MITSUBISHI ELECTRIC CORPORATIONPUBLIC RELATIONS DIVISION
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Mitsubishi Electric Develops Visualization Technology for Use in
Domestic Power Consumption Management
Estimates the power consumption of home appliances without the need for additional equipment

TOKYO, January 29, 2019 – Mitsubishi Electric Corporation (TOKYO: 6503) announced today that it hasdeveloped new technology that allows the estimated power consumption of individual home appliances to be
extrapolated from the overall power consumption of each household. The new solution, the result of joint
research with Tohoku Electric Power Co., Inc., makes use of Mitsubishi Electric’s pioneering AI technology
Maisart®* to estimate power consumption to a high degree of accuracy without the need to install newmeasuring instruments.
* Mitsubishi Electric's AI creates the State-of-the-ART in technology

With this new technology, Mitsubishi Electric Corporation aims to spur the provision of new services using
the power consumption data of electricity supply companies and to improve energy conservation awareness inhomes. The solution has already been deployed in an energy-saving assist service under the Customer-Assisted
Smarter Project that Tohoku Electric Power Co., Inc. commenced in July 2018.**** See Tohoku Electric Power Co., Inc.’s news release at http://www.tohoku-epco.co.jp/news/normal/1197475_1049.html

Based on the results of recent verifications, Mitsubishi Electric Corporation will continue research anddevelopment aimed at further improving the estimation accuracy of its new solution.

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Fig. 1 Outline of visualization of power consumption details

Background
Smart meters that measure household electricity consumption at frequent regular intervals are becoming
increasingly common. Existing smart meters only measure the overall power consumption of the whole house,but there is a growing need to know the power consumption of individual home appliances. Technically, theinstallation of a current sensor on the home’s power distribution board would allow the power consumption ofeach appliance to be monitored, but the cost of installing such sensors can be prohibitive. Mitsubishi Electric
Corporation has therefore developed this new "Technology to Visualize Power Consumption" solution, which
deploys artificial intelligence to extrapolate the power consumption of individual home appliances from thepower consumption of the whole house to a high degree of accuracy.
Key Features
1) Leverages AI technology to estimate individual home appliance power consumption without the needfor additional measuring devices- Artificial intelligence is used to extrapolate the power consumption of each home appliance from thepower consumption data of the whole house, as measured by a smart meter.
- No need to install new measuring instruments since existing smart meters are used.
- The amount of data collected and stored is just one percent of that required by conventional
estimation methods.
Using AI, typical electricity usage patterns are extracted from data such as family composition and theattributes of the home appliances. The power consumption of each home appliance is then extrapolated

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from the power consumption data of the whole house measured by a smart meter. Traditional methods
measure the power consumption of individual home appliances at intervals of 10 seconds or less using acurrent sensor or other measuring device. However, this new technology utilizes the existing data captured
by smart meters, so there is no need to install new measuring instruments. As a result, the amount of stored
data can be reduced to one percent or less of that required by existing methods, which in turn reduces theamount of calculation required to provide estimates.
2)

Typical patterns allow power consumption for each home appliance to be estimated to a high degreeof accuracy- The AI functionality performs a three-stage clustering based on the power consumption of the wholehouse and each home appliance measured in advance within monitored houses, as well as informationon the composition of the family and the home appliances they own.
- A typical pattern is created using AI, which corrects fluctuations caused by variations in daily activity
time and groups together houses with similar power consumption characteristics.
- The AI functionality automatically selects the most similar typical pattern, reducing errors by applying
actual values and achieving a high level of accuracy.
The AI functionality performs three-stage clustering (see Fig. 2) based on the pre-measured power
consumption of the whole house and each home appliance, and on attributes such as family composition
and the number and type of home appliances. Houses with similar electricity usage are automaticallygrouped and representative values for each group are created as a typical pattern. In addition, by absorbing
minor time fluctuations in activities that vary depending on the day and the family, such as waking, cooking
and the time at which family members return home, the AI calculates the correlation between the typicalpattern and the measured data to estimate power consumption more accurately (see Fig. 3). Since the AI
function automatically selects the most similar typical pattern, the discrepancy with actual values is reduced,achieving a high level of estimation accuracy.

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AI extracts attributes that determine the daily power consumption of each home appliance;
Stage 1for example, the characteristics of groups whose usage of air conditioners accounts for a large
proportion of their total electricity consumption (e.g. their daily power consumption, floor
space, the age of their house)
The results of groupings made in the first stage are further classified by the similarities

Stage 2

established by smart meter measurements, such as those using more electricity in the morningand evening and those using more electricity during the night.
The results of grouping in the second stage are further classified by the similarities of the hour-Stage 3

by-hour power consumption for each home appliance, such as those using air conditionersregardless of the time of day, those using air conditioners only at night or those using air
conditioners extensively in the mornings and evenings.
Fig. 2 Method of creating a typical pattern

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Fig. 3 Power consumption estimation method for each home applianceContribution to the Environment
The provision of energy-saving advices and other services to households by electric power companies helps
reduce the environmental impact of energy generation by promoting energy conservation in homes.
About Maisart
Maisart encompasses Mitsubishi Electric’s proprietary artificial intelligence (AI) technology, including its
compact AI, automated design deep-learning algorithm and extra-efficient smart-learning AI. Maisart is anabbreviation for "Mitsubishi Electric's AI creates the State-of-the-ART in technology." Under the corporate
axiom "Original AI technology makes everything smart," the company is leveraging original AI technology
and edge computing to make devices smarter and life more secure, intuitive and convenient.
Patents
Pending patents for the technology announced in this news release number four in Japan.
Maisart is a registered trademark of Mitsubishi Electric Corporation.

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About Mitsubishi Electric Corporation
With nearly 100 years of experience in providing reliable, high-quality products, Mitsubishi ElectricCorporation (TOKYO: 6503) is a recognized world leader in the manufacture, marketing and sales of electricaland electronic equipment used in information processing and communications, space development and satellitecommunications, consumer electronics, industrial technology, energy, transportation and building equipment.
Embracing the spirit of its corporate statement, Changes for the Better, and its environmental statement, EcoChanges, Mitsubishi Electric endeavors to be a global, leading green company, enriching society withtechnology. The company recorded consolidated group sales of 4,444.4 billion yen (in accordance with IFRS;
US$ 41.9 billion*) in the fiscal year ended March 31, 2018. For more information visit:
www.MitsubishiElectric.com*At an exchange rate of 106 yen to the US dollar, the rate given by the Tokyo Foreign Exchange Market on
March 31, 20186/6