IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i15p5780-d1209686.html
   My bibliography  Save this article

Assessment of Subsidization Strategies for Multi-Objective Optimization of Energy Efficiency Measures for Building Renovation at District Scale

Author

Listed:
  • Federico Battini

    (Competence Centre for Mountain Innovation Ecosystems, Free University of Bozen-Bolzano, 39100 Bolzano, Italy)

  • Giovanni Pernigotto

    (Competence Centre for Mountain Innovation Ecosystems, Free University of Bozen-Bolzano, 39100 Bolzano, Italy
    Faculty of Engineering, Free University of Bozen-Bolzano, 39100 Bolzano, Italy)

  • Federica Morandi

    (Faculty of Engineering, Free University of Bozen-Bolzano, 39100 Bolzano, Italy)

  • Andrea Gasparella

    (Faculty of Engineering, Free University of Bozen-Bolzano, 39100 Bolzano, Italy)

  • Jérôme Henri Kämpf

    (Energy Informatics Group, Idiap Research Institute, 1920 Martigny, Switzerland)

Abstract

In recent years, public authorities around the world have used incentive strategies to encourage the renovation of the existing building stock to meet the set carbon neutrality targets. However, the design of the incentives typically does not consider that the subsidized energy efficiency measures should result in robust long-term improvements with respect to various objectives. Moreover, building energy retrofit analyses are commonly conducted at the individual building level rather than at urban scale, which could instead significantly accelerate the renovation rate. In this context, the current research aims to combine these different factors to support the design of building energy retrofit programs. We developed 21 subsidization strategies and their impact was evaluated on a parametric multi-objective optimization with respect to energy, economic, and environmental performance for a district located in Bolzano, Northern Italy. The optimization was performed considering a set of energy efficiency measures, pertaining to building envelope, climate change, economic scenarios, and two types of energy supplies. The results showed that (1) the impact of climate change is limited for the climate of Bolzano; (2) the type of energy supply strongly influences the economic feasibility of the retrofit investments; (3) when the investment is profitable, the optimal solutions include those measures with the largest impact on energy efficiency; and (4) subsidization strategies modify the number and composition of the Pareto solutions.

