IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i8p4416-d536753.html
   My bibliography  Save this article

Parametric Study on Residential Passive House Building in Different Chinese Climate Zones

Author

Listed:
  • Xing Li

    (School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, China)

  • Qinli Deng

    (School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, China)

  • Zhigang Ren

    (School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, China)

  • Xiaofang Shan

    (School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, China)

  • Guang Yang

    (School of Civil Engineering, Liaoning Technical University, Fuxin 123000, China)

Abstract

With the increasing of building energy consumptions, the related issues of energy crisis and environmental pollution become more and more prominent. As an effective energy-saving technology, the passive house (PH) has been widely applied in China to reduce the building energy utilization. However, the design and application of PH vary with different climate conditions. Therefore, it is significant to conduct the parameterization of PH and propose a suitable design zoning of PH in China. In our study, a comprehensive feasibility analysis of the implementation of PH is performed, which chooses 31 representative cities covering 5 climatic regions. The sensitivity analysis firstly filters the key parameters that heavily affect energy consumption. The results indicate that the key parameters include external wall heat transfer coefficient (WU), basement ceiling heat transfer coefficient (BCU), solar heat gain coefficient (SHGC), glass G value (UG), heat recovery efficiency (HERE) and humidity recovery efficiency (HURE). Then, with the multiple regression approach, the values of key parameters are optimized. Based on the determined values of sensitive parameters, the design zoning of PH in China is finally proposed, which can guide the design of PH as well as enhance the application of PH in China.

