IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v282y2021ipas0306261920314562.html
   My bibliography  Save this article

Multi-objective optimisations of envelope components for a prefabricated house in six climate zones

Author

Listed:
  • Naji, Sareh
  • Aye, Lu
  • Noguchi, Masa

Abstract

The ever-increasing attention towards implementation of environmentally sustainable buildings necessitates the predictions of energy consumption and indoor environmental quality (IEQ) during early design stages. Prefabrication of buildings changes the construction process and components which affects building performance. Better understanding the effects of envelope components on energy performance and IEQ will inform design decisions leading to the creation of more sustainable buildings. In this article multi-objective optimisations of building envelope were carried out by coupling TRNSYS (Transient System Simulation Tool) and jEPlus + EA (EnergyPlus simulation manager for parametrics + Evolutionary Algorithms). The objective functions to be minimised were thermal discomfort hours (TDH), daylight unsatisfied hours (DUH) and life cycle costs (LCC) while maintaining acceptable sound transmission levels and indoor air quality. The decision variables were envelope components of a prefabricated house. Applications for six different climate zones corresponding to eight locations in Australia were investigated. The optimal solution sets were unique for each climate zone. The optimal solutions achieved 27–31% savings in LCC compared to the baseline. The reductions for TDH varied from 6% to 55% among the locations. As a result of trade-offs, the selected compromised solutions in each climate could achieve better reductions for either TDH, LCC or both.

