IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i9p3944-d1141311.html
   My bibliography  Save this article

Toward Improved Urban Building Energy Modeling Using a Place-Based Approach

Author

Listed:
  • Guglielmina Mutani

    (DENERG-Department of Energy, Politecnico di Torino, Corso Duca Degli Abruzzi 24, 10129 Torino, Italy)

  • Pamela Vocale

    (Department of Engineering and Architecture, University of Parma, Parco Area Delle Scienze 181/A, 43124 Parma, Italy)

  • Kavan Javanroodi

    (Division of Building Physics, Department of Building and Environmental Technology, Faculty of Engineering, LTH Lund University, 22363 Lund, Sweden)

Abstract

Urban building energy models present a valuable tool for promoting energy efficiency in building design and control, as well as for managing urban energy systems. However, the current models often overlook the importance of site-specific characteristics, as well as the spatial attributes and variations within a specific area of a city. This methodological paper moves beyond state-of-the-art urban building energy modeling and urban-scale energy models by incorporating an improved place-based approach to address this research gap. This approach allows for a more in-depth understanding of the interactions behind spatial patterns and an increase in the number and quality of energy-related variables. The paper outlines a detailed description of the steps required to create urban energy models and presents sample application results for each model. The pre-modeling phase is highlighted as a critical step in which the geo-database used to create the models is collected, corrected, and integrated. We also discuss the use of spatial auto-correlation within the geo-database, which introduces new spatial-temporal relationships that describe the territorial clusters of complex urban environment systems. This study identifies and redefines three primary types of urban energy modeling, including process-driven, data-driven, and hybrid models, in the context of place-based approaches. The challenges associated with each type are highlighted, with emphasis on data requirements and availability concerns. The study concludes that a place-based approach is crucial to achieving energy self-sufficiency in districts or cities in urban-scale building energy-modeling studies.

Suggested Citation

  • Guglielmina Mutani & Pamela Vocale & Kavan Javanroodi, 2023. "Toward Improved Urban Building Energy Modeling Using a Place-Based Approach," Energies, MDPI, vol. 16(9), pages 1-17, May.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:9:p:3944-:d:1141311
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/9/3944/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/9/3944/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rüdiger Wink & Laura Kirchner & Florian Koch & Daniel Speda, 2016. "There are Many Roads to Reindustrialization and Resilience: Place-based Approaches in Three German Urban Regions," European Planning Studies, Taylor & Francis Journals, vol. 24(3), pages 463-488, March.
    2. Guglielmina Mutani & Valeria Todeschi, 2021. "Optimization of Costs and Self-Sufficiency for Roof Integrated Photovoltaic Technologies on Residential Buildings," Energies, MDPI, vol. 14(13), pages 1-25, July.
    3. Bouw, Kathelijne & Noorman, Klaas Jan & Wiekens, Carina J. & Faaij, André, 2021. "Local energy planning in the built environment: An analysis of model characteristics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    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. A. T. D. Perera & Kavan Javanroodi & Dasaraden Mauree & Vahid M. Nik & Pietro Florio & Tianzhen Hong & Deliang Chen, 2023. "Challenges resulting from urban density and climate change for the EU energy transition," Nature Energy, Nature, vol. 8(4), pages 397-412, April.
    6. Østergård, Torben & Jensen, Rasmus Lund & Maagaard, Steffen Enersen, 2018. "A comparison of six metamodeling techniques applied to building performance simulations," Applied Energy, Elsevier, vol. 211(C), pages 89-103.
    7. 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.
    8. Francesco Mancini & Sabrina Romano & Gianluigi Lo Basso & Jacopo Cimaglia & Livio de Santoli, 2020. "How the Italian Residential Sector Could Contribute to Load Flexibility in Demand Response Activities: A Methodology for Residential Clustering and Developing a Flexibility Strategy," Energies, MDPI, vol. 13(13), pages 1-25, July.
    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. 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.
    3. Oraiopoulos, A. & Howard, B., 2022. "On the accuracy of Urban Building Energy Modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    4. 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.
    5. Damianakis, Nikolaos & Mouli, Gautham Ram Chandra & Bauer, Pavol & Yu, Yunhe, 2023. "Assessing the grid impact of Electric Vehicles, Heat Pumps & PV generation in Dutch LV distribution grids," Applied Energy, Elsevier, vol. 352(C).
    6. Omar Shafqat & Elena Malakhatka & Nina Chrobot & Per Lundqvist, 2021. "End Use Energy Services Framework Co-Creation with Multiple Stakeholders—A Living Lab-Based Case Study," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
    7. Anna Kipping & Erik Trømborg, 2017. "Modeling Aggregate Hourly Energy Consumption in a Regional Building Stock," Energies, MDPI, vol. 11(1), pages 1-20, December.
    8. 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.
    9. Estiri, Hossein, 2014. "Building and household X-factors and energy consumption at the residential sector," Energy Economics, Elsevier, vol. 43(C), pages 178-184.
    10. 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).
    11. Ijaz Ul Haq & Amin Ullah & Samee Ullah Khan & Noman Khan & Mi Young Lee & Seungmin Rho & Sung Wook Baik, 2021. "Sequential Learning-Based Energy Consumption Prediction Model for Residential and Commercial Sectors," Mathematics, MDPI, vol. 9(6), pages 1-17, March.
    12. Wang, Manyu & Wei, Chu, 2024. "Toward sustainable heating: Assessment of the carbon mitigation potential from residential heating in northern rural China," Energy Policy, Elsevier, vol. 190(C).
    13. Dujuan Yang & Harry Timmermans & Aloys Borgers, 2016. "The prevalence of context-dependent adjustment of activity-travel patterns in energy conservation strategies: results from a mixture-amount stated adaptation experiment," Transportation, Springer, vol. 43(1), pages 79-100, January.
    14. 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).
    15. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    16. Szajkó, Gabriella & Rácz, Viktor József & Kis, András, 2024. "The role of price incentives in enhancing carbon sequestration in the forestry sector of Hungary," Forest Policy and Economics, Elsevier, vol. 158(C).
    17. Filippín, Celina & Ricard, Florencia & Flores Larsen, Silvana & Santamouris, Mattheos, 2017. "Retrospective analysis of the energy consumption of single-family dwellings in central Argentina. Retrofitting and adaptation to the climate change," Renewable Energy, Elsevier, vol. 101(C), pages 1226-1241.
    18. Dieckhoener, Caroline & Hecking, Harald, 2012. "Greenhouse Gas Abatement Cost Curves of the Residential Heating Market – a Microeconomic Approach," EWI Working Papers 2012-16, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    19. Rafael de Arce & Ramón Mahía, 2019. "Drivers of Electricity Poverty in Spanish Dwellings: A Quantile Regression Approach," Energies, MDPI, vol. 12(11), pages 1-18, May.
    20. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A three-stage optimization methodology for envelope design of passive house considering energy demand, thermal comfort and cost," Energy, Elsevier, vol. 192(C).

    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:16:y:2023:i:9:p:3944-:d:1141311. 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.