Effective utilization system of renewable energy through the use of vehicle

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10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, China 10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, The 15th International Symposium Heatingenergy and Cooling Effective utilization system ofDistrict renewable China on

through the use of vehicle

Assessing the feasibility of using heat demand-outdoor Effective utilization system ofthe renewable energy a a Yoshikifor Tomura , the Tsuguhiko * demand forecast temperature function a long-term heat through use district ofNakagawa vehicle Okayama Prefectural University Graduate School of Information Engineering

a

c a I. Andrića,b,c*, A.Yoshiki Pinaa, P.Tomura Ferrãoaa,, Tsuguhiko J. FournierbNakagawa ., B. Lacarrière , O. Le Correc * a

IN+ Center for Innovation, aTechnology and PolicyUniversity Research Graduate - Instituto School Superior Av. Engineering Rovisco Pais 1, 1049-001 Lisbon, Portugal Okayama Prefectural of Técnico, Information b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France Abstract

Electric Vehicle (EV) and Fuel Cell Vehicle (FCV) can be used not only as transportation for people and goods

Abstract but also for storage and transportation of energy. As a method to realize this philosophy, a new system which has Abstract two storage methods has been proposed. The first method: photovoltaic power generator (PV) power is stored as

Electric in Vehicle and Fuel Cell Vehicle (FCV) can be isused not as only as transportation for Heat people and Water goods electricity the EV(EV) battery. The second method: PV power stored thermal energy in the Pump District heating networks are commonly addressed thea literature one the most effective asolutions for decreasing the but also(HPWH) for storage andconverts transportation of energy. As method to realize this philosophy, new system which has Heater which electricity into a in thermal energyas such asofthe hot water. greenhouse gas emissions from theproposed. building sector. These systems photovoltaic require highand investments whichwater are returned through the are heat two methods been Thewhich first method: power (PV) power is stored as Instorage this paper, somehas new energy systems combine PV, EVs heat generator pump heater (HPWH) sales. Dueintothe the EV changed climate conditions and building renovation policies, heat demand the future could decrease, electricity battery. The secondPVmethod: power stored asinthermal energyinin theas Heat Pump Water compared and studied. In these systems, power isPV stored as is electricity the EV battery, and thermal energy in prolonging the investment return period. Heater (HPWH) which converts electricity into a thermal energy such as AI-EVs the hot water. the HPWH. As the result, a novel energy system which combines PV, and HPWH is able to reduce CO 2 The scope ofsome this paper isenergy to assesssystems the feasibility using the heat demand – outdoor temperature function for heat demand In main this paper, whichofefficiency. combine PV, EVs and heat pump water heater (HPWH) are emissions by more thannew 75% with high economic In order to expand the new system, a novel concept forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 compared studied. In these systems, power is stored as electricity in the EV battery, and asfuels thermal energy in vehicle byand using bio-fuel such as AI-EVPV is effective. Additionally, the quantity of the renewable necessary for buildings that in both aconstruction period and typology. Three weather scenarios and (low,HPWH medium, andreduce three district the HPWH. Asvary the result, novel energy system which combines PV,ofAI-EVs is high) able to CO 2 adjustment among seasons in the new system is less than 20% present fossil fuel consumption when all renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were emissions by more than 75% withenergy. high economic efficiency. In order to expand the new system, a novel concept energy is substituted by renewable compared with results from a dynamic heat demand model, previously developed and validated by the authors. vehicle by using bio-fuel such as AI-EV is effective. Additionally, the quantity of the renewable fuels necessary for The results showed that when only weatherLtd. change is considered, the margin of error could be acceptable for some applications © 2019 The Authors. Published by Elsevier the adjustment among seasons inpower the generator new20% system is less than 20% of present fossil fuel consumption when all Keywords: Electric Vehicle; photovoltaic (theiserror in annual was lower for license all weather scenarios considered). However, after introducing renovation This an open accessdemand article under the CCthan BY-NC-ND (http://creativecommons.org/licenses/by-nc-nd/4.0/) energy is substituted by renewable energy. scenarios, the error value increased to 59.5% (depending on the weather scenarios combination considered). Peer-review under responsibility of theupscientific committee of ICAE2018 – Theand 10threnovation International Conference on Applied Energy.

