The current situation of the smart community verification projects in Japan p 1 Many projects were launched to establish smart community models since

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1 October 13th, 2015 France-Japan Community Forum ADEME-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 Community Group Electric Power Industry and Community Research Subunit Fossil Fuels and Electric Power Industry Unit THE INSTITUTE OF ENERGY ECONOMICS, JAPAN(IEEJ)

2 The current situation of the smart community verification projects in Japan p 1 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) Housing estate model The followingness of the consumer side is inspected targeted for about 700 houses, the buildings and the EVs, etc.. Mitsubishi Heavy Industries, Ltd. Mitsubishi Electric Corporation Kansai Electric Power Co., Inc. etc.. 4 Kitakyushu-city Regional urban center model In a specific supply area, the cogeneration power plant is regarded as a base load power supply and the followingness is inspected targeted for the area and the houses, etc.. Fuji Electric Co., Ltd. NIPPON STEEL & SUMITOMO METAL CORPORATION etc.. Sasebo Minamata Tottori Okayama Osaka Awaji Fukuyama Satsumasendai Tsu Kazuno Aizuwakamatsu Toyama Niseko Kitakami Hitachi Kashiwa Kamaishi/Miyako Onagawa/Kesennuma/Ohira/Ishinomaki yamamoto Minamisōma Minamiboso Miyakojima Key words of a smart community Use of ICT. Efficient use of the area energy. Realization of comfortable living and business activity. 1 Yokohama-city 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. TOSHIBA CORPORATION Tokyo Electric Power Co., Inc. etc.. Wide area metropolis model 2 Toyota-City Individual housing model The project of local production for local consumption at about 70 newly built houses where the equipment of energy creation and saving energy were established. The project of a next generation traffic system and car. Toyota Motor Corporation and Chubu Electric Power Co., Ltd. etc.. Example of project area Niseko Town, Hokkaido Kazuno City, Akita Kamaishi City, Iwate Kitakami City, Iwate Miyako City, Iwate Onagawa Town, Miyagi Kesennuma City, Miyagi Form of the project Local production for local consumption model using geothermal heat Local production for local consumption model using geothermal heat CEMS model CEMS model EMS model for the fish processing industrial park EMS model for the fish processing industrial park EMS model for the fish processing industrial park EMS model for the industrial park Ohira Village, Miyagi Ishinomaki City, Miyagi CEMS model Yamamoto Town, Miyagi CEMS model Minamisōma City, Fukushima Large-scale HEMS model Aizuwakamatsu City, Fukushima Hitachi City, Ibaraki Kashiwa City, Chiba Minamiboso City, Chiba Toyama City, Toyama Tsu City, Mie Osaka City, Osaka Osaka City, Osaka Awaji City, Hyogo Tottori City, Tottori Okayama City, Okayama Fukuyama City, Hiroshima Sasebo City, Nagasaki Minamata City, Kumamoto Satsumasendai City, Kagoshima Miyakojima, Okinawa CEMS model EV bus model CEMS model CEMS model Compact city model EMS model for campuses V2B model CEMS model using groundwater heat Local production for local consumption model using electric storage facility CEMS model CEMS model using liquefied petroleum gas EMS model using a ship EMS model for the theme Park EMS model for a fishing and agricultural village EMS model for the industrial park Local production for local consumption model for islands

3 The overview image of 4 area projects p 2 Target field for projects Energy management in a consumer side p3 Information and Communication Technology Household sector house ICT General house ICT Community (or Area) ICT Business and Industrial sector Building Energy management CGS Factory ICT Transportation sector EV/PHV FC Bus Fuel cell-powered vehicle ICT Modal shift Compact EV Index of the measure Inhibitory dose of the electric amount of consumption(mainly) kw kwh Inhibitory dose Hour Confirmation of the effect The effect of Energy saving The effect of carbon dioxide emissions reduction The effect of reduction in peak electric power + Various questionnaire results

4 The type of energy management p 3 Type Explanation of outline Energy saving Main inspection item Carbon dioxide emissions reduction Power peak-cut Case Ⅰ Dynamic pricing The verification experiment of the which is led by electricity rate p4 ~ p6 Assume tightness of electric power supply and demand. Control electricity rates for targeted general households. Recommend the verification participant about an electricity rate of the peak time of the day beforehand on the previous day of the day. Monitor reaction of consumers for energy saving. ( ) Case Ⅱ The verification experiment of the using EMS p7 ~ p12 Control power demand by using EMS for each sector including residential, business, industrial, transportation, or a whole community. Monitor reaction of consumers for energy saving and adjustment of supply and demand by. :Demand Response EMS :Energy Management System

5 Case Ⅰ The basic specification for Dynamic Pricing p 4 Basic specification :Demand Response Dynamic Pricing 2 meter Visualization of the electric amount of consumption 1 Recommend of the Home display PC or phone, etc. TOU (Time of Use) CPP 3 (Critical Peak Pricing) Weekday (Usually) Day of the Several times during the one season - (Multi-step type) Approaches for effective improvement 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 fixed according to the each season or time. Weekday Electricity rate Higher electricity rate unit price is set compared to usual rates for emergency peak. Send a notice of electricity rate beforehand on the previous day of the day. Day of the Base multiplied by 4 Base multiplied by 3 Base multiplied by 2 Base Base Peak time 0 am 7 am 11 pm 12 pm 0 am 7 am 1 pm 4 pm 11 pm 12 pm

