Friday 25 May 2012

NIALM in industry

Since the Pittsburgh workshop I've learnt a lot about industry's perspective of NIALM. Academic work is often criticised for solving simplified problems, and I believe it's important to understand what our friends in industry believe to be the real-world problems. This post is meant to list the companies I'm aware of that are working in this field, and summarise their approach to energy disaggregation. As always, please leave a comment or drop me an email if you know of any inaccuracies or omissions.

AlertMe (now part of Centrica Hive), Cambridge, UK

AlertMe is a company focusing on household monitoring for energy reduction and security purposes. Their Analytics package is able to use second by second measurements to disaggregate the whole-home data to identify individual appliances, analyse their performance and provide personalised feedback and recommendations.

Bidgely (formerly MyEnerSave), CA, USA

Bidgely is a meter-agnostic cloud-based electricity disaggregation company focused generating actionable appliance-level feedback from second to minute level aggregate power data. Their web interface allows users to either connect third party meters (TED, WattVision etc.). In addition, customers are able to upload data collected from smart meters to Bidgely's platform for analysis.

EEme (now part of Uplight), NC, USA

EEme are a spin-out from Carnegie Mellon University, who apply energy disaggregation to 15-minute smart meter data to provide demand side management analytics. EEme released a report describing the accuracy of disaggregation product as calculated by Pecan Street’s 3rd party evaluation tool. The evaluation tool which provided EEme with 15-minute aggregate smart meter data and weather data from hundreds of homes, and required EEme to return monthly totals for four of the largest energy consuming appliances.

Fludia, Paris, France

Fludia is a French company specialising in energy management, and aim to provide their customers with energy efficiency technology. They have developed a device to retrofit non-smart meters, called Fludiameter, such that 1 minute resolution energy data can be collected without installing a whole new meter. Fludia also provide a tool to break down electricity consumption into its end uses, called Beluso, which makes use of household aggregate data and also information entered from a household survey.

Homepulse (formerly WattGo), Aix-en-Provence, France

Homepulse is a French company whose technology disaggregates electricity and gas consumption in-near real-time into categories, such as standby, cold appliances, hot water, home appliances and heating. The company also released a whitepaper detailing the aggregate monitoring of thousands of households along with the collection of a range of metadata, which forms the training data for their algorithms.

Informetis, Japan

Informetis are a spin out of Sony R&D, whose technology offers both historic appliance-specific energy breakdowns and real-time disaggregation. Furthermore, their product aims to detect abnormal power consumption of individual appliances. The product currently works with either a custom plug-in sensor, or a smart meter running custom firmware. In July 2015, Informetis expanded the company by opening a second office in Europe, operating out of Cambridge in the UK.


LoadIQ are a company focusing on electricity disaggregation within commercial and industrial domains. The company offers solutions aimed at reducing business' costs as a result of inefficient electricity consumption.

Navetas, Oxford, UK

Navetas is a spin-out company from the University of Oxford who have partnered with a meter manufacturer to focus upon disaggregating appliance energy consumption given the high-resolution aggregate data.

Neurio (from Energy Aware), Vancouver, BC, Canada

Neurio recently raised Kickstarter funding to develop their electricity disaggregation technology, which consists of a hardware sensor featuring two CT clamps, capable of reporting voltage, current, real power and power factor at 1 second intervals. The company also offer a cloud-based service which breakdown your household electricity usage into individual appliances.

Onzo, London, UK

Onzo is a London-based energy analytics company, who recently sold their energy display business to SSE Labs, allowing them to concentrate solely on data analytics. Their website boasts a proprietary energy knowledgebase containing tens of thousands of household's energy data at a range of resolutions, as well as thousands of energy signatures from individual appliances from a range of manufacturers. Furthermore, their disaggregation algorithms not only infer the energy consumption of appliances, but also determine household occupancy schedules and appliance diagnostic information.

PlotWatt, NC, USA

PlotWatt are a meter-agnostic cloud-based electricity disaggregation company focused on disaggregating second to minute level aggregate power data. Their web interface allows users to either connect third party meters (TED, WattVision etc.) or upload files of their consumption data.

Powersavvy, Castlebar, Ireland

Powersavvy is a company looking to highlight energy savings to both households and businesses. They offer their own meter, which can be installed for either 6 days or indefinitely, and is used to provide disaggregated advice based on the data they collect. Their website quotes that savings of 30% can be easily achieved using their products.

