IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i21p14163-d957980.html
   My bibliography  Save this article

Sensitivity Analysis for Decisive Design Parameters for Energy and Indoor Visual Performances of a Glazed Façade Office Building

Author

Listed:
  • Ramkishore Singh

    (School of Chemical Engineering and Physical Sciences, Lovely Professional University, Jalandhar-Delhi G.T. Road, Phagwara 144411, Panjab, India)

  • Dharam Buddhi

    (Uttaranchal Institute of Technology, Uttaranchal University, Dehradun 248007, Uttarakhand, India)

  • Samar Thapa

    (Department of Environmental Sciences, Information and Statistics, Ca’Foscari University of Venice, 30172 Venice, Italy)

  • Chander Prakash

    (School of Mechanical Engineering, Lovely Professional University, Jalandhar-Delhi G.T. Road, Phagwara 144411, Panjab, India)

  • Rajesh Singh

    (Department of Research and Development, Uttaranchal University, Dehradun 248007, Uttarakhand, India)

  • Atul Sharma

    (Department of Basic Sciences & Humanities, Rajiv Gandhi Institute of Petroleum Technology, Amethi 229304, Uttar Pradesh, India)

  • Shane Sheoran

    (Future Industries Institute, Mawson Lakes Campus, University of South Australia, Mawson Lakes, SA 5095, Australia)

  • Kuldeep Kumar Saxena

    (Department of Mechanical Engineering, GLA University, Mathura 281406, Uttar Pradesh, India)

Abstract

The large size of a glazed component allows greater access to natural light inside and a wider view of the outdoors while protecting the inside from extreme weather conditions. However, glazed components make buildings energy inefficient compared to opaque components if not designed suitably, and sometimes they create glare discomforts too. In order to protect against excessive natural light and direct sunlight and for privacy, dynamic shading devices are integrated into the glazed façade. In this study, the impact of various glazing and shading design parameters has been investigated by performing uncertainty and sensitivity analyses. The uncertainty analysis indicates that the variance coefficients for the source energy use, lighting energy use, useful daylight illuminance (UDI), and shade-deployed time fraction are in the ranges of 15.04–30.47, 39.05–45.06, 40.57–49.92, and 19.35–52%, respectively. The dispersion in the energy and indoor visual performance is evident by the large variation in the source energy consumption and UDI (500–2000), which vary in the ranges of 250–450 kWh/(m 2 -year) and 5–90%. Furthermore, a sensitivity analysis identified the window-to-wall ratio (WWR), aspect ratio (ASR), glazing type (Gt), absorptance of the wall (Aw), and shade transmittance (ST) as major influences of the parameters. Each of the identified parameters has a different proportionate impact depending on the façade orientation and performance parameters.

