October 13th, 2015
France-Japan Smart Community ForumADEME-NEDO seminar on smart grids & Lyon smart community project

The current approaches and issues
on the smart community verification projects in Japan

Naoji Yamamoto
Senior Researcher
Smart Community GroupElectric Power Industry and Smart Community Research Subunit
Fossil Fuels and Electric Power Industry Unit

THE INSTITUTE OF ENERGY ECONOMICS, JAPAN(IEEJ)IEEJ：November 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.

The current situation of the smart community verification projects in Japan

p1○ Many projects were launched to establish smart community models since 2009 in Japan.
(As of August 2015: More than 120 cases)○ Representative of the project:“Next generation energy and social demonstration system verification project “ by the Ministry of Economy,
Trade and Industry in 4 areas (●).

③ Keihanna（Kyoto Area）① Yokohama-city

Housing estate model
・The followingness of the consumer side isinspected targeted for about 700 houses,
the buildings and the EVs, etc..

Wide area metropolis
model

Niseko・The large-scale project which targeted
for about 4000 houses and 10 buildings,
etc..
・ The project which integrates the storage battery in the area, and is managed
and controlled.

Mitsubishi Heavy Industries, Ltd.
Mitsubishi Electric Corporation
Kansai Electric Power Co., Inc. etc..

④ Kitakyushu-city

Kitakami

Regional urban centermodel

Kamaishi/Miyako

Aizuwakamatsu

・In a specific supply area, the cogeneration power plant is regarded as abase load power supply and thefollowingness is inspected targeted
for the area and the houses, etc..
Fuji Electric Co., Ltd.
NIPPON STEEL & SUMITOMOMETAL CORPORATION etc..

TOSHIBA CORPORATIONTokyo Electric Power Co., Inc. etc..

KazunoToyamaOnagawa/Kesennuma/Ohira/Ishinomaki
yamamoto

Minamiboso
Tsu

SaseboMinamata

Awaji
Fukuyama
Satsumasendai

Osaka

Miyakojima

Local production for local consumption
model using geothermal heatKazuno City, Akita

Local production for local consumption
model using geothermal heat

Kamaishi City, Iwate

CEMS model

Kitakami City, Iwate

CEMS model

Miyako City, Iwate

EMS model for the fish processing industrial
park

Onagawa Town, Miyagi

EMS model for the fish processing industrial
park

Kesennuma City, Miyagi

EMS model for the fish processing industrial
park

Ohira Village, Miyagi

EMS model for the industrial park

Ishinomaki City, Miyagi

CEMS model

Yamamoto Town, Miyagi

CEMS model

Minamisōma City, Fukushima Large-scale HEMS model

Hitachi City, Ibaraki

EV bus model

Kashiwa City, Chiba

CEMS model

Minamiboso City, Chiba

CEMS model② Toyota-City

Toyama City, Toyama

Compact city model

Tsu City, Mie

EMS model for campuses

Individual housing model

Osaka City, Osaka

V2B model

Osaka City, Osaka

CEMS model using groundwater heat

Awaji City, Hyogo

Local production for local consumption
model using electric storage facility

Tottori City, Tottori

CEMS model

Okayama City, Okayama

CEMS model using liquefied petroleum gas

Fukuyama City, Hiroshima

EMS model using a ship

Sasebo City, Nagasaki

EMS model for the theme Park

Minamata City, Kumamoto

EMS model for a fishing and agriculturalvillage

Satsumasendai City,
Kagoshima

EMS model for the industrial park

Miyakojima, Okinawa

Local production for local consumption
model for islands

・The project of local production for
local consumption at about 70 newly
built houses where the equipment ofenergy creation and saving energy
were established.
・ The project of a next generation
traffic system and car.

Key words of a smart community✔ Use of ICT.
✔ Efficient use of the area energy.
✔ Realization of comfortable living and business activity.

