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An empirically grounded model for simulating normative energy use feedback interventions

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  • Anderson, Kyle
  • Lee, SangHyun

Abstract

Researchers have begun developing simulation models as a cost-effective and expeditious means to explore and enhance our understanding of energy use behavior interventions. These models have provided unique insights into potential energy savings as a result of improved occupant behavior, but have not yet reached the capability to be used for predictive modeling purposes. Therefore, this paper attempts to build on previous modeling efforts and develops an empirically and conceptually grounded occupant behavior model for simulating normative feedback interventions based on literature from the social science and field data. This model is then used to conduct “what if” analyses testing three novel normative feedback intervention strategies and the effect of social network structure on intervention outcomes. The most successful and immediately applicable strategy consists of sending normative feedback only to individuals who use more energy than the group norm. This strategy resulted in a mean energy use reduction of 1.4kW h per week per occupant, 2.2%, relative to traditional individual and normative feedback strategies used today. Lastly, it was found that the social network structure in which the interventions took place affected the absolute outcomes (i.e., net change) of the simulations but not the relative outcomes (i.e., strategy ranking).

Suggested Citation

  • Anderson, Kyle & Lee, SangHyun, 2016. "An empirically grounded model for simulating normative energy use feedback interventions," Applied Energy, Elsevier, vol. 173(C), pages 272-282.
    • Handle: RePEc:eee:appene:v:173:y:2016:i:c:p:272-282
    DOI: 10.1016/j.apenergy.2016.04.063
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    5. Zhou, Yang & Shi, Zhixiong & Shi, Zhengyu & Gao, Qing & Wu, Libo, 2019. "Disaggregating power consumption of commercial buildings based on the finite mixture model," Applied Energy, Elsevier, vol. 243(C), pages 35-46.
    6. Khosrowpour, Ardalan & Jain, Rishee K. & Taylor, John E. & Peschiera, Gabriel & Chen, Jiayu & Gulbinas, Rimas, 2018. "A review of occupant energy feedback research: Opportunities for methodological fusion at the intersection of experimentation, analytics, surveys and simulation," Applied Energy, Elsevier, vol. 218(C), pages 304-316.
    7. Li, Rui & Fang, Debin & Xu, Jiajun, 2024. "Does China's carbon inclusion policy promote household carbon emissions reduction? Theoretical mechanisms and empirical evidence," Energy Economics, Elsevier, vol. 132(C).
    8. Sebastian Hoffmann & Fabian Adelt & Johannes Weyer, 2020. "Modelling End-User Behavior and Behavioral Change in Smart Grids. An Application of the Model of Frame Selection," Energies, MDPI, vol. 13(24), pages 1-26, December.
    9. Lee, Junghun & Kim, Jeonggook & Song, Doosam & Kim, Jonghun & Jang, Cheolyong, 2017. "Impact of external insulation and internal thermal density upon energy consumption of buildings in a temperate climate with four distinct seasons," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1081-1088.
    10. Shen, Meng & Li, Xiang & Lu, Yujie & Cui, Qingbin & Wei, Yi-Ming, 2021. "Personality-based normative feedback intervention for energy conservation," Energy Economics, Elsevier, vol. 104(C).
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