introducing smart meter disaggregation

Smart Meter Disaggregation

This blog entry is part of a series of posts introducing the topic of smart meter disaggregation.  In previous posts we've looked at the wider reasons for wanting to reduce energy consumption and we've taken a brief look at smart meters.  In the following blog post, I want to introduce the concept of smart meter disaggregation, also known as "non-intrusive load monitoring" or NILM for short1.  The main aim of smart meter disaggregation is to infer two things from a smart meter signal: 1) which appliances are active in the signal and 2) how much energy has each device consumed.  This blog post will summarise the arguments for disaggregation and we'll look at some of the main challenges.

Why bother to reduce energy consumption

This blog entry is part of a series of posts introducing the topic of smart meter disaggregation.  This specific post looks at the wider reasons for reducing energy consumption.  In other words, this post explains some of the reasons which keep me up at night when I'm not distracted by work! The reasons for reducing energy consumption typically fall into one of two categories: financial and environmental.  We'll focus mostly on the consumption of electricity but the arguments are mostly applicable to the consumption of all sorts of energy.

Financial reasons

There's been a lot of coverage in the press recently about high energy prices.  In January 2012, for example, the Citizens' Advice Bureau stated that 43% of people are worried that they can't afford their next fuel bill.  The following plot shows average annual domestic electricity prices in the UK from 1994 to 2011 (data from DECC, 2011).

Average annual domestic electricity prices in the UK.Average annual domestic electricity prices in the UK.

Electricity prices have risen from 2004 to today; but, when compared to data from the 1990s, today's prices are not quite as earth-shatteringly high as some news papers would have us believe.

What has caused the 35% price rise (in real terms) from 2003 to 2011?  I'm no expert but let's discuss two datasets which shed some light on what's going on.

What is a smart meter?

This blog entry is part of a series of posts introducing the topic of smart meter disaggregation.

Your existing electricity meter probably looks something like this:

Attribution: Kristoferb at en.wikipedia

(image taken by Kristoferb at en.wikipedia)

By 2019, the UK government have mandated every electricity meter in homes and businesses will be replaced by a "smart meter" (that's a grand total of 53 million meters).  A smart meter is simply a digital meter with some basic communications functions.  It will be paid for and installed by the utility company.  It will talk to the utility company over a GPRS data connection; and it will also be able to talk to the "home area network" to provide data to in-house energy displays.

The draft spec for smart meters in the UK was published by the Smart Metering Design Group in August 2011.  The specification states that the meter must be able to supply meter readings to the home area network at a rate of one reading every five seconds.  The meter will measure voltage, real power and reactive power (in both directions).  Some utility companies have already started to install smart meters; British Gas plan to have 2 million smart meters installed by the end of 2012 (Centrica, 2010). 

If you can't wait for a smart meter to be installed then you could buy and install a "home energy monitor". These are available for around £40; although some utility companies give them away for free.  Home energy monitors are user-installable.  I used a Current Cost home energy monitor for my MSc project on disaggregation.  It recorded a sample of apparent power once every six seconds.

This is a reading produced by my Current Cost home energy monitor:

meterPlotmeterPlot

The value of sample at time t is the sum of the power being consumed by every appliance active at time t​.

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