Niseko Town, Hokkaido

CEMS model

Kashiwa

Okayama

Form of the project

Aizuwakamatsu City,
Fukushima

Minamisōma
HitachiTottoriExample of project area

Toyota Motor Corporation andChubu Electric Power Co., Ltd. etc..

IEEJ：November 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.

The overview image of 4 area projects

p2

p3

ICT

Household sector
Information and Communication
Technology

Energy management
in a consumer side

Target field for projects

Smart house

ICT

Business and Industrial
sectorTransportation
sector

ICT

EV/PHV
Modal shift
Factory

General house
Building

FC BusFuel cell-powered
vehicleCGS

ICTEnergymanagement

ICT

Compact
EV

Community (or Area)
ｋＷ

Inhibitory doseof the electric amount of consumption（Mainly）

Index ofthe measure▲kWh
Inhibitory dose
Hour

Confirmationof the effect1
The effectof Energy saving

2

The effectof carbon dioxide
emissions reduction

3

The effectof reduction inpeak electric power＋

Variousquestionnaire
results

IEEJ：November 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.

The type of energy management

Type

Explanation of outline

Case Ⅰ
Dynamic pricing

The verification experimentof the DR
which is led by electricity rate

p4

～

p6

Case Ⅱ
The verification experimentof the DR using EMS
p7

～

p12

※DR ：Demand Response※EMS ：Energy Management System✔ Assume tightness of electric power supply
and demand.
✔ Control electricity rates for targeted generalhouseholds.
✔ Recommend the verification participant
about an electricity rate of the peak time ofthe day beforehand on the previous dayof the DR day.
✔ Monitor reaction of consumers for energy
saving .
✔ Control power demand by using EMS foreach sector including residential, business,
industrial, transportation, or a wholecommunity.
✔ Monitor reaction of consumers for energy
saving and adjustment of supply anddemand by DR.

p3

Main
inspection item
EnergysavingCarbondioxideemissions
reduction

●

（▲）

●

Power
peak-cut●●

IEEJ：November 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.

The basic specification for Dynamic Pricing

Case Ⅰ

Basic specification

Weekday（Usually）
Day of the DR
Several times
during theone season

Approaches for
effective
improvement

Smart
meter

Visualizationof the electricamount ofconsumption※１▲▲

Dynamic Pricing ※２※ＤＲ：Demand Response

Recommend of the DR

TOU（Time of Use）

（Critical Peak Pricing）

CPP ※３Home display

PC or Smartphone, etc.

●

－

－

●

－

●

●

●

－

●

（Multi-step type）※１ Improvement of the visualization effect ：The visualization of the electric amount of consumption with an additional value.（Ranking indication, etc.）※２ Improvement of TOU and CPP effect ：The consulting for energy saving.（Energy saving method or recommend replacing old appliances, etc.）※３ Joining promotion of the CPP（opt-in type）：“Bill Protection” （Notify electricity rate of CPP service）“Shadow Billing” (Compare charges between CCP rate and usual rate)

Image of TOU

Image of CPP

Electricity rate

・The unit price of electricity rate is fixedaccording to the each season or time.

Electricity rate

p4

WeekdayBasemultiplied by 4・Higher electricity rate unit priceis set compared to usual
rates for emergency peak.
・Send a notice of electricity
rate beforehand on theprevious day of the DR day.

Base
multiplied by 3
Basemultiplied by 2

Day of the DR

Base

Base
Peak time

0 am

7 am

11 pm

12 pm

0 am

7 am

1 pm

4 pm

11 pm

12 pm

IEEJ：November 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.

The system configuration which achieves Dynamic Pricing

Case Ⅰ

System pattern １

System pattern ２
ServerServerData of electric information

Power measuring
instrument

Distribution board

p5

Internet

Internet

A route: Cellular phone system
BluetoothB route

Smart
meter

Data of electric
information

DR
Smart
Improvedphone,
electronic meter
CellularRouterHome display
phone（Data of 1 day before）
or PC, etc.

