IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v9y2017i7p1252-d105011.html
   My bibliography  Save this article

Multicriteria Spatial Decision Support Systems for Future Urban Energy Retrofitting Scenarios

Author

Listed:
  • Patrizia Lombardi

    (InterUniversity Department of Regional and Urban Studies and Planning (DIST), Polytechnic University of Turin, 39 Viale Mattioli, 10125 Turin, Italy)

  • Francesca Abastante

    (InterUniversity Department of Regional and Urban Studies and Planning (DIST), Polytechnic University of Turin, 39 Viale Mattioli, 10125 Turin, Italy)

  • Sara Torabi Moghadam

    (InterUniversity Department of Regional and Urban Studies and Planning (DIST), Polytechnic University of Turin, 39 Viale Mattioli, 10125 Turin, Italy)

  • Jacopo Toniolo

    (InterUniversity Department of Regional and Urban Studies and Planning (DIST), Polytechnic University of Turin, 39 Viale Mattioli, 10125 Turin, Italy)

Abstract

Nowadays, there is an increasing concern about sustainable urban energy development taking into account national priorities of each city. Many cities have started to define future strategies and plans to reduce energy consumption and greenhouse gas emissions. Urban energy scenarios involve the consideration of a wide range of conflicting criteria, both socio-economic and environmental ones. Moreover, decision-makers (DMs) require proper tools that can support their choices in a context of multiple stakeholders and a long-term perspective. In this context, Multicriteria Spatial Decision Support Systems (MC-SDSS) are often used in order to define and analyze urban scenarios since they support the comparison of different solutions, based on a combination of multiple factors. The main problem, in relation to urban energy retrofitting scenarios, is the lack of appropriate knowledge and evaluation criteria. The latter are crucial for delivering and assessing urban energy scenarios through a MC-SDSS tool. The main goal of this paper is to analyze and test two different methods for the definition and ranking of the evaluation criteria. More specifically, the paper presents an on-going research study related to the development of a MC-SDSS tool able to identify and evaluate alternative energy urban scenarios in a long-term period perspective. This study refers to two Smart City and Communities research projects, namely: DIMMER (District Information Modeling and Management for Energy Reduction) and EEB (Zero Energy Buildings in Smart Urban Districts).

Suggested Citation

  • Patrizia Lombardi & Francesca Abastante & Sara Torabi Moghadam & Jacopo Toniolo, 2017. "Multicriteria Spatial Decision Support Systems for Future Urban Energy Retrofitting Scenarios," Sustainability, MDPI, vol. 9(7), pages 1-13, July.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:7:p:1252-:d:105011
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/9/7/1252/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/9/7/1252/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Chalal, Moulay Larbi & Benachir, Medjdoub & White, Michael & Shrahily, Raid, 2016. "Energy planning and forecasting approaches for supporting physical improvement strategies in the building sector: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 761-776.
    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. Ilaria Marotta & Francesco Guarino & Sonia Longo & Maurizio Cellura, 2021. "Environmental Sustainability Approaches and Positive Energy Districts: A Literature Review," Sustainability, MDPI, vol. 13(23), pages 1-45, November.
    2. Sławomira Hajduk, 2021. "Multi-Criteria Analysis of Smart Cities on the Example of the Polish Cities," Resources, MDPI, vol. 10(5), pages 1-23, May.
    3. Sławomira Hajduk & Dorota Jelonek, 2021. "A Decision-Making Approach Based on TOPSIS Method for Ranking Smart Cities in the Context of Urban Energy," Energies, MDPI, vol. 14(9), pages 1-23, May.
    4. Grazia Napoli & Rossella Corrao & Gianluca Scaccianoce & Simona Barbaro & Laura Cirrincione, 2022. "Public and Private Economic Feasibility of Green Areas as a Passive Energy Measure: A Case Study in the Mediterranean City of Trapani in Southern Italy," Sustainability, MDPI, vol. 14(4), pages 1-20, February.
    5. Jhon Ricardo Escorcia Hernández & Sara Torabi Moghadam & Patrizia Lombardi, 2023. "Sustainability Assessment in Social Housing Environments: An Inclusive Indicators Selection in Colombian Post-Pandemic Cities," Sustainability, MDPI, vol. 15(3), pages 1-24, February.
    6. Simona Barbaro & Grazia Napoli, 2023. "Energy Communities in Urban Areas: Comparison of Energy Strategy and Economic Feasibility in Italy and Spain," Land, MDPI, vol. 12(7), pages 1-24, June.
    7. Becchio, Cristina & Bottero, Marta Carla & Corgnati, Stefano Paolo & Dell’Anna, Federico, 2018. "Decision making for sustainable urban energy planning: an integrated evaluation framework of alternative solutions for a NZED (Net Zero-Energy District) in Turin," Land Use Policy, Elsevier, vol. 78(C), pages 803-817.
    8. Cinzia Colapinto & Raja Jayaraman & Fouad Ben Abdelaziz & Davide La Torre, 2020. "Environmental sustainability and multifaceted development: multi-criteria decision models with applications," Annals of Operations Research, Springer, vol. 293(2), pages 405-432, October.
    9. Arturas Kaklauskas & Gintautas Dzemyda & Laura Tupenaite & Ihar Voitau & Olga Kurasova & Jurga Naimaviciene & Yauheni Rassokha & Loreta Kanapeckiene, 2018. "Artificial Neural Network-Based Decision Support System for Development of an Energy-Efficient Built Environment," Energies, MDPI, vol. 11(8), pages 1-20, August.

