inspection, Building Information Modeling Reconstruction and Building Performance Simulation

Author

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  • Faustino Patiño-Cambeiro

    (Industrial Engineering School, University of Vigo, Rúa Maxwell, 36310 Vigo, Spain)

  • Guillermo Bastos

    (Industrial Engineering School, University of Vigo, Rúa Conde de Torrecedeira 86, 36208 Vigo, Spain)

  • Julia Armesto

    (Mining Engineering School, University of Vigo, Campus as Lagoas Marcosende, 36310 Vigo, Spain)

  • Faustino Patiño-Barbeito

    (Industrial Engineering School, University of Vigo, Rúa Conde de Torrecedeira 86, 36208 Vigo, Spain)

Abstract

There is an urgent need for energy efficiency in buildings within the European framework, considering its environmental implications, and Europe’s energy dependence. Furthermore, the need for enhancing and increasing productivity in the building industry turns new technologies and building energy performance simulation environments into extremely interesting solutions towards rigorous analysis and decision making in renovation within acceptable risk levels. The present work describes a multidisciplinary approach for the estimation of the energy performance of an educational building. The research involved data acquisition with advanced geomatic tools, the development of an optimized building information model, and energy assessment in Building Performance Simulation (BPS) software. Interoperability issues were observed in the different steps of the process. The inspection and diagnostic phases were conducted in a timely, accurate manner thanks to automated data acquisition and subsequent analysis using Building Information Modeling based tools (BIM-based tools). Energy simulation was performed using Design Builder, and the results obtained were compared with those yielded by the official software tool established by Spanish regulations for energy certification. The discrepancies between the results of both programs have proven that the official software program is conservative in this sense. This may cause the depreciation of the assessed buildings.

Suggested Citation

  • Faustino Patiño-Cambeiro & Guillermo Bastos & Julia Armesto & Faustino Patiño-Barbeito, 2017. "Multidisciplinary Energy Assessment of Tertiary Buildings: Automated Geomatic Inspection, Building Information Modeling Reconstruction and Building Performance Simulation," Energies, MDPI, vol. 10(7), pages 1-17, July.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:1032-:d:105203
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    References listed on IDEAS

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    1. Neil Burford & Rod Jones & Stephen Reynolds & David Rodley, 2016. "Macro Micro Studio: A Prototype Energy Autonomous Laboratory," Sustainability, MDPI, vol. 8(6), pages 1-25, May.
    2. Gourlis, Georgios & Kovacic, Iva, 2016. "A study on building performance analysis for energy retrofit of existing industrial facilities," Applied Energy, Elsevier, vol. 184(C), pages 1389-1399.
    3. WoonSeong Jeong & JeongWook Son, 2016. "An Algorithm to Translate Building Topology in Building Information Modeling into Object-Oriented Physical Modeling-Based Building Energy Modeling," Energies, MDPI, vol. 9(1), pages 1-23, January.
    4. Delia D’Agostino & Paolo Zangheri & Luca Castellazzi, 2017. "Towards Nearly Zero Energy Buildings in Europe: A Focus on Retrofit in Non-Residential Buildings," Energies, MDPI, vol. 10(1), pages 1-15, January.
    5. Atam, Ercan, 2017. "Current software barriers to advanced model-based control design for energy-efficient buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1031-1040.
    6. Fumo, Nelson, 2014. "A review on the basics of building energy estimation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 53-60.
    7. Wang, Xiaoxin & Kendrick, Christopher & Ogden, Raymond & Walliman, Nicholas & Baiche, Bousmaha, 2013. "A case study on energy consumption and overheating for a UK industrial building with rooflights," Applied Energy, Elsevier, vol. 104(C), pages 337-344.
    8. Faustino Patiño-Cambeiro & Julia Armesto & Faustino Patiño-Barbeito & Guillermo Bastos, 2016. "Perspectives on Near ZEB Renovation Projects for Residential Buildings: The Spanish Case," Energies, MDPI, vol. 9(8), pages 1-16, August.
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    Cited by:

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