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Environmental and energy performance assessment of buildings using scenario modelling and fuzzy analytic network process

Author

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  • Hu, Shushan
  • Hoare, Cathal
  • Raftery, Paul
  • O’Donnell, James

Abstract

A well-recognised gap exists between measured and predicted building energy performance. Some practical assessment approaches offer the potential to reduce this gap using multiple indicators that evaluate building performance. Such approaches rely on subjective analysis of indicators’ relative weights but are typically limited to a fixed assessment structure. Scenario modelling is one method that enables flexible and multi-granular environmental and energy performance assessment by coupling building function with other pivotal aspects of building operation. However, this method weighs all performance criteria equally. The objective of this paper is to empower building managers with enhanced environmental and energy performance assessment by integrating scenario modelling with a Fuzzy Analytic Network Process. Scenario modelling decomposes environmental and energy performance assessment into a set of flexible mappings between performance indicators and multi-granular building objects while Fuzzy Analytic Network Process enables calculation of relative weights by encapsulating ambiguity in domain expertise and complex interactions among often conflicting criteria. A case study demonstrated the engineering value of this approach. The sports centre obtained an operational score of 56.9 out of 100, or level 4 of 6 (i.e. very good) in terms of operational performance classification using calculated relative weights and intermediate results for eight carefully-identified indicators. When compared to an equivalent assessment using equally weighted criteria, the proposed approach enables more informative and targeted evaluations. With these results, building managers can quickly identify inefficient areas of building operation and improve energy consumption while maintaining building function. The approach is applicable for a wide range of buildings.

Suggested Citation

  • Hu, Shushan & Hoare, Cathal & Raftery, Paul & O’Donnell, James, 2019. "Environmental and energy performance assessment of buildings using scenario modelling and fuzzy analytic network process," Applied Energy, Elsevier, vol. 255(C).
  • Handle: RePEc:eee:appene:v:255:y:2019:i:c:s0306261919314758
    DOI: 10.1016/j.apenergy.2019.113788
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    Citations

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    Cited by:

    1. Palladino, Domenico, 2023. "Energy performance gap of the Italian residential building stock: Parametric energy simulations for theoretical deviation assessment from standard conditions," Applied Energy, Elsevier, vol. 345(C).
    2. Zheming Tong & Yue Li, 2020. "Real-Time Reconstruction of Contaminant Dispersion from Sparse Sensor Observations with Gappy POD Method," Energies, MDPI, vol. 13(8), pages 1-12, April.
    3. Jonghoon Ahn, 2021. "Abatement of the Increases in Cooling Energy Use during a Period of Intense Heat by a Network-Based Adaptive Controller," Sustainability, MDPI, vol. 13(3), pages 1-17, January.
    4. Yu, Yang & Wu, Shibo & Yu, Jianxing & Xu, Ya & Song, Lin & Xu, Weipeng, 2022. "A hybrid multi-criteria decision-making framework for offshore wind turbine selection: A case study in China," Applied Energy, Elsevier, vol. 328(C).
    5. Mrówczyńska, M. & Skiba, M. & Sztubecka, M. & Bazan-Krzywoszańska, A. & Kazak, J.K. & Gajownik, P., 2021. "Scenarios as a tool supporting decisions in urban energy policy: The analysis using fuzzy logic, multi-criteria analysis and GIS tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).

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