Suggested Citation

  • Federico Battini & Giovanni Pernigotto & Federica Morandi & Andrea Gasparella & Jérôme Henri Kämpf, 2023. "Assessment of Subsidization Strategies for Multi-Objective Optimization of Energy Efficiency Measures for Building Renovation at District Scale," Energies, MDPI, vol. 16(15), pages 1-23, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:15:p:5780-:d:1209686
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/15/5780/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/15/5780/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fahad Haneef & Giovanni Pernigotto & Andrea Gasparella & Jérôme Henri Kämpf, 2021. "Application of Urban Scale Energy Modelling and Multi-Objective Optimization Techniques for Building Energy Renovation at District Scale," Sustainability, MDPI, vol. 13(20), pages 1-26, October.
    2. Francesco Asdrubali & Gianluca Grazieschi & Marta Roncone & Francesca Thiebat & Corrado Carbonaro, 2023. "Sustainability of Building Materials: Embodied Energy and Embodied Carbon of Masonry," Energies, MDPI, vol. 16(4), pages 1-28, February.
    3. Cremer, Leo & Weber, Christine, 2022. "Deep energy retrofits: How effective and robust are policy instruments?," Energy Policy, Elsevier, vol. 170(C).
    4. Nguyen, Anh-Tuan & Reiter, Sigrid & Rigo, Philippe, 2014. "A review on simulation-based optimization methods applied to building performance analysis," Applied Energy, Elsevier, vol. 113(C), pages 1043-1058.
    5. Thrampoulidis, Emmanouil & Hug, Gabriela & Orehounig, Kristina, 2023. "Approximating optimal building retrofit solutions for large-scale retrofit analysis," Applied Energy, Elsevier, vol. 333(C).
    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. Benedek Kiss & Jose Dinis Silvestre & Rita Andrade Santos & Zsuzsa Szalay, 2021. "Environmental and Economic Optimisation of Buildings in Portugal and Hungary," Sustainability, MDPI, vol. 13(24), pages 1-19, December.
    2. Guariso, Giorgio & Sangiorgio, Matteo, 2019. "Multi-objective planning of building stock renovation," Energy Policy, Elsevier, vol. 130(C), pages 101-110.
    3. Sun, Alexander Y., 2020. "Optimal carbon storage reservoir management through deep reinforcement learning," Applied Energy, Elsevier, vol. 278(C).
    4. Waibel, Christoph & Evins, Ralph & Carmeliet, Jan, 2019. "Co-simulation and optimization of building geometry and multi-energy systems: Interdependencies in energy supply, energy demand and solar potentials," Applied Energy, Elsevier, vol. 242(C), pages 1661-1682.
    5. Kokaraki, Nikoleta & Hopfe, Christina J. & Robinson, Elaine & Nikolaidou, Elli, 2019. "Testing the reliability of deterministic multi-criteria decision-making methods using building performance simulation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 991-1007.
    6. Ascione, Fabrizio & De Masi, Rosa Francesca & de Rossi, Filippo & Ruggiero, Silvia & Vanoli, Giuseppe Peter, 2016. "Optimization of building envelope design for nZEBs in Mediterranean climate: Performance analysis of residential case study," Applied Energy, Elsevier, vol. 183(C), pages 938-957.
    7. Tian, Wei & Song, Jitian & Li, Zhanyong & de Wilde, Pieter, 2014. "Bootstrap techniques for sensitivity analysis and model selection in building thermal performance analysis," Applied Energy, Elsevier, vol. 135(C), pages 320-328.
    8. Fernandes, Marco S. & Rodrigues, Eugénio & Gaspar, Adélio Rodrigues & Costa, José J. & Gomes, Álvaro, 2019. "The impact of thermal transmittance variation on building design in the Mediterranean region," Applied Energy, Elsevier, vol. 239(C), pages 581-597.
    9. Niemelä, Tuomo & Kosonen, Risto & Jokisalo, Juha, 2016. "Cost-optimal energy performance renovation measures of educational buildings in cold climate," Applied Energy, Elsevier, vol. 183(C), pages 1005-1020.
    10. Eva Lucas Segarra & Germán Ramos Ruiz & Vicente Gutiérrez González & Antonis Peppas & Carlos Fernández Bandera, 2020. "Impact Assessment for Building Energy Models Using Observed vs. Third-Party Weather Data Sets," Sustainability, MDPI, vol. 12(17), pages 1-27, August.
    11. Tatchell-Evans, Morgan & Kapur, Nik & Summers, Jonathan & Thompson, Harvey & Oldham, Dan, 2017. "An experimental and theoretical investigation of the extent of bypass air within data centres employing aisle containment, and its impact on power consumption," Applied Energy, Elsevier, vol. 186(P3), pages 457-469.
    12. Lin, Yu-Hao & Tsai, Kang-Ting & Lin, Min-Der & Yang, Ming-Der, 2016. "Design optimization of office building envelope configurations for energy conservation," Applied Energy, Elsevier, vol. 171(C), pages 336-346.
    13. Shadram, Farshid & Bhattacharjee, Shimantika & Lidelöw, Sofia & Mukkavaara, Jani & Olofsson, Thomas, 2020. "Exploring the trade-off in life cycle energy of building retrofit through optimization," Applied Energy, Elsevier, vol. 269(C).
    14. 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.
    15. Bingham, Raymond D. & Agelin-Chaab, Martin & Rosen, Marc A., 2019. "Whole building optimization of a residential home with PV and battery storage in The Bahamas," Renewable Energy, Elsevier, vol. 132(C), pages 1088-1103.
    16. García Kerdan, Iván & Raslan, Rokia & Ruyssevelt, Paul & Morillón Gálvez, David, 2017. "A comparison of an energy/economic-based against an exergoeconomic-based multi-objective optimisation for low carbon building energy design," Energy, Elsevier, vol. 128(C), pages 244-263.
    17. Cristina Brunelli & Francesco Castellani & Alberto Garinei & Lorenzo Biondi & Marcello Marconi, 2016. "A Procedure to Perform Multi-Objective Optimization for Sustainable Design of Buildings," Energies, MDPI, vol. 9(11), pages 1-15, November.
    18. Nayara R. M. Sakiyama & Joyce C. Carlo & Leonardo Mazzaferro & Harald Garrecht, 2021. "Building Optimization through a Parametric Design Platform: Using Sensitivity Analysis to Improve a Radial-Based Algorithm Performance," Sustainability, MDPI, vol. 13(10), pages 1-25, May.
    19. 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.
    20. George M. Stavrakakis & Dimitris Al. Katsaprakakis & Markos Damasiotis, 2021. "Basic Principles, Most Common Computational Tools, and Capabilities for Building Energy and Urban Microclimate Simulations," Energies, MDPI, vol. 14(20), pages 1-41, October.

    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:15:p:5780-:d:1209686. 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.