Suggested Citation

  • Naji, Sareh & Aye, Lu & Noguchi, Masa, 2021. "Multi-objective optimisations of envelope components for a prefabricated house in six climate zones," Applied Energy, Elsevier, vol. 282(PA).
    • Handle: RePEc:eee:appene:v:282:y:2021:i:pa:s0306261920314562
    DOI: 10.1016/j.apenergy.2020.116012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261920314562
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2020.116012?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. Rabani, Mehrdad & Bayera Madessa, Habtamu & Mohseni, Omid & Nord, Natasa, 2020. "Minimizing delivered energy and life cycle cost using Graphical script: An office building retrofitting case," Applied Energy, Elsevier, vol. 268(C).
    2. Harmathy, Norbert & Magyar, Zoltán & Folić, Radomir, 2016. "Multi-criterion optimization of building envelope in the function of indoor illumination quality towards overall energy performance improvement," Energy, Elsevier, vol. 114(C), pages 302-317.
    3. Best, Robert E. & Rezazadeh Kalehbasti, P. & Lepech, Michael D., 2020. "A novel approach to district heating and cooling network design based on life cycle cost optimization," Energy, Elsevier, vol. 194(C).
    4. 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.
    5. Mourshed, Monjur, 2016. "Climatic parameters for building energy applications: A temporal-geospatial assessment of temperature indicators," Renewable Energy, Elsevier, vol. 94(C), pages 55-71.
    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. Ascione, Fabrizio & Bianco, Nicola & Maria Mauro, Gerardo & Napolitano, Davide Ferdinando, 2019. "Building envelope design: Multi-objective optimization to minimize energy consumption, global cost and thermal discomfort. Application to different Italian climatic zones," Energy, Elsevier, vol. 174(C), pages 359-374.
    8. Fred Edmond Boafo & Jin-Hee Kim & Jun-Tae Kim, 2016. "Performance of Modular Prefabricated Architecture: Case Study-Based Review and Future Pathways," Sustainability, MDPI, vol. 8(6), pages 1-16, June.
    9. Naji, Sareh & Keivani, Afram & Shamshirband, Shahaboddin & Alengaram, U. Johnson & Jumaat, Mohd Zamin & Mansor, Zulkefli & Lee, Malrey, 2016. "Estimating building energy consumption using extreme learning machine method," Energy, Elsevier, vol. 97(C), pages 506-516.
    10. Chen, Xi & Yang, Hongxing & Sun, Ke, 2016. "A holistic passive design approach to optimize indoor environmental quality of a typical residential building in Hong Kong," Energy, Elsevier, vol. 113(C), pages 267-281.
    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. Mattia Manni & Alessandro Nocente & Martin Bellmann & Gabriele Lobaccaro, 2023. "Multi-Stage Validation of a Solar Irradiance Model Chain: An Application at High Latitudes," Sustainability, MDPI, vol. 15(4), pages 1-18, February.
    2. Shi, Hao & Xu, Huining & Tan, Yiqiu & Li, Qiang & Yi, Wei, 2022. "Multi-objective optimization of operation strategy in snow melting system for airfield runway using genetic algorithm: A case study in Beijing Daxing International Airport," Renewable Energy, Elsevier, vol. 201(P2), pages 100-116.
    3. Tarek M. Kamel & Amany Khalil & Mohammed M. Lakousha & Randa Khalil & Mohamed Hamdy, 2024. "Optimizing the View Percentage, Daylight Autonomy, Sunlight Exposure, and Energy Use: Data-Driven-Based Approach for Maximum Space Utilization in Residential Building Stock in Hot Climates," Energies, MDPI, vol. 17(3), pages 1-27, January.
    4. Rudai Shan & Lars Junghans, 2023. "Multi-Objective Optimization for High-Performance Building Facade Design: A Systematic Literature Review," Sustainability, MDPI, vol. 15(21), pages 1-33, November.
    5. Naji, Sareh & Aye, Lu & Noguchi, Masa, 2021. "Sensitivity analysis on energy performance, thermal and visual discomfort of a prefabricated house in six climate zones in Australia," Applied Energy, Elsevier, vol. 298(C).
    6. Elaouzy, Youssef & El Fadar, Abdellah, 2023. "Sustainability of building-integrated bioclimatic design strategies depending on energy affordability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(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. Ali Sadollah & Mohammad Nasir & Zong Woo Geem, 2020. "Sustainability and Optimization: From Conceptual Fundamentals to Applications," Sustainability, MDPI, vol. 12(5), pages 1-34, March.
    2. Saurbayeva, Assemgul & Memon, Shazim Ali & Kim, Jong, 2023. "Integrated multi-stage sensitivity analysis and multi-objective optimization approach for PCM integrated residential buildings in different climate zones," Energy, Elsevier, vol. 278(PB).
    3. Harkouss, Fatima & Fardoun, Farouk & Biwole, Pascal Henry, 2018. "Passive design optimization of low energy buildings in different climates," Energy, Elsevier, vol. 165(PA), pages 591-613.
    4. Ascione, Fabrizio & Bianco, Nicola & De Stasio, Claudio & Mauro, Gerardo Maria & Vanoli, Giuseppe Peter, 2017. "Artificial neural networks to predict energy performance and retrofit scenarios for any member of a building category: A novel approach," Energy, Elsevier, vol. 118(C), pages 999-1017.
    5. Wu, Xianguo & Feng, Zongbao & Chen, Hongyu & Qin, Yawei & Zheng, Shiyi & Wang, Lei & Liu, Yang & Skibniewski, Miroslaw J., 2022. "Intelligent optimization framework of near zero energy consumption building performance based on a hybrid machine learning algorithm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(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. 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).
    8. Chen, Xi & Yang, Hongxing & Sun, Ke, 2017. "Developing a meta-model for sensitivity analyses and prediction of building performance for passively designed high-rise residential buildings," Applied Energy, Elsevier, vol. 194(C), pages 422-439.
    9. Naji, Sareh & Aye, Lu & Noguchi, Masa, 2021. "Sensitivity analysis on energy performance, thermal and visual discomfort of a prefabricated house in six climate zones in Australia," Applied Energy, Elsevier, vol. 298(C).
    10. Frida Bazzocchi & Cecilia Ciacci & Vincenzo Di Naso, 2021. "Evaluation of Environmental and Economic Sustainability for the Building Envelope of Low-Carbon Schools," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    11. Huang, Junchao & Chen, Xi & Yang, Hongxing & Zhang, Weilong, 2018. "Numerical investigation of a novel vacuum photovoltaic curtain wall and integrated optimization of photovoltaic envelope systems," Applied Energy, Elsevier, vol. 229(C), pages 1048-1060.
    12. Chen, Xi & Yang, Hongxing, 2017. "A multi-stage optimization of passively designed high-rise residential buildings in multiple building operation scenarios," Applied Energy, Elsevier, vol. 206(C), pages 541-557.
    13. 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.
    14. Amal A. Al-Shargabi & Abdulbasit Almhafdy & Dina M. Ibrahim & Manal Alghieth & Francisco Chiclana, 2021. "Tuning Deep Neural Networks for Predicting Energy Consumption in Arid Climate Based on Buildings Characteristics," Sustainability, MDPI, vol. 13(22), pages 1-20, November.
    15. Liu, Che & Sun, Bo & Zhang, Chenghui & Li, Fan, 2020. "A hybrid prediction model for residential electricity consumption using holt-winters and extreme learning machine," Applied Energy, Elsevier, vol. 275(C).
    16. Xiang Liu & Wanjiang Wang & Zixuan Wang & Junkang Song & Ke Li, 2023. "Simulation Study on Outdoor Wind Environment of Residential Complexes in Hot-Summer and Cold-Winter Climate Zones Based on Entropy-Based TOPSIS Method," Sustainability, MDPI, vol. 15(16), pages 1-28, August.
    17. Mao, Ning & Pan, Dongmei & Li, Zhao & Xu, Yingjie & Song, Mengjie & Deng, Shiming, 2017. "A numerical study on influences of building envelope heat gain on operating performances of a bed-based task/ambient air conditioning (TAC) system in energy saving and thermal comfort," Applied Energy, Elsevier, vol. 192(C), pages 213-221.
    18. Hosang Hyun & Hyunsoo Kim & Hyun-Soo Lee & Moonseo Park & Jeonghoon Lee, 2020. "Integrated Design Process for Modular Construction Projects to Reduce Rework," Sustainability, MDPI, vol. 12(2), pages 1-19, January.
    19. 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.
    20. Ana Mafalda Matos & João M. P. Q. Delgado & Ana Sofia Guimarães, 2022. "Energy-Efficiency Passive Strategies for Mediterranean Climate: An Overview," Energies, MDPI, vol. 15(7), pages 1-20, April.

    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:282:y:2021:i:pa:s0306261920314562. 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.