Sense, MA, USA

Sense are a consumer-oriented startup based in Cambridge, Massachusetts, doing sub-second level monitoring of current and voltage through 2 current sensors attached to the service mains in the electric panel. On 01.09.16 Sense received $14M in series A funding to grow the business.

SmartB (from Yetu), Berlin, Germany

SmartB are the energy disaggregation arm of Yetu, who offer a smart home platform which connects household appliances, micro-generators, micro-storage and smart meters via a home gateway. Their home energy management system allows household occupants to view their live or historic household aggregate power demand. Furthermore, they offer a software-based disaggregated breakdown of this 1 second smart meter data. The system also notifies the household occupants if an appliance has consumed significantly more energy than the national average, and offers personalised suggestions for saving energy.

Verdigris, CA, USA

Verdigris is a silicon valley start-up offering Building.AI, a platform for building intelligence. The product consists of a number of circuit panel CT clamps and a disaggregation software package. As a result, they're able to provide appliance-level energy breakdowns, real-time fault detection and persistent building commissioning.

Verlitics, (formerly Emme), OR, USA

Verlitics is a cloud-based company which use bespoke high sample rate meters to provide electricity disaggregation results to domestic customers. They offer web and smartphone interfaces to their home-owners or businesses allowing them to view their disaggregation electricity usage.

Watt-IS, Torres Vedras, Portugal

Watt-IS are an analytics company which aim to disaggregate smart meter data collected by utilities to produce appliance-level energy consumption data and actionable feedback which could be provided to customers. Such feedback includes the potential savings from replacing a refrigerator, reducing the whole-home standby power, and also shifting demand to off-peak times.

Wattics, (formerly Veutility), Dublin, Ireland

Wattics is a software company, partnered with EpiSensor, who have previously provided disaggregated appliance level data from a single point of measurement. Their on-line dashboard identified unneeded or deteriorating appliances and suggested energy saving measures. However, Wattics not longer offer disaggregation functionality.

Wattseeker (from Qualisteo), Nice, France

Wattseeker offer a datalogger, which includes a number of current clamps and options to upload data via 3G, Ethernet or Wi-Fi. These current clamps must sample the current and voltage at a kHz rate since real and reactive power are reported, along with harmonics etc. However, the installation does require a short shutdown of the building's power. Their disaggregation system, LYNX, then disaggregates the electricity consumption to provide actionable energy saving suggestions. Their website indicates that each current clamp can disaggregate up to 12 appliances, with an accuracy of +/- 2%.

Watty, Stockholm, Sweden

Watty is a startup company closely linked with the KTH Royal Institute of Technology. Rather than focusing specifically on energy disaggregation, Watty is an energy analytics company that focuses on producing the insight required to save energy and money for specific buildings.

Wednesday 9 May 2012

Post first NILM workshop thoughts

I've just got back to the UK after attending the 1st International Workshop on Non-Intrusive Load Monitoring in Pittsburgh, USA. First of all, I'd like to congratulate the organisers, Mario Berg├ęs and Zico Kolter, for putting together such a great programme. By my guesses, there must have been 40-50 attendees, from academia, industry and other nonprofit organisations, which in my opinion well represented the research in this field to date.

I particularly enjoyed Sidhant Gupta's very well prepared video and video-conference link up from CHI 2012 in Austin. Sidhant's work takes quite a different perspective to most of the other work we saw at the workshop, since it uses the high frequency electromagnetic interference generated by appliances' switch mode power supplies as the basis for disaggregation. If you weren't at the workshop, you can find a small portion of the video he showed linked to from his website.

The topic of data set availability kept coming up throughout the day. I got the distinct impression that the academic community was crying out for more data, while the industry folks were unsure of how they could open up their own data sets to push the community forward. In the panel session, Zico raised the point that people shouldn't wait to perfect their data set before releasing it. This spurred Mario to release a data set from his home, and hopefully many more will emerge in the near future.

With REDD and Mario's data, that makes 2 data sets out in the wild for benchmarking NIALM methods. If I start to see any other data sets appear, I'll start blog post to help people keep track of them. I'll do my best to keep it up to date, but please email me or comment if you notice any mistakes or omissions.