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Talebi, Behrang & Haghighat, Fariborz & Tuohy, Paul & Mirzaei, Parham A., 2018. "Validation of a community district energy system model using field measured data," Energy, Elsevier, vol. 144(C), pages 694-706.
    7. Joanna Piotrowska-Woroniak & Tomasz Szul, 2022. "Application of a Model Based on Rough Set Theory (RST) to Estimate the Energy Efficiency of Public Buildings," Energies, MDPI, vol. 15(23), pages 1-13, November.
    8. Chévez, Pedro Joaquín & Martini, Irene & Discoli, Carlos, 2019. "Methodology developed for the construction of an urban-energy diagnosis aimed to assess alternative scenarios: An intra-urban approach to foster cities’ sustainability," Applied Energy, Elsevier, vol. 237(C), pages 751-778.
    9. Philipp Rode & Alexandra Gomes & Muhammad Adeel & Fizzah Sajjad & Andreas Koch & Syed Monjur Murshed, 2020. "Between Abundance and Constraints: The Natural Resource Equation of Asia’s Diverging, Higher-Income City Models," Land, MDPI, vol. 9(11), pages 1-33, October.
    10. 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.
    11. 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.
    12. Frayssinet, Loïc & Merlier, Lucie & Kuznik, Frédéric & Hubert, Jean-Luc & Milliez, Maya & Roux, Jean-Jacques, 2018. "Modeling the heating and cooling energy demand of urban buildings at city scale," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2318-2327.
    13. Ángel Luis León-Rodríguez & Rafael Suárez & Pedro Bustamante & Miguel Ángel Campano & David Moreno-Rangel, 2017. "Design and Performance of Test Cells as an Energy Evaluation Model of Facades in a Mediterranean Building Area," Energies, MDPI, vol. 10(11), pages 1-16, November.
    14. Chalal, M.L. & Medjdoub, B. & Bezai, N. & Bull, R. & Zune, M., 2022. "Visualisation in energy eco-feedback systems: A systematic review of good practice," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    15. Mörtberg, Ulla & Goldenberg, Romain & Kalantari, Zahra & Kordas, Olga & Deal, Brian & Balfors, Berit & Cvetkovic, Vladimir, 2017. "Integrating ecosystem services in the assessment of urban energy trajectories – A study of the Stockholm Region," Energy Policy, Elsevier, vol. 100(C), pages 338-349.
    16. Evelien Verellen & Karen Allacker, 2022. "Developing a Building Stock Model to Enable Clustered Renovation—The City of Leuven as Case Study," Sustainability, MDPI, vol. 14(10), pages 1-25, May.
    17. M. Esteban Muñoz H. & Irene Peters, 2014. "Constructing an Urban Microsimulation Model to Assess the Influence of Demographics on Heat Consumption," International Journal of Microsimulation, International Microsimulation Association, vol. 7(1), pages 127-157.
    18. Venkatraj, V. & Dixit, M.K., 2022. "Challenges in implementing data-driven approaches for building life cycle energy assessment: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    19. 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.
    20. Paola Caputo & Costa Gaia & Valentina Zanotto, 2013. "A Methodology for Defining Electricity Demand in Energy Simulations Referred to the Italian Context," Energies, MDPI, vol. 6(12), pages 1-19, December.

    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:9:y:2017:i:7:p:1252-:d:105011. 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.