IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i7p1032-d105203.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/7/1032/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/7/1032/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. 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.
    5. Fumo, Nelson, 2014. "A review on the basics of building energy estimation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 53-60.
    6. 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.
    7. 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.
    8. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Juan García-Cuadrado & Andrea Conserva & Juan Aranda & David Zambrana-Vasquez & Tatiana García-Armingol & Gema Millán, 2022. "Response Surface Method to Calculate Energy Savings Associated with Thermal Comfort Improvement in Buildings," Sustainability, MDPI, vol. 14(5), pages 1-14, March.
    2. Pau Fonseca i Casas & Antoni Fonseca i Casas & Nuria Garrido-Soriano & Alfonso Godoy & Wendys-Carolina Pujols & Jesus Garcia, 2017. "Solution Validation for a Double Façade Prototype," Energies, MDPI, vol. 10(12), pages 1-19, December.
    3. Cristina Piselli & Jessica Romanelli & Matteo Di Grazia & Augusto Gavagni & Elisa Moretti & Andrea Nicolini & Franco Cotana & Francesco Strangis & Henk J. L. Witte & Anna Laura Pisello, 2020. "An Integrated HBIM Simulation Approach for Energy Retrofit of Historical Buildings Implemented in a Case Study of a Medieval Fortress in Italy," Energies, MDPI, vol. 13(10), pages 1-21, May.
    4. Antonio Attanasio & Marco Savino Piscitelli & Silvia Chiusano & Alfonso Capozzoli & Tania Cerquitelli, 2019. "Towards an Automated, Fast and Interpretable Estimation Model of Heating Energy Demand: A Data-Driven Approach Exploiting Building Energy Certificates," Energies, MDPI, vol. 12(7), pages 1-25, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hamburg, Anti & Kuusk, Kalle & Mikola, Alo & Kalamees, Targo, 2020. "Realisation of energy performance targets of an old apartment building renovated to nZEB," Energy, Elsevier, vol. 194(C).
    2. Gourlis, Georgios & Kovacic, Iva, 2017. "Passive measures for preventing summer overheating in industrial buildings under consideration of varying manufacturing process loads," Energy, Elsevier, vol. 137(C), pages 1175-1185.
    3. Ramón Barberán & Diego Colás & Pilar Egea, 2019. "Water Supply and Energy in Residential Buildings: Potential Savings and Financial Profitability," Sustainability, MDPI, vol. 11(1), pages 1-12, January.
    4. Steffen Nielsen & Lars Grundahl, 2018. "District Heating Expansion Potential with Low-Temperature and End-Use Heat Savings," Energies, MDPI, vol. 11(2), pages 1-17, January.
    5. Ernestyna Szpakowska-Loranc, 2021. "Multi-Attribute Analysis of Contemporary Cultural Buildings in the Historic Urban Fabric as Sustainable Spaces—Krakow Case Study," Sustainability, MDPI, vol. 13(11), pages 1-25, May.
    6. Julia Reisinger & Patrick Hollinsky & Iva Kovacic, 2021. "Design Guideline for Flexible Industrial Buildings Integrating Industry 4.0 Parameters," Sustainability, MDPI, vol. 13(19), pages 1-24, September.
    7. López-Ochoa, Luis M. & Las-Heras-Casas, Jesús & López-González, Luis M. & Olasolo-Alonso, Pablo, 2019. "Towards nearly zero-energy buildings in Mediterranean countries: Energy Performance of Buildings Directive evolution and the energy rehabilitation challenge in the Spanish residential sector," Energy, Elsevier, vol. 176(C), pages 335-352.
    8. Kittisak Lohwanitchai & Daranee Jareemit, 2021. "Modeling Energy Efficiency Performance and Cost-Benefit Analysis Achieving Net-Zero Energy Building Design: Case Studies of Three Representative Offices in Thailand," Sustainability, MDPI, vol. 13(9), pages 1-24, May.
    9. Kim, Min-Hwi & Kim, Deukwon & Heo, Jaehyeok & Lee, Dong-Won, 2020. "Energy performance investigation of net plus energy town: Energy balance of the Jincheon Eco-Friendly energy town," Renewable Energy, Elsevier, vol. 147(P1), pages 1784-1800.
    10. Solène Goy & François Maréchal & Donal Finn, 2020. "Data for Urban Scale Building Energy Modelling: Assessing Impacts and Overcoming Availability Challenges," Energies, MDPI, vol. 13(16), pages 1-23, August.
    11. Langevin, J. & Reyna, J.L. & Ebrahimigharehbaghi, S. & Sandberg, N. & Fennell, P. & Nägeli, C. & Laverge, J. & Delghust, M. & Mata, É. & Van Hove, M. & Webster, J. & Federico, F. & Jakob, M. & Camaras, 2020. "Developing a common approach for classifying building stock energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    12. Peep Pihelo & Kalle Kuusk & Targo Kalamees, 2020. "Development and Performance Assessment of Prefabricated Insulation Elements for Deep Energy Renovation of Apartment Buildings," Energies, MDPI, vol. 13(7), pages 1-20, April.
    13. Tomasz Szul & Krzysztof Nęcka & Stanisław Lis, 2021. "Application of the Takagi-Sugeno Fuzzy Modeling to Forecast Energy Efficiency in Real Buildings Undergoing Thermal Improvement," Energies, MDPI, vol. 14(7), pages 1-16, March.
    14. Anti Hamburg & Targo Kalamees, 2018. "The Influence of Energy Renovation on the Change of Indoor Temperature and Energy Use," Energies, MDPI, vol. 11(11), pages 1-15, November.
    15. Jungwon Yoon & Sanghyun Bae, 2020. "Performance Evaluation and Design of Thermo-Responsive SMP Shading Prototypes," Sustainability, MDPI, vol. 12(11), pages 1-35, May.
    16. Amasyali, Kadir & El-Gohary, Nora M., 2018. "A review of data-driven building energy consumption prediction studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1192-1205.
    17. Sun, Kaiyu & Hong, Tianzhen & Taylor-Lange, Sarah C. & Piette, Mary Ann, 2016. "A pattern-based automated approach to building energy model calibration," Applied Energy, Elsevier, vol. 165(C), pages 214-224.
    18. Papineau, Maya & Yassin, Kareman & Newsham, Guy & Brice, Sarah, 2021. "Conditional demand analysis as a tool to evaluate energy policy options on the path to grid decarbonization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    19. Deb, C. & Gelder, L.V. & Spiekman, M. & Pandraud, Guillaume & Jack, R. & Fitton, R., 2021. "Measuring the heat transfer coefficient (HTC) in buildings: A stakeholder's survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    20. Chou, Jui-Sheng & Tran, Duc-Son, 2018. "Forecasting energy consumption time series using machine learning techniques based on usage patterns of residential householders," Energy, Elsevier, vol. 165(PB), pages 709-726.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:1032-:d:105203. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.