IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v268y2020ics0306261920305584.html
   My bibliography  Save this article

A multi-criteria approach to affordable energy-efficient retrofit of primary school buildings

Author

Listed:
  • Moazzen, Nazanin
  • Ashrafian, Touraj
  • Yilmaz, Zerrin
  • Karagüler, Mustafa Erkan

Abstract

The majority of the buildings was built before the energy efficiency prospering in the construction sector. Hence, they are consuming an enormous energy amount that can be preserved considerably by applying some not even advanced retrofit measures. Schools' low budget is a problem that managers are encountered. Thus the high retrofit cost can prevent taking proper actions. However, considering the measures leading to higher energy efficiency with appropriate cost and payback period, together with taking the lifespan of buildings and the economic benefits during this extended period, would make the actions attractive. This research aims at defining a multi-parameter approach to distinguish energy efficient measures with proper cost, payback period and CO2 emission for primary school buildings’ retrofit. It is following the concept of cost-optimal building retrofit introduced by the EPBD-recast. To assess the proposed approach, two typical school buildings were considered as case studies, the model was created and validated by real consumptions, and then some measures were applied to the envelope, mechanical and lighting system. After driven cost-optimal measures, the comfort analyses were conducted and some of the measures were excluded due to worsening the comfort conditions. The results indicate that, in the suitable cost-optimal scenarios, the potential of primary energy savings and CO2 emission reductions are approximately 60%, and savings for global cost would amount to more than 42%, while the payback periods are less than seven years.

