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Cluster analysis and prediction of residential peak demand profiles using occupant activity data

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  • Satre-Meloy, Aven
  • Diakonova, Marina
  • Grünewald, Philipp

Abstract

Researching the dynamics of residential electricity consumption at finely-resolved timescales is increasingly practical with the growing availability of high-resolution data and analytical methods to characterize them. One methodological approach that is popular for exploring consumption dynamics is load profile clustering. Despite an abundance of available algorithmic techniques, clustering load profiles is challenging because clustering methods do not always capture the temporal aspects of electricity consumption and because clusters are difficult to explain without additional descriptive household data. These challenges limit the use of cluster analysis to better understand behavioral and other drivers of electricity usage patterns.

Suggested Citation

  • Satre-Meloy, Aven & Diakonova, Marina & Grünewald, Philipp, 2020. "Cluster analysis and prediction of residential peak demand profiles using occupant activity data," Applied Energy, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:appene:v:260:y:2020:i:c:s0306261919319336
    DOI: 10.1016/j.apenergy.2019.114246
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