IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i9p2230-d353597.html
   My bibliography  Save this article

A GIS-Based Methodology for Speedy Energy Efficiency Mapping: A Case Study in Bologna

Author

Listed:
  • Jacopo Gaspari

    (Department of Architecture, University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy)

  • Michaela De Giglio

    (Department of Architecture, University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy)

  • Ernesto Antonini

    (Department of Architecture, University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy)

  • Vincenzo Vodola

    (Department of Architecture, University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy)

Abstract

The paper reports a methodology developed to map energy consumption of the building stock at the urban scale on a GIS environment. Energy consumption has been investigated, focusing on the shift from the individual building scale to the district one with the purpose of identifying larger homogenous energy use areas for addressing policies and plans to improve the quality and the performance levels at the city scale. The urban planning zoning concept was extended to the energy issue to include the energy behavior of each zone that depends on the performance of its individual buildings. The methodology generates GIS maps providing a district scale visualization of energy consumption according to shared criteria. A case study in Bologna city (Italy) is provided. In the specific case, the last update of Emilia-Romagna regional urban planning regulation required a mapping action regarding energy efficiency of homogeneous urban portions defined by the General Urban Plan. The main achieved results are (a) a methodology to identify homogeneous areas for analyzing energy consumption; (b) an updated energy map of Bologna Municipality.

Suggested Citation

  • Jacopo Gaspari & Michaela De Giglio & Ernesto Antonini & Vincenzo Vodola, 2020. "A GIS-Based Methodology for Speedy Energy Efficiency Mapping: A Case Study in Bologna," Energies, MDPI, vol. 13(9), pages 1-19, May.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:9:p:2230-:d:353597
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/9/2230/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/9/2230/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Parshall, Lily & Gurney, Kevin & Hammer, Stephen A. & Mendoza, Daniel & Zhou, Yuyu & Geethakumar, Sarath, 2010. "Modeling energy consumption and CO2 emissions at the urban scale: Methodological challenges and insights from the United States," Energy Policy, Elsevier, vol. 38(9), pages 4765-4782, September.
    2. 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.
    3. Tronchin, Lamberto & Fabbri, Kristian, 2012. "Energy Performance Certificate of building and confidence interval in assessment: An Italian case study," Energy Policy, Elsevier, vol. 48(C), pages 176-184.
    4. Ballarini, Ilaria & Corgnati, Stefano Paolo & Corrado, Vincenzo, 2014. "Use of reference buildings to assess the energy saving potentials of the residential building stock: The experience of TABULA project," Energy Policy, Elsevier, vol. 68(C), pages 273-284.
    5. Murphy, Lorraine, 2014. "The influence of the Energy Performance Certificate: The Dutch case," Energy Policy, Elsevier, vol. 67(C), pages 664-672.
    6. Fabbri, Kristian, 2015. "Building and fuel poverty, an index to measure fuel poverty: An Italian case study," Energy, Elsevier, vol. 89(C), pages 244-258.
    7. Droutsa, Kalliopi G. & Kontoyiannidis, Simon & Dascalaki, Elena G. & Balaras, Constantinos A., 2016. "Mapping the energy performance of hellenic residential buildings from EPC (energy performance certificate) data," Energy, Elsevier, vol. 98(C), pages 284-295.
    8. Caputo, Paola & Costa, Gaia & Ferrari, Simone, 2013. "A supporting method for defining energy strategies in the building sector at urban scale," Energy Policy, Elsevier, vol. 55(C), pages 261-270.
    9. Van Hoesen, John & Letendre, Steven, 2010. "Evaluating potential renewable energy resources in Poultney, Vermont: A GIS-based approach to supporting rural community energy planning," Renewable Energy, Elsevier, vol. 35(9), pages 2114-2122.
    10. Theodoridou, Ifigeneia & Karteris, Marinos & Mallinis, Georgios & Papadopoulos, Agis M. & Hegger, Manfred, 2012. "Assessment of retrofitting measures and solar systems' potential in urban areas using Geographical Information Systems: Application to a Mediterranean city," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 6239-6261.
    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. Silvia Soutullo & Emanuela Giancola & María Nuria Sánchez & José Antonio Ferrer & David García & María José Súarez & Jesús Ignacio Prieto & Elena Antuña-Yudego & Juan Luís Carús & Miguel Ángel Fernánd, 2020. "Methodology for Quantifying the Energy Saving Potentials Combining Building Retrofitting, Solar Thermal Energy and Geothermal Resources," Energies, MDPI, vol. 13(22), pages 1-25, November.
    2. Aleksandar S. Anđelković & Miroslav Kljajić & Dušan Macura & Vladimir Munćan & Igor Mujan & Mladen Tomić & Željko Vlaović & Borivoj Stepanov, 2021. "Building Energy Performance Certificate—A Relevant Indicator of Actual Energy Consumption and Savings?," Energies, MDPI, vol. 14(12), pages 1-19, June.
    3. Beril Alpagut & Arantza Lopez Romo & Patxi Hernández & Oya Tabanoğlu & Nekane Hermoso Martinez, 2021. "A GIS-Based Multicriteria Assessment for Identification of Positive Energy Districts Boundary in Cities," Energies, MDPI, vol. 14(22), pages 1-18, November.

