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Discriminant effects of consumer electronics use-phase attributes on household energy prediction

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  • Raihanian Mashhadi, Ardeshir
  • Behdad, Sara

Abstract

The aim of this study is to provide a better understanding of the heterogeneities in user-product relationships and their consequences regarding the household energy predictions. Several supervised and unsupervised machine learning algorithms have been applied to a comprehensive data set of residential energy consumptions collected by the US Energy Information Association. The results of the analyses reveal that, while the heterogeneities in the use-phase of consumer electronics could skew their environmental assessment results, they do not possess the same discriminant influences on the household electricity consumption compared to certain socio-demographics or usage of home appliances. Various cross-comparisons among product features and use-phase behaviors have been made and the most important predictors of the residential electricity consumption based on the data have been introduced. Product-level and user-level discussions on the findings have also been provided.

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  • Raihanian Mashhadi, Ardeshir & Behdad, Sara, 2018. "Discriminant effects of consumer electronics use-phase attributes on household energy prediction," Energy Policy, Elsevier, vol. 118(C), pages 346-355.
    • Handle: RePEc:eee:enepol:v:118:y:2018:i:c:p:346-355
    DOI: 10.1016/j.enpol.2018.03.059
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