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Identifying Home System of Practices for Energy Use with K-Means Clustering Techniques

Author

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  • Troy Malatesta

    (Sustainability Policy Institute, School of Design and Built Environment, Curtin University, Building 209, Level 1, Kent St., Bentley, WA 6102, Australia)

  • Jessica K. Breadsell

    (Sustainability Policy Institute, School of Design and Built Environment, Curtin University, Building 209, Level 1, Kent St., Bentley, WA 6102, Australia)

Abstract

Human behaviour is a major driver and determinant of household energy consumption, with routines and practices shaping daily energy profiles. These routines and practices are made up of individual lifestyles and other contextual factors that vary from home to home. Social and psychological theories aim to explain and describe how people consume resources in the home, which has resulted in the development of the home system of practice. This evaluates how occupants live and follow multiple routines which result in varying energy consumption practices. This paper develops a methodology to identify and support the concept of the home system of practice using a data analytical approach and link it to residential energy and distribution network management. This paper utilises k-means cluster analysis to identify these different home systems of practices and routines in energy use by using real-time energy consumption data from July 2019 to March 2021 from a living laboratory in Australia. The results of the analysis show the different daily energy profiles for each of the 39 households, with some homes observing large fluctuations and changes in the way they consume energy during the day. Specific homes were discussed as case studies in this paper focusing on linking the occupants’ contextual factors to their energy profiles. This variation is discussed in terms of the routines of the occupants and associated lifestyles that explain why some energy peaks occurred at different parts of the day and differed during the COVID-19 lockdown period in Australia. The paper conducts a comparison between these case studies to show how people’s lifestyles impact household energy consumption (and variation). These case studies investigated the heating and cooling practices of the occupants to demonstrate how they impact overall consumption. This variation is discussed in relation to energy management and prediction of when homes will consume energy to assist in net-zero energy developments and grid stabilisation operations.

Suggested Citation

  • Troy Malatesta & Jessica K. Breadsell, 2022. "Identifying Home System of Practices for Energy Use with K-Means Clustering Techniques," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9017-:d:869365
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    References listed on IDEAS

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    Cited by:

    1. Troy Malatesta & Qilin Li & Jessica K. Breadsell & Christine Eon, 2023. "Distinguishing Household Groupings within a Precinct Based on Energy Usage Patterns Using Machine Learning Analysis," Energies, MDPI, vol. 16(10), pages 1-25, May.
    2. Marlena Piekut & Kamil Piekut, 2022. "Changes in Patterns of Consumer Spending in European Households," Sustainability, MDPI, vol. 14(19), pages 1-25, October.
    3. Laura Höpfl & Maximilian Grimlitza & Isabella Lang & Maria Wirzberger, 2024. "Promoting sustainable behavior: addressing user clusters through targeted incentives," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.

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