6 Case Ⅰ The system configuration which achieves Dynamic Pricing p 5 System pattern 1 System pattern 2 Server Server meter Distribution board B route Bluetooth Power measuring instrument Data of electric information Adapter Router Home display ( Data of 1 hour before ) Internet phone, Cellular phone or PC, etc. Improved electronic meter Data of electric information A route: Cellular phone system Router Home display (Data of 1 day before) System pattern 3 System pattern 4 Internet Only for applicants phone, Cellular phone or PC, etc. Data of electric information Server Internet Concentrator Internet Server meter B route: 2.4GHz Wireless LAN Router repeater Home display ( Data of 30 minutes before ) :Demand Response Data of electric information phone, Cellular phone or PC, etc. Specified low power radio meter B route: Wi-fi Home display ( Data of 30 minutes before )

7 Case Ⅰ The consideration of a result of a dynamic pricing verification experiment p 6 Yokohama city Toyota city Keihanna (Kyoto area) Kitakyushu city Verification period Apr Sep Jan Feb Jul Feb Jul Feb Participation enterprise Number of households (without ) TOSHIBA,Panasonic etc. Chubu Electric Power Mitsubishi Heavy Industries (MHI) Mitsubishi Electric (MELCO) Kansai Electric Power About 1,080 houses About 90 houses About 700 houses Fuji Electric About 180 houses (in a special supply area) Electrification rate 40% 73% 30% 100% 1 Electric rate 2 Effect of the energy saving TOU CPP Remarks (Weekday) 45/kWh (Holiday) 21/kWh 100/kWh (1step) Non-publication (Weekday) 20/kWh Non-publication 50, 80, 100/kWh (3Step) 40, 60, 80/kWh (3Step) 50, 75, 100, 150/kWh (4Step) Classification Virtual price Virtual price Virtual price Real price Bill Protection Shadow Billing 2 1 = $79(2012.7)~ $107(2014.9) 97(2012.7)~ 138(2014.9) TOU (included in the following) (included in the following) CPP (Summer) 9.3%~ 14.9% (Winter) Non-publication (Summer) 11% (Winter) 10% (Summer) 9.1% (Winter) 11.7% (Summer) 2.9~ 5.9% (Winter) 2.0~ 4.0% (The 9.1% in the Tokyo result in 2011 is included in the following, because 1.) (Summer) 18.8~ 20.2% (Winter) 16.2~ 16.6% The given price in advance (saved price) Image of the Virtual price Image of the analysis of the effect Image of the effect of an energy saving Implementation of the CPP Implementation of the CPP balance: returned to a participant Implementation of the CPP It's subtracted according to the electric amount of consumption used at the time. One season Visualization Control group Visualization + TOU + CPP Comparison of the electric amount of consumption Treatment group The electric amount of consumption (kwh) The standard in the verification Control group TOU about 10% CPP CPP CPP Treatment group effect Total ~about max 20%

8 Case Ⅱ Image of the verification experiment of the using EMS p 7 General electricity utility (Virtual) Demand forecasting Community Community (or Area) CEMS/AEMS (EDMS) EDMS: Energy Data Management System EMS: Energy Management System :Demand Response Community (or Area) Open A 2.0b The verification of WASEDA University (AS) AS:Demand Response Automation Server Point management Center for community /Solar heat Household sector HEMS House Storage battery Business and Industrial sector Building BEMS EV management center EMS Transportation sector EVC Vehicle charging stand Apartment V2M MEMS Heat source equipment e.g.) Heat pump e.g.) Fuel cell Heat source equipment for V2H HEMS Vehicle charging stand PHV/EV HEMS BEMS Heat source equipment (CGS etc.) FEMS Factory Heat source equipment (CGS etc.) for V2X FEMS EV Fuel Cell Bus Copyright The Institute of Energy Economics, TDMS: Traffic Japan Data All Management Rights System Reserved. PHV Next generation vehicle FC Storage battery TDMS Compact EV Refrigerated car with

9 Case Ⅱ Yokohama : Case study of the Storage Battery SCADA system(toshiba, etc.) p 8 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. Image of the SCADA SCADA:Supervisory Control And Data Acquisition Power Peak-cut Power distribution system (Grid) Bulk power system (Grid) An example of the result Target value of the peak-cut (1pm~4pm): 1,640kWh Charge control Discharge control House A block () charge discharge Concentrated (virtual battery) charge discharge House B block ( ) Host system EMS Storage battery SCADA Building C block ( ) Result :1,535kWh (94% achievement) for community Total of 3 units: 650kW ( lithium-ion battery) charge discharge charge discharge Customer:about 500 houses (Assumption value) Structure for SCADA MEIDENSYA and NEC TOSHIBA Load leveling HITACHI Source of photo: City Portal of New Energy Promotion Council Japan. (add descriptions)