Router

Adapter

Home display（ Data of 1 hour before ）System pattern ３DR

System pattern ４

Only forapplicantsSmartphone,
Cellularphone
or PC, etc.

Data of electric information
ServerConcentrator

Internet

Internet

B route: 2.4GHz
Smart
meter

Data of electric
information

Wireless LAN
Home display Routerrepeater（ Data of 30 minutes before ）※DR：Demand Response

Specified low
power radio

DR
Smart
phone,
Cellularphone
or PC, etc.

DR

ServerB route: Wi-fi

Smart
meter

Home display（ Data of 30 minutes before ）IEEJ：November 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.

Case ⅠThe consideration of a result of a dynamic pricing verification experiment
Yokohama city

Apr. 2013 - Sep. 2014

Verification periodp6

Toyota city

Keihanna (Kyoto area)

Kitakyushu city
Fuji ElectricJan. 2013 - Feb. 2014

Jul. 2012 - Feb. 2014

Jul. 2012 - Feb. 2014

ParticipationenterpriseTOSHIBA ,Panasonic etc.

Chubu Electric Power

Mitsubishi Heavy Industries (MHI)
Mitsubishi Electric (MELCO)
Kansai Electric Power

Number of households（without Photovoltaics）

About 1,080 houses

About 90 houses

About 700 houses

About 180 houses（in a special supply area）

Electrification rate

40%

73%

30%

100%※１TOU
Electric
rate

CPP

※２

Classification

Remarks(Weekday) ¥45／kWh(Holiday) ¥21／kWh¥100／kWh（１step）
Virtual priceNon-publication

Non-publication(Weekday) ¥20／kWh¥50 , 80 , 100／kWh（３Step）¥40 , 60 , 80／kWh（３Step）¥50 , 75 , 100 , 150／kWh（４Step）

Virtual price

Virtual priceReal price・Bill Protection
・Shadow Billing※２ ¥1 = $79（2012.7）～ $107（2014.9）、€97（2012.7）～ €138（2014.9）(Summer)▲2.9～▲5.9%(Summer)▲18.8～▲20.2%(Winter) ▲10%(Winter) ▲2.0～▲4.0%(Winter) ▲16.2～▲16.6%(Summer)▲9.3%～▲14.9%(Winter) Non-publication

Image of the analysis of the effect

Implementationof the CPP

Visualization

Implementationof the CPP

Visualization

Implementationof the CPP￥balance：
returned to a participant※It's subtracted according to the electric
One season
amount of consumption used at the DR time.

＋
TOU
＋
CPP

Comparison of the electricamount of consumption
Control group

Treatment group

Image of the effect of an energy saving

Control
group

TOU

about▲１０％
CPP

CPP CPP

effect（included in the following）

Image of the Virtual priceThe given price in advance（saved price）(Summer)▲11%（included in the following）

The standard
in the verification

CPP(Winter) ▲11.7%(The ▲9.1% in the Tokyo
result in 2011 is included in
the following, because ※１.)

(Summer)▲9.1%

The electric amount of consumption(kWh）

Effectof theenergysavingTOU

Total～about max▲２０％
Treatment group

IEEJ：November 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.

Case Ⅱ

Image of the verification experiment of the DR using EMS※EMS： Energy Management System※DR ：Demand Response

Smart Community
Generalelectricity utility（Virtual）

Community (or Area)

Demand forecasting

Community (or Area)

ＣＥＭＳ／ＡＥＭＳ （ＥＤＭＳ）
DR

Open ADR 2.0b
The verificationof WASEDA University（DRAS）※EDMS：
Energy Data Management System

Point
management
CenterDR

DR※DRAS：Demand Response Automation ServerHouseholdsectorStoragebattery

Photovoltaics／Solar heat

ＨＥＭＳ
Photovoltaics

p7

Storage battery for community

Transportation
sectorBusiness and Industrial
sectorPhotovoltaics

EV management
centerＢＥＭＳ
Building

House

ＥＶＣ
Photovoltaics

EMS

Vehiclecharging stand
HEMS

Storage battery

Apartment
ＭＥＭＳ

V2M

Heat source equipment

Heat source
equipment

Photovoltaics

Vehicle charging stand
BEMS

EV

Storage battery
for V2H
Photovoltaics
PHV／EV
Heat source equipment(CGS etc.）
HEMS

