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Influence of interior layouts on occupant energy-saving behaviour in buildings: An integrated approach using Agent-Based Modelling, System Dynamics and Building Information Modelling

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  • Uddin, Mohammad Nyme
  • Chi, Hung-Lin
  • Wei, His-Hsien
  • Lee, Minhyun
  • Ni, Meng

Abstract

Interior layouts of a building may influence the presence and movement of occupants, which can lead them to participate in a certain activity, energy-saving behaviour for instance, which occurs at a particular location within an indoor space. Moreover, rearranging this interior layout can help understanding how and why occupants use more energy and encourage their energy-saving behaviours through occupancy-based interventions. However, only a handful of studies have attempted to evaluate the effects of interior layout on the energy-saving behaviour of occupants. In light of this, this study offers a comprehensive modelling framework for investigating the influence of interior layouts on occupants' energy-saving behaviours by integrating Agent-Based Modelling (ABM), Systems Dynamics (SD), and Building Information Modelling (BIM). The occupant behaviour within this hybrid model is built based upon the theory of reasoned action. Moreover, while most of the ABM studies related to occupant behaviour are based on synthetic data, this study used real energy data collected from customized sensors to validate the proposed model. As a result, it has been shown that adjustment of interior layout (i.e., occupant intervention) can improve building energy performance by 14.9%. In terms of model validation, the proposed hybrid model has exhibited an acceptable level of accuracy with an average CV(RMSE) of 10.5%, MBE of 1.5%, and R2 of 0.77. This study differs from other existing studies in that it adopts an interior layout-based human behavioural investigation considering stochastic attitudes and subjective norms of occupants and provides a robust validation through empirical-based intervention.

Suggested Citation

  • Uddin, Mohammad Nyme & Chi, Hung-Lin & Wei, His-Hsien & Lee, Minhyun & Ni, Meng, 2022. "Influence of interior layouts on occupant energy-saving behaviour in buildings: An integrated approach using Agent-Based Modelling, System Dynamics and Building Information Modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
  • Handle: RePEc:eee:rensus:v:161:y:2022:i:c:s1364032122002921
    DOI: 10.1016/j.rser.2022.112382
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    as
    1. Abanda, F.H. & Byers, L., 2016. "An investigation of the impact of building orientation on energy consumption in a domestic building using emerging BIM (Building Information Modelling)," Energy, Elsevier, vol. 97(C), pages 517-527.
    2. Jia, Mengda & Srinivasan, Ravi S. & Raheem, Adeeba A., 2017. "From occupancy to occupant behavior: An analytical survey of data acquisition technologies, modeling methodologies and simulation coupling mechanisms for building energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 525-540.
    3. Delzendeh, Elham & Wu, Song & Lee, Angela & Zhou, Ying, 2017. "The impact of occupants’ behaviours on building energy analysis: A research review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1061-1071.
    4. Hwang Yi, 2020. "Visualized Co-Simulation of Adaptive Human Behavior and Dynamic Building Performance: An Agent-Based Model (ABM) and Artificial Intelligence (AI) Approach for Smart Architectural Design," Sustainability, MDPI, vol. 12(16), pages 1-18, August.
    5. Klessmann, Corinna & Held, Anne & Rathmann, Max & Ragwitz, Mario, 2011. "Status and perspectives of renewable energy policy and deployment in the European Union—What is needed to reach the 2020 targets?," Energy Policy, Elsevier, vol. 39(12), pages 7637-7657.
    6. Sebastian Strunz, Erik Gawel, and Paul Lehmann, 2015. "Towards a general Europeanization of EU Member States energy policies?," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 2).
    7. Kangas, Hanna-Liisa & Lazarevic, David & Kivimaa, Paula, 2018. "Technical skills, disinterest and non-functional regulation: Barriers to building energy efficiency in Finland viewed by energy service companies," Energy Policy, Elsevier, vol. 114(C), pages 63-76.
    8. Tiantian Du & Sabine Jansen & Michela Turrin & Andy van den Dobbelsteen, 2020. "Effects of Architectural Space Layouts on Energy Performance: A Review," Sustainability, MDPI, vol. 12(5), pages 1-23, February.
    9. Shi-Yi Song & Hong Leng, 2020. "Modeling the Household Electricity Usage Behavior and Energy-Saving Management in Severely Cold Regions," Energies, MDPI, vol. 13(21), pages 1-22, October.
    10. Qadeer Ali & Muhammad Jamaluddin Thaheem & Fahim Ullah & Samad M. E. Sepasgozar, 2020. "The Performance Gap in Energy-Efficient Office Buildings: How the Occupants Can Help?," Energies, MDPI, vol. 13(6), pages 1-27, March.
    11. Germán Ramos Ruiz & Carlos Fernández Bandera, 2017. "Validation of Calibrated Energy Models: Common Errors," Energies, MDPI, vol. 10(10), pages 1-19, October.
    12. Wang, Huan & Chen, Wenying & Shi, Jingcheng, 2018. "Low carbon transition of global building sector under 2- and 1.5-degree targets," Applied Energy, Elsevier, vol. 222(C), pages 148-157.
    13. Anjos, Miguel F. & Vieira, Manuel V.C., 2017. "Mathematical optimization approaches for facility layout problems: The state-of-the-art and future research directions," European Journal of Operational Research, Elsevier, vol. 261(1), pages 1-16.
    14. Soares, N. & Bastos, J. & Pereira, L. Dias & Soares, A. & Amaral, A.R. & Asadi, E. & Rodrigues, E. & Lamas, F.B. & Monteiro, H. & Lopes, M.A.R. & Gaspar, A.R., 2017. "A review on current advances in the energy and environmental performance of buildings towards a more sustainable built environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 845-860.
    15. Gaetani, Isabella & Hoes, Pieter-Jan & Hensen, Jan L.M., 2018. "Estimating the influence of occupant behavior on building heating and cooling energy in one simulation run," Applied Energy, Elsevier, vol. 223(C), pages 159-171.
    16. Chen, Yixing & Hong, Tianzhen & Piette, Mary Ann, 2017. "Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis," Applied Energy, Elsevier, vol. 205(C), pages 323-335.
    17. Wang, Chen & Engels, Anita & Wang, Zhaohua, 2018. "Overview of research on China's transition to low-carbon development: The role of cities, technologies, industries and the energy system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1350-1364.
    18. Zhang, Kai & Zhao, Dongliang & Yin, Xiaobo & Yang, Ronggui & Tan, Gang, 2018. "Energy saving and economic analysis of a new hybrid radiative cooling system for single-family houses in the USA," Applied Energy, Elsevier, vol. 224(C), pages 371-381.
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    2. Xu, Xiaoxiao & Yu, Hao & Sun, Qiuwen & Tam, Vivian W.Y., 2023. "A critical review of occupant energy consumption behavior in buildings: How we got here, where we are, and where we are headed," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    3. Yan, Biao & Yang, Wansheng & He, Fuquan & Zeng, Wenhao, 2023. "Occupant behavior impact in buildings and the artificial intelligence-based techniques and data-driven approach solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    4. Cheng, Xiu & Li, Wenbo & Yang, Jiameng & Zhang, Linling, 2023. "How convenience and informational tools shape waste separation behavior: A social network approach," Resources Policy, Elsevier, vol. 86(PB).

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