Stephen Makonin has just uploaded the last of the videos to the NILM 2016 Youtube playlist, meaning that you can now easily watch individual talks from the conference. In particular, I'd recommend George Hart's keynote talk: Life after NILM, covering what it was like to do energy disaggregation in the '80s, his passion for mathematics throughout his life, his more recent shift towards art and sculpture, and finally his educational workshops.
The full set of slides and papers relating to each talk are also available via the NILM 2016 program if you'd like to catch up on everything else from the conference too. Happy watching!
My name is Oliver Parson, and I'm currently employed as a Senior Data Scientist at Bulb. I'm interested in investigating the ways in which machine learning can be used to break down household energy consumption data into individual appliances, also known as Non-intrusive Appliance Load Monitoring (NILM) or energy disaggregation.
Saturday 21 May 2016
Wednesday 18 May 2016
5 things I learned from NILM 2016
The 3rd International Workshop on Non-Intrusive Load Monitoring was held on the 14-15 May 2016 at the beautiful mountaintop campus of Simon Fraser University, Vancouver, Canada. I thoroughly enjoyed the event, and just wanted to summarise a few of my thoughts having had the flight home to digest the weekend's activities.
1. NILM is not dead
Despite the jokes that were thrown around at the European workshop last year, the NILM community is very much as alive as it has ever been. The Vancouver workshop was the first 2-day energy disaggregation conference, the best attended, and in my opinion the most stimulating in terms of presentations and discussions. That being said, NILM is still far from a solved problem. Michael Baker from SBW Consulting presented a paper which evaluated the performance of three NILM vendors, and concluded that "further development of disaggregation algorithms is needed before they are sufficiently accurate to provide customers with accurate estimate of how much they spend on most end uses."
2. Different customers want energy breakdowns for different reasons
Most academic researchers (I'm including myself here) see NILM as a tool to encourage energy efficiency, but utilities also see it as a tool for customer engagement. For example, a perfect monthly energy breakdown might be useful for both, but the disaggregation methodology might be quite different. In the case of energy efficiency the aim might be to identify the rare cases where large energy savings are possible, while in the customer engagement case it might be preferable for the disaggregation result to be more conservative when identifying such edge cases, since false positives are likely to be much more costly in terms of reputation than correct identification.
3. The assumption that disaggregation leads to significant energy efficiency has never been concretely demonstrated
Jack Kelly gave an excellent presentation of his paper which summarised the literature regarding whether disaggregated feedback leads to energy savings. One of the most shocking messages was that "the four studies which directly compared aggregate feedback against disaggregated feedback found that aggregate feedback is at least as effective as disaggregated feedback" (see full paper for details). Jack was very careful to clarify that this does not mean that disaggregated data is useless, but rather that the community desperately needs a large, well-controlled, long-duration, randomised, international study to confidently quantify energy reductions as a result of disaggregated data.
4. An academic energy disaggregation competition is badly needed
The panel discussion following the two algorithm sessions brought a lively debate around what a NILM competition might look like. Phrases like "bring it on!" were thrown around, though it also became clear that defining a scenario (e.g. sample rate, scale) which encouraged broad participation is a real challenge. Furthermore, such a competition would need a strong investment in time from an impartial organiser as well as an expensive process of data collection.
5. NILM researchers love puzzles
George Hart gave an excellent keynote talk describing what it was like to perform energy disaggregation research in the 1980s. He then went on to talk to a transfixed audience about his more recent interests in mathematical sculpture and puzzle solving. However, nothing prepared me for the silence which dropped over dinner when he handed out a series of puzzles (mostly physical blocks which had to be separated or assembled) as every researcher forgot the topic of the conference and indulged in some more traditional problem solving.
Sunday 15 May 2016
Watch NILM 2016 Day 2 Livestream
The stream for day 2 of NILM 2016 is now live:
https://www.youtube.com/watch?v=KlqkP3EVXUY
I'll try to add links to the videos of each talk once they're available.
https://www.youtube.com/watch?v=KlqkP3EVXUY
I'll try to add links to the videos of each talk once they're available.
Friday 13 May 2016
NILM 2016 Livestream
Update 08:46 14.05.2016: new youtube link
Update 09:06 14.05.2016: new youtube link
https://www.youtube.com/watch?v=3YHBC-xvm4c
This livestream will be a little experimental, so please keep an eye on NILM2016 on Twitter if we encounter any technical difficulties. For those of you who are not able to attend or watch the livestream, we are hoping to upload videos of the presentations to YouTube to be viewed at a later date.
Friday 6 May 2016
Data Management guest lecture
Yesterday I gave a guest lecture on Gopal Ramchurn's Data Management course at the University of Southampton. It was great fun exposing the first year Computer Science undergrads to technologies like Cassandra, Elastic Search and Kafka, while also contradicting a lot of what I was taught about database design on the same course 9 years ago. My favourite questions from the (surprisingly attentive) audience were:
If you're interested in a similar guest lecture on your course please don't hesitate to get in touch!
- Doesn't all that data replication negate the point of using a database in the first place?
- Why wouldn't you pay for supported packages of open source technologies?
If you're interested in a similar guest lecture on your course please don't hesitate to get in touch!
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