Photovoltaics

Storage battery
Next generation vehicle
TDMS
FC

ＦＥＭＳ
Factorye.g.) Heat pump

PHV

Storage battery
for V2X

Fuel Cell Bus
FEMS

Storagebattery

CompactEVe.g.) Fuel cell

Storage battery

Refrigerated car with Storage battery
Heat source equipment Storage battery(CGS etc.）
IEEJ：November
2015, Copyright© The Institute of Energy Economics,※TDMS： Traffic
Data AllManagement
Japan
Rights System
Reserved.

Case Ⅱ

Yokohama ： Case study of the Storage Battery SCADA system（TOSHIBA, etc.）

p8○ Characteristic of the storage battery SCADA system ：・ The management system which controls multiple batteries installed in houses, buildings or the community as one virtual battery.

○ Advantage of the storage battery SCADA system：

・ Reduction of the operative cost of the storage battery.
・ Realization of "System stabilization" and “Large scale introduction of renewable energy" by using the storage battery.

Power
Peak-cut

Image of the Storage battery SCADA※SCADA：Supervisory Control And Data Acquisition

Discharge control

Bulk power system（Grid）【An example of the result】

Power distribution system(Grid)

Concentrated
Storage battery（virtual battery）

House

・Target value of the peak-cut（1pm～4pm): 1,640kWh
Host system
ＥＭＳ・Result

DR

Storagebattery
SCADA

chargedischarge

Ａ block

Charge control

chargeTotal of 3 units： 650kW
Building （ lithium-ion battery）

House

chargeＢ block（ Storage battery ）Load leveling

Storage battery
for community
discharge

Structure for
Storage battery SCADA HITACHIMEIDENSYA and NEC（Storage battery）
discharge：1,535kWh（94％ achievement）

Ｃ block（ Storage battery ）chargeTOSHIBA

discharge

Customer：about 500 houses※Source of photo： “Smart City Portal of New Energy Promotion（Assumption value)
Council Japan.”（add descriptions)
IEEJ：November 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.

Case Ⅱ

Toyota： Case study of the Next Generation Vehicles（Toyota Motor, etc.）

p9○ Approach of the household sector：

・The "V2H" verification experiment which regards a battery for PHV and an EV as one of charging equipment, and charges and discharges
a battery.

○ Approach of the transportation sector：

・Example① The verification experiment about the peak-cut and peak-shift of the electric power (Smart charge infrastructure).
・Example② The verification experiment about the supply of electric power to disaster protection shelter base (Fuel cell vehicle :FC Bus).
・Example③ The verification experiment about the Modal shift (One mile mobility: Ha-mo RIDE , etc.).

Image of the transportation sector

Image of the household sector
ＣＯ２▲７０％（ 2014 records compared to 2005 ） ※TDMS：
Traffic Data Management System

EDMS

Photovoltaics

Internet※EDMS：
Energy Data Management System

TDMS

EDMS

About 70 houses
CONTROLLER
OF HOUSEHOLDAPPLIANCE

HEMS

Ex. ①
Peak-cut and peak-shift

Distribution
board

Ex. ② Supply of electric
power to disasterprevention shelter baseDisaster prevention
shelter base

CONTROLLER

Ex. ③
Modal shift

Use of public
transportation

High Speed
Power Line
Communication
PHV/EV

Storage battery（Lead-acid or Lithium-ion）

Battery
4.4kWhHeat source equipment（Heatpump or Fuel Cell）
AC100V
1.5kW

V2H（Vehicle to Home）

Amountof the charge （kW）

Control of thesmart charge infrastructurePowersupplydeadline

DC/AC

FC Bus100 cars

Use of carshare（one mile mobility）

DC100VPower peak-cut
Max ▲30％hour

・Maximum output：9.8kW
・Continuous supply：175.5kWh

CO2
▲10％

Compact EV

IEEJ：November 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.

