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Creation of a screening analytical approach for the efficient detection of anomalous performance across large refrigeration pack estates using electrical usage data.

Author(s) : BRADY N., WALSH J.

Summary

Historical analysis of electrical energy usage data from over 350 High Temperature and Low Temperature retail refrigeration packs has shown a very high level of variability in pack electrical energy usage. This noisy big data environment makes the task of detecting anomalous pack behaviour energy wastage events, a very difficult one. This paper attempts to address this problem, by presenting a modified process characterization approach that through the meaningful subcategorisation and statistical analysis of a pack’s annualized energy usage, can give the practitioner a much better understanding of the relative contributions of baseload, within day variation, and summer seasonal variation sources, present within a pack. It goes on to show that the resultant creation of a screening analytic using only electrical usage data, when applied across a complete estate, can deliver effective pack level nomaly detection, and subsequent cost savings through the timely detection and avoidance of these significant energy wastage events.

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Pages: 8

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Details

  • Original title: Creation of a screening analytical approach for the efficient detection of anomalous performance across large refrigeration pack estates using electrical usage data.
  • Record ID : 30017508
  • Languages: English
  • Source: 4th IIR International Conference on Sustainability and the Cold Chain. Proceedings: Auckland, New Zealand, April 7-9, 2016.
  • Publication date: 2016/04/07
  • DOI: http://dx.doi.org/10.18462/iir.iccc.2016.0032

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