IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i6p2599-d1361553.html
   My bibliography  Save this article

Validating ‘GIS-UBEM’—A Residential Open Data-Driven Urban Building Energy Model

Author

Listed:
  • Javier García-López

    (Instituto Universitario de Arquitectura y Ciencias de La Construcción, Escuela Técnica Superior de Arquitectura, Universidad de Sevilla, Av. de la Reina Mercedes, 2, 41012 Sevilla, Spain)

  • Juan José Sendra

    (Instituto Universitario de Arquitectura y Ciencias de La Construcción, Escuela Técnica Superior de Arquitectura, Universidad de Sevilla, Av. de la Reina Mercedes, 2, 41012 Sevilla, Spain)

  • Samuel Domínguez-Amarillo

    (Instituto Universitario de Arquitectura y Ciencias de La Construcción, Escuela Técnica Superior de Arquitectura, Universidad de Sevilla, Av. de la Reina Mercedes, 2, 41012 Sevilla, Spain)

Abstract

The study of energy consumption in buildings, particularly residential ones, brings with it significant socio-economic and environmental implications, as it accounts for approximately 40% of CO 2 emissions, 18% in the case of residential buildings, in Europe. On a number of levels, energy consumption serves as a key parameter in urban sustainability indicators and energy plans. Access to data on energy consumption is crucial for energy planning, management, knowledge generation, and awareness. Urban Building Energy Models (UBEMs), which are emerging tools for simulating energy consumption at neighborhood scale, allow for more efficient intervention and energy rehabilitation planning. However, UBEM validation requires reliable reference data, which are often challenging to obtain at urban scale due to privacy concerns and data accessibility issues. Recent advances, such as automation and open data utilization, are proving promising in addressing these challenges. This study aims to provide a standardized UBEM validation process by presenting a case study that was carried out utilizing open data to develop bottom-up engineering models of residential energy demand at urban scale, with a resolution level of individual buildings, and a subsequent adjustment and validation using reference tools. This study confirms that the validated GIS-UBEM model heating and cooling demands and consumption fall within the confidence bands of ±15% and ±12.5%, i.e., the confidence bands required for the approval of official alternative simulation methods for energy certification. This paves the way for its application in urban-scale studies and practices with a well-established margin of confidence, covering a wide range of building typologies, construction models, and climates comparable to those considered in the validation process. The primary application of this model is to determine the starting point and subsequent evaluation of improvement scenarios at a district scale, examining issues such as massive energy rehabilitation interventions, energy planning, demand analysis, vulnerability studies, etc.

Suggested Citation

  • Javier García-López & Juan José Sendra & Samuel Domínguez-Amarillo, 2024. "Validating ‘GIS-UBEM’—A Residential Open Data-Driven Urban Building Energy Model," Sustainability, MDPI, vol. 16(6), pages 1-19, March.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:6:p:2599-:d:1361553
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/6/2599/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/6/2599/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ang, Yu Qian & Berzolla, Zachary Michael & Reinhart, Christoph F., 2020. "From concept to application: A review of use cases in urban building energy modeling," Applied Energy, Elsevier, vol. 279(C).
    2. Li, Wenliang & Zhou, Yuyu & Cetin, Kristen & Eom, Jiyong & Wang, Yu & Chen, Gang & Zhang, Xuesong, 2017. "Modeling urban building energy use: A review of modeling approaches and procedures," Energy, Elsevier, vol. 141(C), pages 2445-2457.
    3. Guglielmina Mutani & Maryam Alehasin & Yasemin Usta & Francesco Fiermonte & Angelo Mariano, 2023. "Statistical Building Energy Model from Data Collection, Place-Based Assessment to Sustainable Scenarios for the City of Milan," Sustainability, MDPI, vol. 15(20), pages 1-36, October.
    Full references (including those not matched with items on IDEAS)

