Title Non-intrusive Load Monitoring
Name of Person Completing this Form
/ Dave Kresta
Proposer Contact Information
Please list the name, organization, and contact information of the primary person supplying the information for this form (usually the person who originally proposed this emerging technology). / NEEA

503-688-5459 (office)
503-442-9667 (cell)
Detailed Description
A class of products which monitor a building’s energy usage from a single point of access and disaggregate energy uses into individual components. Potential applications for NILMs includes 1) load monitoring/forecasting/research by utilities and energy efficiency organizations, 2) energy audit tool, 3) component of an energy management system to provide actionable information. Potential sectors include residential, commercial, and industrial, although most current efforts appear to be focused on residential applications. Access methods and degree of intrusiveness vary, including devices which plug into standard electrical outlets, devices requiring current transformers (CTs) at the electrical panel, devices which are inserted into the utility meter, and some methods which are software-only, utilizing SmartMeter data. Basic operations include: 1) signal processing (for methods with hardware) is performed, 2) the signal is uploaded to a computer server (typically in “the cloud”), 3) analysis using pattern matching and similar algorithms to identify and classify individual loads, and 4) downloaded to the user into a home energy management display or similar system. Approaches to identification of loads varies and is an ongoing area of research. Some methods require significant user training (turning devices on and off to “teach” the device), whereas other methods seek to leverage pre-loaded signature libraries that gain experience as they are exposed to more loads. The accuracy of products varies depending on the targeted usage, from a goal of very accurate load identification and characterization (at least as accurate as other metering technologies), to method’s seeking to simply identify the top energy uses to 10 or 20% accuracy.
Standard Practice
Existing monitoring techniques are invasive and expensive, requiring monitoring devices for each appliance or plug-load, typically requiring thousands of dollars per home and the installation of numerous pieces of equipment. In residential applications, whole home energy usage information is readily available along with comparative and trend data (e.g. oPower), but information on individual loads is not available making it difficult to ascertain which loads are responsible for energy usage. Conditional Demand Analysis (CDA) is a modeling technique which can be used to disaggregate end uses, but this requires time intensive field studies and surveys along with relatively large samples to support the statistical characterizations. Note that CDA does not support real time information, but is useful only for longer term studies.
Development Status and History
Pioneering NILM work was first introduced by George Hart in the 1980s. Enetics has offered products in this area since 1996, based on work by Hart and EPRI. Their product is dated (e.g Win 95 interface), requires an electrician to install at the utility meter, requires manual appliance identification, and does not provide real-time or automated load identification (although according to them they are “working on this”). Their business model and target market is utilities, requiring an investment of $1200/meter, $8000 for software. New developments in this area are focused on less intrusive monitoring, more sophisticated signal measurements and signal processing, lower costs, real-time load identification, and interfaces with energy management displays. These newer products are in the pre-commercialization phase. Companies currently developing products in this area include (in no particular order): Intel, Emme, Belkin, Enetics, Navetas, PlotWatt, Verdigrist, . Many other companies are offering products which do not currently provide disaggregating capabilities, but are focused on related areas such as metering, home area networks/home energy management systems such as TED, PowerHouse Dynamics, Blue Line Innovations, Energy Hub, Tendril, and many others.
Non-Energy Benefits
May provide real-time intelligence useful for O & M activities. For example a sporadic compressor load may indicate imminent failure, or higher than expected energy usage by an appliance could point to incorrect setup or faulty equipment.
End User Drawbacks
The pioneering work in NILMs occurred in the 1980s, but nobody has successfully driven this technology into the marketplace. Microsoft and Google have entered and exited the home energy management market, and there are a lot of startups as well as established companies trying to penetrate this market. More volatility in the market is to be expected, making it difficult for consumers as well as business partners to choose a way forward. The ability of the technology to successfully differentiate energy sources in a real environment still needs to be proven through lab and field studies. Also, the information must be presented and integrated into a system that provides actionable information (such as a home energy management display) that enables end users to make decisions that reduce their energy consumption. There is a danger of providing too much information, as well as too little, which could stifle the ability of this technology to penetrate the mass market. Research into the effectiveness of home energy management systems must accompany research into the core NILM technology to ensure energy savings benefits.
6  Energy Savings
What is the anticipated range of per-unit energy savings (and demand savings of this technology if relevant) relative to standard practice? This could be expressed as a percentage of baseline energy use. TBD.
7  Cost
Fully metering a home is cost prohibitive, running into the thousands of dollars. Pricing information on NILMs is scarce because of the pre-commercialization status. EMME is a Portland company working on a product that would cost in the $300-$400 range, with a $400 additional piece of display equipment required.
8  Effective Life
How long are the existing and proposed technologies expected to last? TBD.
Cost Effectiveness
What is the simple payback of this technology? Other forms of cost effectiveness (such as ROI) may also be useful here. If actual cost savings aren’t known, this can be a qualitative assessment. TBD.
10  Competing Technologies
What are competing technologies and products? See #2 above. There are several products on the market which do not disaggregate, but rather rely on low cost monitoring devices to plug in between appliances and the wall socket. These devices communicate wirelessly to a central unit and display energy uses for devices which are plugged into these monitoring devices. While these products do not contain elegant disaggregating technology, they could provide “good enough” insight into primary energy uses, particularly if a low-cost, non-intrusive method to incorporate whole home energy usage and dedicated circuit loads (such as HVAC, hot water, oven) was included with these products.
11  Advocates
What organizations or individuals have concluded that this emerging technology has strong potential for improved and cost-effective energy savings?
Some points of contact:
•  Dave Kresta, NEEA
•  Chris Holmes, EPRI – plan to address NILM in 2012
•  Michael Branmbley PNNL
•  Rich Brown, LBNL Scientist
•  Michael Zeifman, Fraunhofer Center
•  Kurt Roth, Fraunhofer
12  Emerging Technology Synopsis
Non-intrusive load monitoring devices (NILMs) monitor a building’s energy usage from a single point of access and disaggregate energy uses into individual components, eliminating the need for detailed sub-metering. NILMs require integration into an energy management display system, enabling end users to make energy efficiency decisions based on actual energy usage, providing insight into how their behavior and decisions impact energy usage on a load-by-load basis.
Products in this area are for the most part in the pre-commercialization phase, with ongoing work to drive down costs, improve ability to differentiate loads, integration with home energy management systems, and minimizing “intrusiveness” of the installation.
Lab and field testing is required in order to validate/confirm operation of these devices, particularly their ability to differentiate and accurately measure loads in a real-world environment.


