PhD

April 2017 update of UK-DALE

I've just updated my UK Domestic Appliance-Level Electricity (UK-DALE) dataset. House 1 now has 4.3 years of data! https://www.doc.ic.ac.uk/~dk3810/data/

Free, 2nd hand, data collection hardware

I'm giving away some of the data collection hardware I used for UK-DALE. Details here.

PhD thesis is all done!

My PhD examiners were happy with the minor corrections I made to my PhD thesis! So I'm all done with my PhD thesis :)

Not currently working on the energy disaggregation competition

Towards the end of last year, I was lucky enough to have a short postdoc paid for by EDF Energy. The main focus of the postdoc was on looking at ways to design a competition to compare the performance of different disaggregation algorithms. This postdoc finished in January 2017 so I am not currently working on the disaggregation competition (although I strongly believe that finding a good way to compare NILM algorithms is one of the most important unsolved problems in NILM).

Very briefly: the main challenge in designing a NILM competition is getting enough clean, private testing data. It turns out that the performance of NILM algorithms can be quite inconsistent across houses: an algorithm might work well on some houses; but on other houses that same algorithm might work badly. Also, one of the promising uses of NILM is to identify "extreme" energy behaviour (such as leaving your electric oven on constantly just in case you fancy doing some baking). Identifying "extreme" behaviour is useful because users can save large sums of money with a single, simple change in behaviour. But - by definition - "extreme" behaviour is rare. Hence we need a large testing dataset (maybe 100 houses) to be confident that we're accurately capturing the performance of each algorithm; and that each algorithm can recognise "extreme" energy behaviour. Recording this quantity of real data would be very expensive and time consuming. Hence we could consider building a high-quality simulator to generate realistic data. But this raises a whole host of additional challenges!

PhD thesis submitted!

Last night I submitted my PhD thesis on "Disaggregation of Domestic Smart Meter Energy Data"! Hurray!

Current Cost and EDF EcoManager RF protocol docs are back online :)

Back in 2012, a few of us hacker folks chipped away at reverse-engineering the radio protocols for Current Cost and EDF EcoManager electricity meters. We kept our notes on a github wiki. Then Current Cost asked us to take those docs down. But, today, Current Cost very kindly allowed us to put the docs back online! Specifically, these two docs are now back online:

Have fun :)

3rd International Workshop on NILM -- SAVE THE DATE!

Dear NILM researchers,

The 3rd International Workshop on Non-Intrusive Load Monitoring (NILM) will be held in Vancouver, Canada from May 14 to 15, 2016. The venue for the workshop is still under consideration. Last workshop was held June/2014 at the University of Texas, Austin, in Austin, TX.

Draft Neural NILM paper

My draft Neural NILM paper is available here, if you're interested (this is currently submitted to a conference)

Comments are very welcome!

About to go on holiday...

update the paper is now or arXiv : "Neural NILM: Deep neural networks applied to energy disaggregation" is now on arXiv

update 2: the code isn't available yet but I definitely plan to release it.

Neural NILM: Deep Neural Networks Applied to Energy Disaggregation

At the NILM Workshop last Wednesday, I presented a poster on "Neural NILM: Deep Neural Networks Applied to Energy Disaggregation". It was a lot of fun discussing it with the participants! There's still a lot of work to do but this approach does work reasonably well right now. More details will come later...

Announcing the 2015 European NILM workshop

The Second European Workshop on Non-intrusive Load Monitoring will be held on 8th July 2015 at Imperial College London. More details on Oli's blog.

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