IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i4p1525-d752769.html
   My bibliography  Save this article

The Impact of Detail, Shadowing and Thermal Zoning Levels on Urban Building Energy Modelling (UBEM) on a District Scale

Author

Listed:
  • Xavier Faure

    (Research Group for Urban Analytics and Transitions (UrbanT), Department of Sustainable Development, Environmental Science and Engineering (SEED), KTH Royal Institute of Technology, Teknikringen 10B, 100 44 Stockholm, Sweden)

  • Tim Johansson

    (Research Group for Urban Analytics and Transitions (UrbanT), Department of Sustainable Development, Environmental Science and Engineering (SEED), KTH Royal Institute of Technology, Teknikringen 10B, 100 44 Stockholm, Sweden)

  • Oleksii Pasichnyi

    (Research Group for Urban Analytics and Transitions (UrbanT), Department of Sustainable Development, Environmental Science and Engineering (SEED), KTH Royal Institute of Technology, Teknikringen 10B, 100 44 Stockholm, Sweden)

Abstract

New modelling tools are required to accelerate the decarbonisation of the building sector. Urban building energy modelling (UBEM) has recently emerged as an attractive paradigm for analysing building energy performance at district and urban scales. The balance between the fidelity and accuracy of created UBEMs is known to be the cornerstone of the model’s applicability. This study aimed to analyse the impact of traditionally implicit modeller choices that can greatly affect the overall UBEM performance, namely, (1) the level of detail (LoD) of the buildings’ geometry; (2) thermal zoning; and (3) the surrounding shadowing environment. The analysis was conducted for two urban areas in Stockholm (Sweden) using MUBES—the newly developed UBEM. It is a bottom-up physics-based open-source tool based on Python and EnergyPlus, allowing for calibration and co-simulation. At the building scale, significant impact was detected for all three factors. At the district scale, smaller effects (<2%) were observed for the level of detail and thermal zoning. However, up to 10% difference may be due to the surrounding shadowing environment, so it is recommended that this is considered when using UBEMs even for district scale analyses. Hence, assumptions embedded in UBEMs and the scale of analysis make a difference.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:4:p:1525-:d:752769
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/4/1525/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/4/1525/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cerezo Davila, Carlos & Reinhart, Christoph F. & Bemis, Jamie L., 2016. "Modeling Boston: A workflow for the efficient generation and maintenance of urban building energy models from existing geospatial datasets," Energy, Elsevier, vol. 117(P1), pages 237-250.
    2. Johari, F. & Peronato, G. & Sadeghian, P. & Zhao, X. & Widén, J., 2020. "Urban building energy modeling: State of the art and future prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 128(C).
    3. 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.
    4. 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).
    5. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    6. Xuan Luo & Tianzhen Hong & Yu-Hang Tang, 2020. "Modeling Thermal Interactions between Buildings in an Urban Context," Energies, MDPI, vol. 13(9), pages 1-17, May.
    7. Pasichnyi, Oleksii & Wallin, Jörgen & Kordas, Olga, 2019. "Data-driven building archetypes for urban building energy modelling," Energy, Elsevier, vol. 181(C), pages 360-377.
    8. Chen, Yixing & Hong, Tianzhen, 2018. "Impacts of building geometry modeling methods on the simulation results of urban building energy models," Applied Energy, Elsevier, vol. 215(C), pages 717-735.
    9. Johansson, Tim & Olofsson, Thomas & Mangold, Mikael, 2017. "Development of an energy atlas for renovation of the multifamily building stock in Sweden," Applied Energy, Elsevier, vol. 203(C), pages 723-736.
    10. Sofie Pandis Iverot & Nils Brandt, 2011. "The development of a sustainable urban district in Hammarby Sjöstad, Stockholm, Sweden?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 13(6), pages 1043-1064, December.
    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. 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.
    2. Shen, Pengyuan & Wang, Huilong, 2024. "Archetype building energy modeling approaches and applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).

    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. Valeria Todeschi & Roberto Boghetti & Jérôme H. Kämpf & Guglielmina Mutani, 2021. "Evaluation of Urban-Scale Building Energy-Use Models and Tools—Application for the City of Fribourg, Switzerland," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    2. Shen, Pengyuan & Wang, Huilong, 2024. "Archetype building energy modeling approaches and applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    3. 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).
    4. 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.
    5. Yanxia Li & Chao Wang & Sijie Zhu & Junyan Yang & Shen Wei & Xinkai Zhang & Xing Shi, 2020. "A Comparison of Various Bottom-Up Urban Energy Simulation Methods Using a Case Study in Hangzhou, China," Energies, MDPI, vol. 13(18), pages 1-23, September.
    6. Perwez, Usama & Yamaguchi, Yohei & Ma, Tao & Dai, Yanjun & Shimoda, Yoshiyuki, 2022. "Multi-scale GIS-synthetic hybrid approach for the development of commercial building stock energy model," Applied Energy, Elsevier, vol. 323(C).
    7. 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).
    8. 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.
    9. Paolo Civiero & Jordi Pascual & Joaquim Arcas Abella & Ander Bilbao Figuero & Jaume Salom, 2021. "PEDRERA. Positive Energy District Renovation Model for Large Scale Actions," Energies, MDPI, vol. 14(10), pages 1-21, May.
    10. 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).
    11. Avichal Malhotra & Simon Raming & Jérôme Frisch & Christoph van Treeck, 2021. "Open-Source Tool for Transforming CityGML Levels of Detail," Energies, MDPI, vol. 14(24), pages 1-26, December.
    12. Shiyi Song & Hong Leng & Ran Guo, 2022. "Multi-Agent-Based Model for the Urban Macro-Level Impact Factors of Building Energy Consumption on Different Types of Land," Land, MDPI, vol. 11(11), pages 1-24, November.
    13. Prataviera, Enrico & Vivian, Jacopo & Lombardo, Giulia & Zarrella, Angelo, 2022. "Evaluation of the impact of input uncertainty on urban building energy simulations using uncertainty and sensitivity analysis," Applied Energy, Elsevier, vol. 311(C).
    14. Yang, Xiu'e & Liu, Shuli & Zou, Yuliang & Ji, Wenjie & Zhang, Qunli & Ahmed, Abdullahi & Han, Xiaojing & Shen, Yongliang & Zhang, Shaoliang, 2022. "Energy-saving potential prediction models for large-scale building: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    15. Oraiopoulos, A. & Howard, B., 2022. "On the accuracy of Urban Building Energy Modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    16. Niall Buckley & Gerald Mills & Samuel Letellier-Duchesne & Khadija Benis, 2021. "Designing an Energy-Resilient Neighbourhood Using an Urban Building Energy Model," Energies, MDPI, vol. 14(15), pages 1-17, July.
    17. Vahid-Ghavidel, Morteza & Jafari, Mehdi & Letellier-Duchesne, Samuel & Berzolla, Zachary & Reinhart, Christoph & Botterud, Audun, 2024. "Integrated energy demand-supply modeling for low-carbon neighborhood planning," Applied Energy, Elsevier, vol. 358(C).
    18. Johari, F. & Peronato, G. & Sadeghian, P. & Zhao, X. & Widén, J., 2020. "Urban building energy modeling: State of the art and future prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 128(C).
    19. 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.
    20. 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.

    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:15:y:2022:i:4:p:1525-:d:752769. 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.