Suggested Citation

  • Xing Li & Qinli Deng & Zhigang Ren & Xiaofang Shan & Guang Yang, 2021. "Parametric Study on Residential Passive House Building in Different Chinese Climate Zones," Sustainability, MDPI, vol. 13(8), pages 1-19, April.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:8:p:4416-:d:536753
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/8/4416/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/8/4416/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sierra-Pérez, Jorge & Rodríguez-Soria, Beatriz & Boschmonart-Rives, Jesús & Gabarrell, Xavier, 2018. "Integrated life cycle assessment and thermodynamic simulation of a public building’s envelope renovation: Conventional vs. Passivhaus proposal," Applied Energy, Elsevier, vol. 212(C), pages 1510-1521.
    2. Chen, Xi & Yang, Hongxing & Wang, Yuanhao, 2017. "Parametric study of passive design strategies for high-rise residential buildings in hot and humid climates: miscellaneous impact factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 442-460.
    3. Dalbem, Renata & Grala da Cunha, Eduardo & Vicente, Romeu & Figueiredo, Antonio & Oliveira, Rui & Silva, Antonio César Silveira Baptista da, 2019. "Optimisation of a social housing for south of Brazil: From basic performance standard to passive house concept," Energy, Elsevier, vol. 167(C), pages 1278-1296.
    4. Yomi Babatunde & Sui Pheng Low, 2015. "Construction Industry in China," Springer Books, in: Cross-Cultural Management and Quality Performance, edition 127, chapter 0, pages 31-43, Springer.
    5. Heiselberg, Per & Brohus, Henrik & Hesselholt, Allan & Rasmussen, Henrik & Seinre, Erkki & Thomas, Sara, 2009. "Application of sensitivity analysis in design of sustainable buildings," Renewable Energy, Elsevier, vol. 34(9), pages 2030-2036.
    6. Badescu, Viorel & Laaser, Nadine & Crutescu, Ruxandra, 2010. "Warm season cooling requirements for passive buildings in Southeastern Europe (Romania)," Energy, Elsevier, vol. 35(8), pages 3284-3300.
    7. Liu, Di & Zhao, Fu-Yun & Tang, Guang-Fa, 2010. "Active low-grade energy recovery potential for building energy conservation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 2736-2747, December.
    8. Wang, Yang & Du, Jiangtao & Kuckelkorn, Jens M. & Kirschbaum, Alexander & Gu, Xin & Li, Daoliang, 2019. "Identifying the feasibility of establishing a passive house school in central Europe: An energy performance and carbon emissions monitoring study in Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    9. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    10. 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.
    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. Shilei Lu & Ran Wang & Shaoqun Zheng, 2017. "Passive Optimization Design Based on Particle Swarm Optimization in Rural Buildings of the Hot Summer and Warm Winter Zone of China," Sustainability, MDPI, vol. 9(12), pages 1-30, December.
    2. Abdo Abdullah Ahmed Gassar & Choongwan Koo & Tae Wan Kim & Seung Hyun Cha, 2021. "Performance Optimization Studies on Heating, Cooling and Lighting Energy Systems of Buildings during the Design Stage: A Review," Sustainability, MDPI, vol. 13(17), pages 1-47, September.
    3. Waqas Ahmed Mahar & Griet Verbeeck & Sigrid Reiter & Shady Attia, 2020. "Sensitivity Analysis of Passive Design Strategies for Residential Buildings in Cold Semi-Arid Climates," Sustainability, MDPI, vol. 12(3), pages 1-22, February.
    4. Yıldız, Yusuf & Arsan, Zeynep Durmuş, 2011. "Identification of the building parameters that influence heating and cooling energy loads for apartment buildings in hot-humid climates," Energy, Elsevier, vol. 36(7), pages 4287-4296.
    5. Chenfei Liu & Stephen Sharples & Haniyeh Mohammadpourkarbasi, 2021. "Evaluating Insulation, Glazing and Airtightness Options for Passivhaus EnerPHit Retrofitting of a Dwelling in China’s Hot Summer–Cold Winter Climate Region," Energies, MDPI, vol. 14(21), pages 1-17, October.
    6. Fang Wang & Wen-Jia Yang & Wei-Feng Sun, 2020. "Heat Transfer and Energy Consumption of Passive House in a Severely Cold Area: Simulation Analyses," Energies, MDPI, vol. 13(3), pages 1-19, February.
    7. Zhao, Zeming & Li, Hangxin & Wang, Shengwei, 2022. "Identification of the key design parameters of Zero/low energy buildings and the impacts of climate and building morphology," Applied Energy, Elsevier, vol. 328(C).
    8. Nutkiewicz, Alex & Mastrucci, Alessio & Rao, Narasimha D. & Jain, Rishee K., 2022. "Cool roofs can mitigate cooling energy demand for informal settlement dwellers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    9. Vincenzo Varriale & Antonello Cammarano & Francesca Michelino & Mauro Caputo, 2021. "Sustainable Supply Chains with Blockchain, IoT and RFID: A Simulation on Order Management," Sustainability, MDPI, vol. 13(11), pages 1-23, June.
    10. Makam, Vaishno Devi & Millossovich, Pietro & Tsanakas, Andreas, 2021. "Sensitivity analysis with χ2-divergences," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 372-383.
    11. Plischke, Elmar & Borgonovo, Emanuele, 2019. "Copula theory and probabilistic sensitivity analysis: Is there a connection?," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1046-1059.
    12. Wen Shi & Xi Chen & Jennifer Shang, 2019. "An Efficient Morris Method-Based Framework for Simulation Factor Screening," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 745-770, October.
    13. F. Wang & G. H. Huang & Y. Fan & Y. P. Li, 2020. "Robust Subsampling ANOVA Methods for Sensitivity Analysis of Water Resource and Environmental Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(10), pages 3199-3217, August.
    14. Solène Goy & François Maréchal & Donal Finn, 2020. "Data for Urban Scale Building Energy Modelling: Assessing Impacts and Overcoming Availability Challenges," Energies, MDPI, vol. 13(16), pages 1-23, August.
    15. Daniel Harenberg & Stefano Marelli & Bruno Sudret & Viktor Winschel, 2019. "Uncertainty quantification and global sensitivity analysis for economic models," Quantitative Economics, Econometric Society, vol. 10(1), pages 1-41, January.
    16. Behzad Rismanchi & Juan Mahecha Zambrano & Bryan Saxby & Ross Tuck & Mark Stenning, 2019. "Control Strategies in Multi-Zone Air Conditioning Systems," Energies, MDPI, vol. 12(3), pages 1-14, January.
    17. 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.
    18. Liang Zhao & Wei Zhang & Wenshun Wang, 2022. "BIM-Based Multi-Objective Optimization of Low-Carbon and Energy-Saving Buildings," Sustainability, MDPI, vol. 14(20), pages 1-17, October.
    19. Tobias Fissler & Silvana M. Pesenti, 2022. "Sensitivity Measures Based on Scoring Functions," Papers 2203.00460, arXiv.org, revised Jul 2022.
    20. Gigih Rahmandhani Setyantho & Hansaem Park & Seongju Chang, 2021. "Multi-Criteria Performance Assessment for Semi-Transparent Photovoltaic Windows in Different Climate Contexts," Sustainability, MDPI, vol. 13(4), pages 1-21, February.

    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:13:y:2021:i:8:p:4416-:d:536753. 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.