Questions to Guide Discussion:

1.  What types of signals/ sensors/ info are we most in need of?

2.  Are there technologies ready for additional testing (is the time right; are we the right entity to do it)?

3.  What kind of research could be done in the next year?

Signals

kWh/mo

kWh/minute

Current

Voltage

Real and reactive power

Harmonics

EFI

Types of analysis

Detect “events”(identify appliance by watt draw increase)

Identify appliances via real and reactive power (e.g Refrigerator at 250W and 200 VAR)

Waveforms (current vs time, power vs time) - pattern matching of start up transients)

Magnitude of harmonics

Electromagnetic "noise" detection

Sensors

Utility meter

AMR utility meter

Utility meter add-on (reads kWh in smaller time intervals)

Plug (senses electrical signals for whole house)

CT (at meter)

CT (at panel)

CT (each circuit)

Plug (senses energy use for appliance plugged into it)

Uses of information

Customer: In-home display (whole house info)

Customer: Website feedback (whole house, trends)

Customer: end use information (rough estimates)

Customer: end use information (appliance specific info)

Research:

M&V:

Power Planning: load shapes for each end use

Power Planning: identification of types of loads and power system implications (CFLs vs LEDs, Power factor, motor load characteristics)

Applications

1.  Residential

2.  Commercial

Developmental stage

1.  Commercially available

2.  Pre-commercialization

a.  Beta

b.  Proof of concept

Potential types of research

Sensors

Signal interpretation (eg. “database of “signatures”)

Accuracy (including multiple identical loads, multi-state loads) for various purposes

Pair with other service (e.g. NILM plus Behavior for commercial facility)

Collaborate with EPRI, California, Fraunhofer, etc; Smartgrid, etc

Clarify what’s commercially available, costs, etc

Consider lab tests, field tests, etc

Utility/consumer issues (access to AMI signals, privacy, data storage, etc)

Test the simplest and the most complex