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.

1 comment:

  1. I think NILM should attach to industrial domain where saving energy or tracking the unnormal working in industrial machines with the support of NILM will are very very interesting.