Unlock the true potential of Smart Meter with big data analytics: Use Load Disaggregation techniques to deliver increased household energy savings. (037-13)

Prateek Chakravarty, Bidgely Inc, USA
Abhay Gupta, Bidgely, USA


efficiency, energy analysis, household consumption, innovative technologies, household appliances, disaggregation, bill itemization


Energy/Load Disaggregation refers to a set of statistical approaches for extracting end-use and/or appliance level data from an aggregate, or whole building, energy signal. Using the algorithms in conjunction with Smart Meters is the most cost-effective and scalable solution for getting this data. The proposed paper explains how appliance level data affords numerous benefits, including enhanced consumer engagement, increased household energy savings (upto 12%), and virtual audit tool.

The paper also addresses two energy problems. First, billions of dollars have been invested in Smart Meter infrastructure, but it has not been leveraged to the fullest by the Utilities. Second, residential consumers lack the tools to help them make informed energy saving decisions; the tools that exist are either relatively expensive (in-person audits), intrusive (plug-level sensor based), or lack specific actionable measures (energy dashboards, energy reports, historic usage, etc.). We propose to solve these issues by strategically marrying them using Disaggregation. Bidgely's consumer engagement platform - based on Load Disaggregation - helps overcome these behavioral barriers and create a new paradigm in energy efficiency that is: (i) Convenient: no appliance-level sensors; no software patch downloads; (ii) Cost-effective: web and mobile applications obviate the need for in-home displays; and (iii) Actionable: highly personalized energy saving tips that can differentiate between appliance-related and behavioral inefficiencies.

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Panels of the eceee 2013 Summer Study:

Panel 1. Foundations of future energy policy

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