    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. Pagliaro, Francesca & Hugony, Francesca & Zanghirella, Fabio & Basili, Rossano & Misceo, Monica & Colasuonno, Luca & Del Fatto, Vincenzo, 2021. "Assessing building energy performance and energy policy impact through the combined analysis of EPC data – The Italian case study of SIAPE," Energy Policy, Elsevier, vol. 159(C).
    2. Delmastro, Chiara & Mutani, Guglielmina & Corgnati, Stefano Paolo, 2016. "A supporting method for selecting cost-optimal energy retrofit policies for residential buildings at the urban scale," Energy Policy, Elsevier, vol. 99(C), pages 42-56.
    3. 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.
    4. Krarti, Moncef & Aldubyan, Mohammad & Williams, Eric, 2020. "Residential building stock model for evaluating energy retrofit programs in Saudi Arabia," Energy, Elsevier, vol. 195(C).
    5. Pasichnyi, Oleksii & Wallin, Jörgen & Levihn, Fabian & Shahrokni, Hossein & Kordas, Olga, 2019. "Energy performance certificates — New opportunities for data-enabled urban energy policy instruments?," Energy Policy, Elsevier, vol. 127(C), pages 486-499.
    6. 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.
    7. Bischof, Julian & Duffy, Aidan, 2022. "Life-cycle assessment of non-domestic building stocks: A meta-analysis of current modelling methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    8. Wang, Wei & Hong, Tianzhen & Xu, Xiaodong & Chen, Jiayu & Liu, Ziang & Xu, Ning, 2019. "Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm," Applied Energy, Elsevier, vol. 248(C), pages 217-230.
    9. Heidenthaler, Daniel & Deng, Yingwen & Leeb, Markus & Grobbauer, Michael & Kranzl, Lukas & Seiwald, Lena & Mascherbauer, Philipp & Reindl, Patricia & Bednar, Thomas, 2023. "Automated energy performance certificate based urban building energy modelling approach for predicting heat load profiles of districts," Energy, Elsevier, vol. 278(PB).
    10. Shen, Pengyuan & Wang, Huilong, 2024. "Archetype building energy modeling approaches and applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    11. Hanan S.S. Ibrahim & Ahmed Z. Khan & Shady Attia & Yehya Serag, 2021. "Classification of Heritage Residential Building Stock and Defining Sustainable Retrofitting Scenarios in Khedivial Cairo," Sustainability, MDPI, vol. 13(2), pages 1-26, January.
    12. Brandão de Vasconcelos, Ana & Pinheiro, Manuel Duarte & Manso, Armando & Cabaço, António, 2015. "A Portuguese approach to define reference buildings for cost-optimal methodologies," Applied Energy, Elsevier, vol. 140(C), pages 316-328.
    13. 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).
    14. 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.
    15. Pasichnyi, Oleksii & Wallin, Jörgen & Kordas, Olga, 2019. "Data-driven building archetypes for urban building energy modelling," Energy, Elsevier, vol. 181(C), pages 360-377.
    16. Franke, Melanie & Nadler, Claudia, 2019. "Energy efficiency in the German residential housing market: Its influence on tenants and owners," Energy Policy, Elsevier, vol. 128(C), pages 879-890.
    17. Edgar Lorenzo-Sáez & José-Vicente Oliver-Villanueva & Eloina Coll-Aliaga & Lenin-Guillermo Lemus-Zúñiga & Victoria Lerma-Arce & Antonio Reig-Fabado, 2020. "Energy Efficiency and GHG Emissions Mapping of Buildings for Decision-Making Processes against Climate Change at the Local Level," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
    18. Hardy, A. & Glew, D., 2019. "An analysis of errors in the Energy Performance certificate database," Energy Policy, Elsevier, vol. 129(C), pages 1168-1178.
    19. Bianchi, Carlo & Zhang, Liang & Goldwasser, David & Parker, Andrew & Horsey, Henry, 2020. "Modeling occupancy-driven building loads for large and diversified building stocks through the use of parametric schedules," Applied Energy, Elsevier, vol. 276(C).
    20. Kazas, Georgios & Fabrizio, Enrico & Perino, Marco, 2017. "Energy demand profile generation with detailed time resolution at an urban district scale: A reference building approach and case study," Applied Energy, Elsevier, vol. 193(C), pages 243-262.

    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:13:y:2020:i:9:p:2230-:d:353597. 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.