Suggested Citation

  • Ramkishore Singh & Dharam Buddhi & Samar Thapa & Chander Prakash & Rajesh Singh & Atul Sharma & Shane Sheoran & Kuldeep Kumar Saxena, 2022. "Sensitivity Analysis for Decisive Design Parameters for Energy and Indoor Visual Performances of a Glazed Façade Office Building," Sustainability, MDPI, vol. 14(21), pages 1-27, October.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14163-:d:957980
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/21/14163/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/21/14163/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ramos, Greici & Ghisi, Enedir, 2010. "Analysis of daylight calculated using the EnergyPlus programme," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(7), pages 1948-1958, September.
    2. Cuce, Erdem & Riffat, Saffa B., 2015. "A state-of-the-art review on innovative glazing technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 695-714.
    3. Mechri, Houcem Eddine & Capozzoli, Alfonso & Corrado, Vincenzo, 2010. "USE of the ANOVA approach for sensitive building energy design," Applied Energy, Elsevier, vol. 87(10), pages 3073-3083, October.
    4. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A three-stage optimization methodology for envelope design of passive house considering energy demand, thermal comfort and cost," Energy, Elsevier, vol. 192(C).
    5. Kannan, R., 2009. "Uncertainties in key low carbon power generation technologies - Implication for UK decarbonisation targets," Applied Energy, Elsevier, vol. 86(10), pages 1873-1886, October.
    6. Georgios E. Arnaoutakis & Dimitris A. Katsaprakakis, 2021. "Energy Performance of Buildings with Thermochromic Windows in Mediterranean Climates," Energies, MDPI, vol. 14(21), pages 1-14, October.
    7. Li, Danny H.W. & Cheung, K.L. & Wong, S.L. & Lam, Tony N.T., 2010. "An analysis of energy-efficient light fittings and lighting controls," Applied Energy, Elsevier, vol. 87(2), pages 558-567, February.
    8. Singh, Ramkishore & Lazarus, I.J. & Kishore, V.V.N., 2015. "Effect of internal woven roller shade and glazing on the energy and daylighting performances of an office building in the cold climate of Shillong," Applied Energy, Elsevier, vol. 159(C), pages 317-333.
    9. Liu, Mingzhe & Wittchen, Kim Bjarne & Heiselberg, Per Kvols, 2015. "Control strategies for intelligent glazed façade and their influence on energy and comfort performance of office buildings in Denmark," Applied Energy, Elsevier, vol. 145(C), pages 43-51.
    10. Bettonvil, Bert & Kleijnen, Jack P. C., 1997. "Searching for important factors in simulation models with many factors: Sequential bifurcation," European Journal of Operational Research, Elsevier, vol. 96(1), pages 180-194, January.
    11. Singh, Ramkishore & Lazarus, I.J. & Kishore, V.V.N., 2016. "Uncertainty and sensitivity analyses of energy and visual performances of office building with external venetian blind shading in hot-dry climate," Applied Energy, Elsevier, vol. 184(C), pages 155-170.
    12. Tomlin, Alison. S., 2006. "The use of global uncertainty methods for the evaluation of combustion mechanisms," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1219-1231.
    13. 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.
    14. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "Impact of adjustment strategies on building design process in different climates oriented by multiple performance," Applied Energy, Elsevier, vol. 266(C).
    15. Saltelli, A. & Andres, T. H. & Homma, T., 1995. "Sensitivity analysis of model output. Performance of the iterated fractional factorial design method," Computational Statistics & Data Analysis, Elsevier, vol. 20(4), pages 387-407, October.
    16. 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.
    17. Ramkishore Singh & Dharam Buddhi & Nikolai Ivanovich Vatin & Chander Prakash & Saurav Dixit & Gurbir Singh Khera & Sergei A. Solovev & Svetlana B. Ilyashenko & Vinod John, 2022. "Life Cycle Saving Analysis of an Earth-Coupled Building without and with Roof Evaporative Cooling for Energy Efficient Potato Storage Application," Energies, MDPI, vol. 15(11), pages 1-18, June.
    18. Yu, W. & Harris, T.J., 2009. "Parameter uncertainty effects on variance-based sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 596-603.
    19. Saroglou, Tanya & Theodosiou, Theodoros & Givoni, Baruch & Meir, Isaac A., 2019. "A study of different envelope scenarios towards low carbon high-rise buildings in the Mediterranean climate - can DSF be part of the solution?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    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. Singh, Ramkishore & Lazarus, I.J. & Kishore, V.V.N., 2016. "Uncertainty and sensitivity analyses of energy and visual performances of office building with external venetian blind shading in hot-dry climate," Applied Energy, Elsevier, vol. 184(C), pages 155-170.
    2. Singh, Ramkishore & Lazarus, I.J. & Kishore, V.V.N., 2015. "Effect of internal woven roller shade and glazing on the energy and daylighting performances of an office building in the cold climate of Shillong," Applied Energy, Elsevier, vol. 159(C), pages 317-333.
    3. 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.
    4. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "Impact of adjustment strategies on building design process in different climates oriented by multiple performance," Applied Energy, Elsevier, vol. 266(C).
    5. Balali, Amirhossein & Yunusa-Kaltungo, Akilu & Edwards, Rodger, 2023. "A systematic review of passive energy consumption optimisation strategy selection for buildings through multiple criteria decision-making techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    6. 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).
    7. Li, Hangxin & Wang, Shengwei & Cheung, Howard, 2018. "Sensitivity analysis of design parameters and optimal design for zero/low energy buildings in subtropical regions," Applied Energy, Elsevier, vol. 228(C), pages 1280-1291.
    8. 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.
    9. 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.
    10. Yuan, Jun & Nian, Victor & Su, Bin & Meng, Qun, 2017. "A simultaneous calibration and parameter ranking method for building energy models," Applied Energy, Elsevier, vol. 206(C), pages 657-666.
    11. Yildiz, Yusuf & Korkmaz, Koray & Göksal Özbalta, Türkan & Durmus Arsan, Zeynep, 2012. "An approach for developing sensitive design parameter guidelines to reduce the energy requirements of low-rise apartment buildings," Applied Energy, Elsevier, vol. 93(C), pages 337-347.
    12. 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.
    13. Sun, Yanyi & Liang, Runqi & Wu, Yupeng & Wilson, Robin & Rutherford, Peter, 2017. "Development of a comprehensive method to analyse glazing systems with Parallel Slat Transparent Insulation material (PS-TIM)," Applied Energy, Elsevier, vol. 205(C), pages 951-963.
    14. Kleijnen, Jack P. C. & Sargent, Robert G., 2000. "A methodology for fitting and validating metamodels in simulation," European Journal of Operational Research, Elsevier, vol. 120(1), pages 14-29, January.
    15. Tian, Wei, 2013. "A review of sensitivity analysis methods in building energy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 411-419.
    16. Mechri, Houcem Eddine & Capozzoli, Alfonso & Corrado, Vincenzo, 2010. "USE of the ANOVA approach for sensitive building energy design," Applied Energy, Elsevier, vol. 87(10), pages 3073-3083, October.
    17. 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.
    18. 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.
    19. Xue, Peng & Li, Qian & Xie, Jingchao & Zhao, Mengjing & Liu, Jiaping, 2019. "Optimization of window-to-wall ratio with sunshades in China low latitude region considering daylighting and energy saving requirements," Applied Energy, Elsevier, vol. 233, pages 62-70.
    20. Marinakis, Vangelis & Doukas, Haris & Karakosta, Charikleia & Psarras, John, 2013. "An integrated system for buildings’ energy-efficient automation: Application in the tertiary sector," Applied Energy, Elsevier, vol. 101(C), pages 6-14.

    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:14:y:2022:i:21:p:14163-:d:957980. 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.