Suggested Citation

  • Moazzen, Nazanin & Ashrafian, Touraj & Yilmaz, Zerrin & Karagüler, Mustafa Erkan, 2020. "A multi-criteria approach to affordable energy-efficient retrofit of primary school buildings," Applied Energy, Elsevier, vol. 268(C).
  • Handle: RePEc:eee:appene:v:268:y:2020:i:c:s0306261920305584
    DOI: 10.1016/j.apenergy.2020.115046
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261920305584
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2020.115046?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ascione, Fabrizio & Bianco, Nicola & De Stasio, Claudio & Mauro, Gerardo Maria & Vanoli, Giuseppe Peter, 2016. "Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: A new approach to assess cost-optimality," Applied Energy, Elsevier, vol. 174(C), pages 37-68.
    2. 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.
    3. Wu, Raphael & Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2017. "Multiobjective optimisation of energy systems and building envelope retrofit in a residential community," Applied Energy, Elsevier, vol. 190(C), pages 634-649.
    4. Jiang, Yingni, 2010. "Generation of typical meteorological year for different climates of China," Energy, Elsevier, vol. 35(5), pages 1946-1953.
    5. Salata, Ferdinando & Ciancio, Virgilio & Dell'Olmo, Jacopo & Golasi, Iacopo & Palusci, Olga & Coppi, Massimo, 2020. "Effects of local conditions on the multi-variable and multi-objective energy optimization of residential buildings using genetic algorithms," Applied Energy, Elsevier, vol. 260(C).
    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. Ongpeng, Jason Maximino C. & Rabe, Brian Immanuel B. & Razon, Luis F. & Aviso, Kathleen B. & Tan, Raymond R., 2022. "A multi-criterion decision analysis framework for sustainable energy retrofit in buildings," Energy, Elsevier, vol. 239(PD).
    2. 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).
    3. Huang, He & Wang, Honglei & Hu, Yu-Jie & Li, Chengjiang & Wang, Xiaolin, 2022. "Optimal plan for energy conservation and CO2 emissions reduction of public buildings considering users' behavior: Case of China," Energy, Elsevier, vol. 261(PA).
    4. Hye Gi Kim & Hyun Jun Kim & Chae Hwan Jeon & Myeong Won Chae & Young Hum Cho & Sun Sook Kim, 2020. "Analysis of Energy Saving Effect and Cost Efficiency of ECMs to Upgrade the Building Energy Code," Energies, MDPI, vol. 13(18), pages 1-22, September.
    5. Ružena Králiková & Laura Džuňová & Ervin Lumnitzer & Miriama Piňosová, 2022. "Simulation of Artificial Lighting Using Leading Software to Evaluate Lighting Conditions in the Absence of Daylight in a University Classroom," Sustainability, MDPI, vol. 14(18), pages 1-16, September.
    6. Li, Qing & Zhang, Lianying & Zhang, Limao & Wu, Xianguo, 2021. "Optimizing energy efficiency and thermal comfort in building green retrofit," Energy, Elsevier, vol. 237(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. 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).
    2. Ascione, Fabrizio & Bianco, Nicola & Mauro, Gerardo Maria & Vanoli, Giuseppe Peter, 2019. "A new comprehensive framework for the multi-objective optimization of building energy design: Harlequin," Applied Energy, Elsevier, vol. 241(C), pages 331-361.
    3. Mohamed Hamdy & Gerardo Maria Mauro, 2017. "Multi-Objective Optimization of Building Energy Design to Reconcile Collective and Private Perspectives: CO 2 -eq vs. Discounted Payback Time," Energies, MDPI, vol. 10(7), pages 1-26, July.
    4. Prada, A. & Gasparella, A. & Baggio, P., 2018. "On the performance of meta-models in building design optimization," Applied Energy, Elsevier, vol. 225(C), pages 814-826.
    5. Ascione, Fabrizio & Bianco, Nicola & Mauro, Gerardo Maria & Napolitano, Davide Ferdinando, 2019. "Retrofit of villas on Mediterranean coastlines: Pareto optimization with a view to energy-efficiency and cost-effectiveness," Applied Energy, Elsevier, vol. 254(C).
    6. Ciardiello, Adriana & Rosso, Federica & Dell'Olmo, Jacopo & Ciancio, Virgilio & Ferrero, Marco & Salata, Ferdinando, 2020. "Multi-objective approach to the optimization of shape and envelope in building energy design," Applied Energy, Elsevier, vol. 280(C).
    7. Yeh, Shih-Chuan, 2019. "High performance natural lighting system combined with SPSC," Renewable Energy, Elsevier, vol. 143(C), pages 226-232.
    8. Maria Ferrara & Valentina Monetti & Enrico Fabrizio, 2018. "Cost-Optimal Analysis for Nearly Zero Energy Buildings Design and Optimization: A Critical Review," Energies, MDPI, vol. 11(6), pages 1-32, June.
    9. Torres-Rivas, Alba & Palumbo, Mariana & Haddad, Assed & Cabeza, Luisa F. & Jiménez, Laureano & Boer, Dieter, 2018. "Multi-objective optimisation of bio-based thermal insulation materials in building envelopes considering condensation risk," Applied Energy, Elsevier, vol. 224(C), pages 602-614.
    10. Ferrara, Maria & Rolfo, Andrea & Prunotto, Federico & Fabrizio, Enrico, 2019. "EDeSSOpt – Energy Demand and Supply Simultaneous Optimization for cost-optimized design: Application to a multi-family building," Applied Energy, Elsevier, vol. 236(C), pages 1231-1248.
    11. Petkov, Ivalin & Mavromatidis, Georgios & Knoeri, Christof & Allan, James & Hoffmann, Volker H., 2022. "MANGOret: An optimization framework for the long-term investment planning of building multi-energy system and envelope retrofits," Applied Energy, Elsevier, vol. 314(C).
    12. Cascone, Ylenia & Capozzoli, Alfonso & Perino, Marco, 2018. "Optimisation analysis of PCM-enhanced opaque building envelope components for the energy retrofitting of office buildings in Mediterranean climates," Applied Energy, Elsevier, vol. 211(C), pages 929-953.
    13. Schito, Eva & Conti, Paolo & Testi, Daniele, 2018. "Multi-objective optimization of microclimate in museums for concurrent reduction of energy needs, visitors’ discomfort and artwork preservation risks," Applied Energy, Elsevier, vol. 224(C), pages 147-159.
    14. 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.
    15. Maria Psillaki & Nikolaos Apostolopoulos & Ilias Makris & Panagiotis Liargovas & Sotiris Apostolopoulos & Panos Dimitrakopoulos & George Sklias, 2023. "Hospitals’ Energy Efficiency in the Perspective of Saving Resources and Providing Quality Services through Technological Options: A Systematic Literature Review," Energies, MDPI, vol. 16(2), pages 1-21, January.
    16. Olkkonen, Ville & Hirvonen, Janne & Heljo, Juhani & Syri, Sanna, 2021. "Effectiveness of building stock sustainability measures in a low-carbon energy system: A scenario analysis for Finland until 2050," Energy, Elsevier, vol. 235(C).
    17. Shamsi, Mohammad Haris & Ali, Usman & Mangina, Eleni & O’Donnell, James, 2021. "Feature assessment frameworks to evaluate reduced-order grey-box building energy models," Applied Energy, Elsevier, vol. 298(C).
    18. Li, Honglian & Huang, Jin & Hu, Yao & Wang, Shangyu & Liu, Jing & Yang, Liu, 2021. "A new TMY generation method based on the entropy-based TOPSIS theory for different climatic zones in China," Energy, Elsevier, vol. 231(C).
    19. Li, Chong & Zhou, Dequn & Wang, Hui & Lu, Yuzheng & Li, Dongdong, 2020. "Techno-economic performance study of stand-alone wind/diesel/battery hybrid system with different battery technologies in the cold region of China," Energy, Elsevier, vol. 192(C).
    20. Zhang, Xingxing & Lovati, Marco & Vigna, Ilaria & Widén, Joakim & Han, Mengjie & Gal, Csilla & Feng, Tao, 2018. "A review of urban energy systems at building cluster level incorporating renewable-energy-source (RES) envelope solutions," Applied Energy, Elsevier, vol. 230(C), pages 1034-1056.

    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:eee:appene:v:268:y:2020:i:c:s0306261920305584. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.