10 Case Ⅱ Toyota: Case study of the Next Generation Vehicles(Toyota Motor, etc.) p 9 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 ( 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 household sector Image of the transportation sector EDMS Internet CO2 70% ( 2014 records compared to 2005 ) TDMS: Traffic Data Management System EDMS: Energy Data Management System TDMS EDMS About 70 houses CONTROLLER OF HOUSEHOLD APPLIANCE HEMS Distribution board Ex. 1 Peak-cut and peak-shift CONTROLLER Ex. 2 Supply of electric power to disaster prevention shelter base Disaster prevention shelter base Ex. 3 Modal shift Use of public transportation PHV/EV Battery 4.4kWh High Speed Power Line Communication AC100V 1.5kW (Lead-acid or Lithium-ion) Heat source equipment (Heat pump or Fuel Cell) V2H(Vehicle to Home) Control of the smart charge infrastructure Amount of the charge (kw) deadline Power supply FC Bus DC100V DC/AC 100 cars Use of carshare (one mile mobility) Maximum output hour :9.8kW Power peak-cut CO2 Continuous supply Max 30% 10% Compact EV :175.5kWh

11 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 request from CEMS, and controlling a charge timing of EV. Image of the adjustment of supply and demand Image of the EVC verification experiment Prediction of the community demand to recommend 1day before. to recommend before time. (about 1 hour before) Hours of : about 3~1 hours CEMS Total demand 3.3MW (Assumption value) 30kW for community (by the simulator) 1MW(Assumption value) CEMS EVC 23 units 3~4kW 10kWh 30kWh HEMS BEMS EV 16kWh and10.5kwh The timing of EV charging is controlled. Electricity demand (kw) Assumption demand about 3MWh Community demand 30-minute balancing rule (about 80% achievement) Target demand Within ±3% Hour Surplus electric power (Peak time) Battery 100 units of EV Send a message to promote EV charge. Charge demand: 30% increase EV = Buffer of the surplus electric power

12 Case Ⅱ Kitakyushu: Case study of the CEMS ( Fuji Electricetc Co., LTD.) 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 Electric power system (Grid) 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 Yahata-higashida area Prediction of Specific supply area the area demand Yahata-higashida area (about 120 hectare = 297 acre ) Shimonoseki-City Cogeneration power plant (33MW) CEMS Total demand 21MW FC power generation Hydrogen Regional power saving station Kitakyushu-City Fukuoka-city Wind power generation HEMS BEMS Heat supply FEMS Solar heat Earth thermal for community (300kW) General household (230 houses) Factory, Hospital and Retail store, etc. (70 offices) Source of photo: City Portal of New Energy Promotion Council Japan.

13 Case Ⅱ The basic specification of the verification experiment of the using EMS p 12 :Demand Response The type of energy management : 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 Type of energy management Sector meter Visualization of electricity consumption For manager For consumers Renewable Energy (PV, etc.) Prediction of the demand (EMS) Recommend of the Indirect control Home display PC or phone, etc.. Incentive pay Storage battery Direct control Heat source equipment Load control Charge infrastructure Other Shortening of the time CEMS HEMS BEMS FEMS EVC - - Remarks There are measurement methods with CT and the tap. The effect is limited. Introduce energy saving equipment and gas equipment. Expansion of the heat supply. etc.. Prior steps for managing electricity demand Visualization of electricity consumption ( Confirmation of results ) Acceptance of the renewable energy Prediction of the demand (Setting of the target) Recommendation of to recommend 1 day before. to recommend before time. Control person's behavior + Control machines + Control time

14 The consideration of issues based on 4 area verification projects p 13 Sector Issues Expected domains in future Community (or Area) Household Business and Industrial Transportation PPS : Power Producer and Supplier How to secure funds for the incentive payment. Development of the capacity market and PPS market. Expansion of the equipment and sector for the service. How to secure funds for the incentive payment. Expansion of the household appliance and equipment for the service. Durability of energy saving behavior and visualization effect. How to secure funds for the 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 and the cloud type depending on a building scale). How to secure funds for the incentive payment. Expansion of the equipment for the service. The spread of next-generation cars. The spread of energy filling stations. The spread of traffic management systems (TMS). 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. Develop mechanism for surplus electric power generated from PV within a home. e.g. Dissemination of HEMS, PV, as a 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. 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 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 the cooperation with the traffic authorities. It is a common issue to secure funds for the 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.

15 Challenge for the spread of a smart community p 14 Needs for a smart community Affordable electricity rate Flexible energy usage within an area Local production for local consumption of energy Improvement of the local value Measures for disaster prevention Resilience Measures for environment City planning Value-added service Compact city Regional economy revitalization Improvement of administrative service etc. Internet of Things (IOT) Ripple effect in the area Satisfaction Judgment 3E+S Benefit Cost It s necessary to judge overall based on the cost benefit and an additional value. Regional attractiveness Comfort Quality of life (QOL) 3E+S : Energy Security, Economic Efficiency, Environment and Safety etc.

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