DECC meeting on disaggregating UK smart meter data

Last week I attended an expert panel meeting for the Department of Energy and Climate Change to discuss how smart meter data could be used to better understand household energy use. The meeting was organised by Cambridge Architectural Research Ltd, and brought together a wide range of stakeholders from government, industry and academia. Among the many potential projects and barriers which were discussed, I've categorised what I believe to be the important facts:

Data availability

UK smart meters will only automatically upload 30 min data for billing purposes. However, 10 second data will also be available to Consumer Access Devices (CAD), via short range WiFi. This creates two possibilities for disaggregation from 10 second data:

1. A disaggregation system could be installed in each household as a CAD
2. A CAD could upload data to cloud storage via the home broadband connection

The second option seems the most realistic to me, given the intrinsic opt-in nature of disaggregation and the benefits of performing disaggregation in the cloud.

Data granularity

The most recent smart meter specification (SMETS v2 2013) states that only 10 second apparent power data will be available to CADs. However, it would theoretically be possible to increase the reporting rate up to 1 second data through a smart meter firmware upgrade. This rate of 1 report per second is the theoretical maximum rate of smart meters as a result of hardware limitations. Furthermore, current, voltage, harmonics, reactive power etc. will not be reported by smart meters at any sub-10 second rate.

Appliance database

Another topic discussed was the potential for a UK appliance database, similar to the Tracebase database, or a disaggregation test set, similar to the REDD data set. One potential source of data is the Powering the Nation database, which DECC/DEFRA plan to release in the near future. The study collected data from 250 homes which were monitored for either 1 month or 1 year to investigate domestic energy consumption habits.