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Household Classification Using Smart Meter Data

Author

Listed:
  • Carroll Paula

    (Centre for Business Analytics, School of Business, University College Dublin, Belfield, Dublin 4, Dublin, Ireland)

  • Murphy Tadhg

    (Centre for Business Analytics, School of Business, University College Dublin, Belfield, Dublin 4, Dublin, Ireland)

  • Hanley Michael

    (Centre for Business Analytics, School of Business, University College Dublin, Belfield, Dublin 4, Dublin, Ireland)

  • Dempsey Daniel

    (Centre for Business Analytics, School of Business, University College Dublin, Belfield, Dublin 4, Dublin, Ireland)

  • Dunne John

    (Central Statistics Office, Skehard Road, Mahon, Cork, Ireland)

Abstract

This article describes a project conducted in conjunction with the Central Statistics Office of Ireland in response to a planned national rollout of smart electricity metering in Ireland. We investigate how this new data source might be used for the purpose of official statistics production. This study specifically looks at the question of determining household composition from electricity smart meter data using both Neural Networks (a supervised machine learning approach) and Elastic Net Logistic regression. An overview of both classification techniques is given. Results for both approaches are presented with analysis. We find that the smart meter data alone is limited in its capability to distinguish between household categories but that it does provide some useful insights.

Suggested Citation

  • Carroll Paula & Murphy Tadhg & Hanley Michael & Dempsey Daniel & Dunne John, 2018. "Household Classification Using Smart Meter Data," Journal of Official Statistics, Sciendo, vol. 34(1), pages 1-25, March.
    • Handle: RePEc:vrs:offsta:v:34:y:2018:i:1:p:1-25:n:1
    DOI: 10.1515/jos-2018-0001
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    References listed on IDEAS

    as
    1. Valeria Di Cosmo & Sean Lyons & Anne Nolan, 2014. "Estimating the Impact of Time-of-Use Pricing on Irish Electricity Demand," The Energy Journal, , vol. 35(2), pages 117-136, April.
    2. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    3. Aydinalp, Merih & Ismet Ugursal, V. & Fung, Alan S., 2002. "Modeling of the appliance, lighting, and space-cooling energy consumptions in the residential sector using neural networks," Applied Energy, Elsevier, vol. 71(2), pages 87-110, February.
    4. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
    5. McKenna, Eoghan & Richardson, Ian & Thomson, Murray, 2012. "Smart meter data: Balancing consumer privacy concerns with legitimate applications," Energy Policy, Elsevier, vol. 41(C), pages 807-814.
    Full references (including those not matched with items on IDEAS)

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