    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. Rafael Campamà Pizarro & Ricardo Bernardo & Maria Wall, 2023. "Streamlining Building Energy Modelling Using Open Access Databases—A Methodology towards Decarbonisation of Residential Buildings in Sweden," Sustainability, MDPI, vol. 15(5), pages 1-17, February.
    2. Kobashi, Takuro & Choi, Younghun & Hirano, Yujiro & Yamagata, Yoshiki & Say, Kelvin, 2022. "Rapid rise of decarbonization potentials of photovoltaics plus electric vehicles in residential houses over commercial districts," Applied Energy, Elsevier, vol. 306(PB).
    3. Oraiopoulos, A. & Howard, B., 2022. "On the accuracy of Urban Building Energy Modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    4. Ehsan Kamel, 2022. "A Systematic Literature Review of Physics-Based Urban Building Energy Modeling (UBEM) Tools, Data Sources, and Challenges for Energy Conservation," Energies, MDPI, vol. 15(22), pages 1-24, November.
    5. Yael Nidam & Ali Irani & Jamie Bemis & Christoph Reinhart, 2023. "Census-based urban building energy modeling to evaluate the effectiveness of retrofit programs," Environment and Planning B, , vol. 50(9), pages 2394-2406, November.
    6. 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.
    7. Tian, Shen & Shao, Shuangquan & Liu, Bin, 2019. "Investigation on transient energy consumption of cold storages: Modeling and a case study," Energy, Elsevier, vol. 180(C), pages 1-9.
    8. 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).
    9. Younghun Choi & Takuro Kobashi & Yoshiki Yamagata & Akito Murayama, 2021. "Assessment of waterfront office redevelopment plan on optimal building energy demand and rooftop photovoltaics for urban decarbonization," Papers 2108.09029, arXiv.org.
    10. Xavier Faure & Tim Johansson & Oleksii Pasichnyi, 2022. "The Impact of Detail, Shadowing and Thermal Zoning Levels on Urban Building Energy Modelling (UBEM) on a District Scale," Energies, MDPI, vol. 15(4), pages 1-18, February.
    11. Johari, F. & Lindberg, O. & Ramadhani, U.H. & Shadram, F. & Munkhammar, J. & Widén, J., 2024. "Analysis of large-scale energy retrofit of residential buildings and their impact on the electricity grid using a validated UBEM," Applied Energy, Elsevier, vol. 361(C).
    12. Moore, David & Webb, Amanda L., 2022. "Evaluating energy burden at the urban scale: A spatial regression approach in Cincinnati, Ohio," Energy Policy, Elsevier, vol. 160(C).
    13. Shamsi, Mohammad Haris & Ali, Usman & Mangina, Eleni & O’Donnell, James, 2021. "Feature assessment frameworks to evaluate reduced-order grey-box building energy models," Applied Energy, Elsevier, vol. 298(C).
    14. Stefano Converso & Paolo Civiero & Stefano Ciprigno & Ivana Veselinova & Saffa Riffat, 2023. "Toward a Fast but Reliable Energy Performance Evaluation Method for Existing Residential Building Stock," Energies, MDPI, vol. 16(9), pages 1-24, May.
    15. Alaia Sola & Cristina Corchero & Jaume Salom & Manel Sanmarti, 2018. "Simulation Tools to Build Urban-Scale Energy Models: A Review," Energies, MDPI, vol. 11(12), pages 1-24, November.
    16. Christoph Sejkora & Lisa Kühberger & Fabian Radner & Alexander Trattner & Thomas Kienberger, 2020. "Exergy as Criteria for Efficient Energy Systems—A Spatially Resolved Comparison of the Current Exergy Consumption, the Current Useful Exergy Demand and Renewable Exergy Potential," Energies, MDPI, vol. 13(4), pages 1-51, February.
    17. Yamaguchi, Yohei & Shoda, Yuto & Yoshizawa, Shinya & Imai, Tatsuya & Perwez, Usama & Shimoda, Yoshiyuki & Hayashi, Yasuhiro, 2023. "Feasibility assessment of net zero-energy transformation of building stock using integrated synthetic population, building stock, and power distribution network framework," Applied Energy, Elsevier, vol. 333(C).
    18. Mastrucci, Alessio & Marvuglia, Antonino & Benetto, Enrico & Leopold, Ulrich, 2020. "A spatio-temporal life cycle assessment framework for building renovation scenarios at the urban scale," Renewable and Sustainable Energy Reviews, Elsevier, vol. 126(C).
    19. Martin Eriksson & Jan Akander & Bahram Moshfegh, 2022. "Investigating Energy Use in a City District in Nordic Climate Using Energy Signature," Energies, MDPI, vol. 15(5), pages 1-22, March.
    20. Aldubyan, Mohammad & Krarti, Moncef, 2022. "Impact of stay home living on energy demand of residential buildings: Saudi Arabian case study," Energy, Elsevier, vol. 238(PA).

    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:jsusta:v:16:y:2024:i:6:p:2599-:d:1361553. 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.