Case Ⅱ

Keihanna： Case study of the CEMS and EV（MHI, MELCO, etc.）

p 10○ Characteristic of the CEMS verification experiment：

・The verification experiment of the adjustment type of supply and demand which regards an entire community as a consumer including
homes, buildings and EVs, and controls the supply and demand for 24 hours depending on a purpose.
・The realization of the energy saving and the carbon dioxide emissions reduction are controlled, and the supply of electric power is linked
with a market price.

○ Characteristic of the EVC verification experiment：

・The verification experiment to reduce a burden of the system electricity by receiving DR request from CEMS, and controlling a charge
timing of EV.

Image of the EVC verification experimentImage of the adjustment of supply and demand・DR to recommend
1day before.
・DR to recommend
before time.

Prediction of
the community
demandCEMS
Total demand
3.3MW(Assumption value)DR（about 1 hour before）

・Hours of DR：
about 3～1 hours

EVC

CEMS
Storage battery
for community(by the simulator)

DR

Photovoltaics

23 units

1MW（Assumption value)

30kW

3～4kW

10kWh

Electricity demand （kW）

HEMS

Assumption demand
about 3MWh

BEMS

30kWh

EV

16kWh
and10.5kWh

The timing of EV charging is controlled.

Community demand

Battery

Target demand

Send a message topromote EV charge.

Within ±３％30-minute balancing rule（about 80％ achievement）

100 units of EV

Charge demand: 30％ increase

Hour

Surplus electric power(Peak time)

EV ＝ Buffer of thesurplus electric power

IEEJ：November 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.

Kitakyushu： Case study of the CEMS （ Fuji Electricetc Co., LTD.）

Case Ⅱ

p 11○ "Cogeneration power plant" and “Regional power saving station" are established in a specific supply
area, and a verification experiment with an actual charge base is developed.
○ The role of Regional power saving station：

・To manage the overall energy services in the area, such as electricity, heat, and water.
・To provide the low electric charges by controlling the storage battery of the houses or community
according to the supply demand situation in the area.

Image of Regional power saving station
・ Energy saving （Target ▲50％）: about 52％ achievement
・ Carbon dioxide emissions reduction（Target ▲20%）: about 40％ achievement※ 2014 records compared to 2005

Electric power system（Grid）

Yahata-higashida area

Regional powersaving station Prediction of Specific supply area

Yahata-higashida area

（about 120 hectare ＝ 297 acre ）Shimonoseki-City

the area demand

CEMS
Cogeneration power plant（33MW）FC power
Total demand generation
Hydrogen
21ＭＷ

Kitakyushu-City
Fukuoka-city○ Regional power saving station

Photovoltaics

Wind power
generation

Heat supply

HEMS

BEMS

FEMS

Solar heat
Earth thermal

Storage battery
for community（300kW）

General household（230 houses）

Factory, Hospital andRetail store, etc.
（70 offices）※Source of photo: “Smart City Portal of New Energy Promotion
Council Japan.”

IEEJ：November 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.

Case Ⅱ

The basic specification of the verification experiment of the DR using EMS○ The type of energy management ：p 12※DR：Demand Response

After visualizing the electric amount of consumption, mainly, it's classified into 2 types,“the indirect control system which controls person's behavior" and "the direct mechanical control system by which a machine controls itself".

