A cloud-based consumer-centric architecture for energy data analytics

  • Authors:

  • Rayman Preet Singh;S. Keshav;Tim Brecht

  • Affiliations:

  • University of Waterloo, Waterloo, ON, Canada;University of Waterloo, Waterloo, ON, Canada;University of Waterloo, Waterloo, ON, Canada

  • Venue:
  • Proceedings of the fourth international conference on Future energy systems
  • Year:
  • 2013

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Abstract

With the advent of utility-owned smart meters and smart appliances, the amount of data generated and collected about consumer energy consumption has rapidly increased. Energy usage data is of immense practical use for consumers for audits, analytics, and automation. Currently, utility companies collect, use, share, and discard usage data at their discretion, with no input from consumers. In many cases, consumers do not even have access to their own data. Moreover, consumers do not have the ability to extract actionable intelligence from their usage data using analytic algorithms of their own choosing: at best they are limited to the analysis chosen for them by their utility. We address these issues by designing and implementing a cloud-based architecture that provides consumers with fast access and fine-grained control over their usage data, as well as the ability to analyse this data with algorithms of their choosing, including third party applications that analyse that data in a privacy preserving fashion. We explain why a cloud-based solution is required, describe our prototype implementation, and report on some example applications we have implemented that demonstrate personal data ownership, control, and analytics.