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Unveiling the Dynamics of Residential Energy Consumption: A Quantitative Study of Demographic and Personality Influences in Singapore Using Machine Learning Approaches

Lookup NU author(s): Dr Anurag Sharma

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2024 by the authors. In the pursuit of instigating a progressive transition towards a more sustainable future, policy officials all over the world are fervently advocating the use of energy conservation techniques targeted at residential customers. Keeping this in mind, a quantitative study was conducted in this work using the data from Singapore, which aims to investigate the relationships between a resident’s pattern of energy utilisation and numerous demographic parameters as well as personality attributes. Moreover, the study was conducted with existing machine learning and data analytics approaches, including k-prototype unsupervised learning and statistical hypothesis tests. The obtained results denote a persuasive correlation between the consumption behaviour of the consumer for different appliances and factors such as income, energy knowledge, usage frequency, personality, etc. For instance, there is a higher probability of a consumer acting frugally and sparingly if they believe their energy consumption is insignificant. These findings can help policymakers identify the appropriate target populations for raising energy awareness in Singapore.


Publication metadata

Author(s): Chew J, Sharma A, Kumar DS, Zhang W, Anant N, Dong J

Publication type: Article

Publication status: Published

Journal: Sustainability

Year: 2024

Volume: 16

Issue: 14

Online publication date: 10/07/2024

Acceptance date: 01/07/2024

Date deposited: 12/08/2024

ISSN (electronic): 2071-1050

Publisher: MDPI

URL: https://doi.org/10.3390/su16145881

DOI: 10.3390/su16145881

Data Access Statement: Data is not publicly available, though the data may be made available on request from the corresponding author.


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