○ The storage charge is a common indispensable item of each sector as a coordinating role of target
achievement and demand fluctuation by PV.
Basic specification
Sector

Smart
meter

Visualization ofelectricity consumption
Formanager

Type of energy management
Indirect

Prediction Recommend of the DR
controlofthe demand
PC orIncentiveFor
Home（PV, etc.）
Smart
（EMS）
consumers
displaypayphone, etc..
Renewable
EnergyDirect control
Heat

Load
control

Storagesourcebattery equipment

Other
ChargeShorteningofinfrastructure the DR time

○

－

△

○

○

－

○

○

－

－

－

△

HEMS

△

－

○

○

○

○

△

○

○

△

△

－

－

BEMS
FEMS

△

○

○

○

○

○

－

○

○

○

○

－

－

EVC

△

○

○

○

○

○

△

○

○

－

－

○

△

Remarks

・There aremeasurement
methods with
CT and the tap.

＋＋

Control time・Introduce
energy saving
equipment andgas equipment.
・Expansion of
the heat supply.
etc..

Control machines

Controlperson's behavior

・DR to recommend 1 day before.
・DR to recommend before time.

Recommendation of DR（Setting of the target）

Prediction of the demand

Acceptanceof the renewable energy

・The effect islimited.

（ Confirmation of results ）Visualizationof electricity
consumption－

Prior steps for managing
electricity demand

CEMS

IEEJ：November 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.

The consideration of issues based on 4 area verification projects

p 13

SectorIssuesExpected domains in future

Community(or Area)○ How to secure funds for the DR incentive payment.
○ Development of the capacity market and PPS market.
○ Expansion of the equipment and sector for the DR
service.

○ Energy aggregator business.
○ Application of CEMS as a method to reinvigorate local
economy.
e.g. Service to promote purchasing will of consumers
and change their actions.

Household○ How to secure funds for the DR incentive payment.

○ Develop mechanism for surplus electric power
generated from PV within a home.
e.g. Dissemination of HEMS, PV, Storage battery asa set.
○ Harmonize between energy and services and closely
link with daily life.
e.g. Management of health and medical care,crime prevention, and the distribution network.

○ Expansion of the household appliance and equipment
for the DR service.
○ Durability of energy saving behavior and visualization
effect .

BusinessandIndustrial○ How to secure funds for the DR incentive payment.
○ Improvement of the precision of the demand prediction
technology (Avoid imbalance).
○ Introduction of EMS based on cost-effectiveness(Development of the local implementation type andthe cloud type depending on a building scale).

Transportation○ How to secure funds for the DR incentive payment.
○ Expansion of the equipment for the DR service.
・The spread of next-generation cars.
・The spread of energy filling stations.
・The spread of traffic management systems (TMS).

○ Business of the negative watt in the electric market.
e.g. Spread of Cloud based BEMS.
○ Energy saving as the whole energy system.
e.g. ・Adaptation of the electricity and heat supply as a
set in wider area.
・Expansion of the visualization of the gas demand
and the DR service.
○ Promotion business of EV charging using surplus
electricity generated by PV.
○ Preparation for the dissemination of TMS.
e.g. Establish a dissemination framework including thecooperation with the traffic authorities.

※PPS : Power Producer and Supplier○ It is a common issue to secure funds for the DR incentive pay.
○ It's the biggest issue to seek a method of incorporating such a mechanism in the society.
This is a more significant issue than a technical issue.

IEEJ：November 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.

Challenge for the spread of a smart community

p 14

Needs for a smart community
Measuresfor disaster prevention

Flexible energy usage
within an area

Affordable
electricity rate

Resilience

Local production for local
consumption of energy

Measuresfor environment

Improvementof the local value

City planning
Compact city

Regional economy
revitalization
Improvementof administrative service

Value-added service
Internet of Things(IOT)

Judgment

Cost

etc.

３Ｅ＋Ｓ
Ripple effectin the area

Benefit

Satisfaction
Quality of life (QOL)

It‘s necessary to judge
overall based on thecost benefit and an
additional value.
Regional attractivenessComfortetc.

※3E+S : Energy Security , Economic Efficiency , Environment and
Safety 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.
IEEJ：November

p 15

Thank you for your attention.

URL：http://eneken.ieej.or.jp
Contact :report@tky.ieej.or.jp

IEEJ：November 2015, Copyright© The Institute of Energy Economics, Japan All Rights Reserved.