The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the After adopting agreement November thethe movement of the CO2forreduction is accelerated. coupled scenarios).the TheParis values suggestedincould be usedofto2016, modify function parameters the scenarios considered,For and 1. Introduction example, Indian and ofEuropean governments improve the accuracy heat demand estimations.announced the policy to prohibit sale of gasoline and diesel vehicles Keywords: Electric Vehicle; photovoltaic power generator 1. Introduction

until 2030 ~ 2040. This policy is gradually expanding all over the world. Therefore, the battery mounted vehicle adopting thePublished Paris agreement in Ltd. November of 2016, the movement of the CO2 reduction is accelerated. For © After 2017 The Authors. by Elsevier example, Indian Europeanofgovernments announcedofthe to prohibitSymposium sale of gasoline andHeating diesel and vehicles Peer-review underand responsibility the Scientific Committee Thepolicy 15th International on District Cooling. until 2030 ~ 2040. This policy is gradually expanding all over the world. Therefore, the battery mounted vehicle * Corresponding author. Tel.:+81-866-94-2137. ; Fax: +81-866-94-2199. Keywords: Heat demand; Climate change E-mail address: Author:Forecast; [email protected], Corresponding author : [email protected] 1876-6102 Copyright © 2018 Elsevier Ltd. All rights reserved. * Corresponding author. Tel.:+81-866-94-2137. ; Fax: +81-866-94-2199. th Selection peer-review under responsibility of the scientific committeeauthor of the :10 International Conference on Applied Energy (ICAE2018). E-mailand address: Author: [email protected], Corresponding [email protected] 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. 1876-6102 Copyright © 2018 Elsevier All rights reserved.of The 15th International Symposium on District Heating and Cooling. Peer-review under responsibility of theLtd. Scientific Committee 1876-6102and © peer-review 2019 The Authors. Published of bythe Elsevier Ltd. Selection under responsibility scientific committee of the 10th International Conference on Applied Energy (ICAE2018). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 – The 10th International Conference on Applied Energy. 10.1016/j.egypro.2019.01.972

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such as EV and FCV will be more important. EV and FCV can be used not only as transportation for people and goods but also for storage and transportation of energy. As a method to realize this philosophy, a new system named PV & EV smart system which is combined with photovoltaic power generator (hereinafter referred to as PV) and EV has been proposed. [1] In the PV & EV smart system, PV power is charged directly to the EV battery, and then the charged PV power is consumed by the energy for traveling, air-conditioning and supplying to a home. This system is able to reduce CO2 emissions with high economic efficiency. In this paper, some new energy systems which combine PV, EVs and heat pump water heater (hereinafter referred to as HPWH) are compared and studied. In these systems, PV power is stored as electricity in the EV battery, as thermal energy in the HPWH. As a result, the reduction of CO 2 emission and the economy in each system is reported. 2. Outline of the energy system studied 2.1. Future energy system The conventional energy system and the future energy system are shown in Figure 1. In the conventional energy system, the amount of energy supply is adjusted according to the consumption of electricity and fuel. Therefore, consumers have no choice to use energy efficiently. On the other hand, in the future energy system, Renewable electricity which generated at various places can be stored, transported and supplied by using the EV battery. Therefore, the energy flows become two-way. In this process, load fluctuations of supply and demand can be adjusted. So, consumers are also suppliers. They are able to manage the system as integrated system with energy supply and consumption. 2.2. Method of adjusting the energy supply and demand In order to adjust the load fluctuation of renewable energy such as PV and wind power, it is important to store the renewable energy to meet with demand. Therefore, two storage methods have been considered. The methods are shown in the Figure 2. The first method, PV power is stored as electricity in the EV battery. The second method, PV power is stored as thermal energy in the HPWH which converts electricity into the hot water. In terms of adjusting the load fluctuation, supply and demand differences between electricity consumption and PV hour by hour are adjusted by a battery, and the hot water consumption which is increased at the specific time such as morning and evening are adjusted by the surplus PV electricity. These operations adjust the home supply and demand during a short period or night and day time. Conventional system

Renewable energy

Gas station

Supply Factory

Future energy system

Gasoline car Factory

New energy flow Home

Home

Night

EV

Electric power Public facilities

EV

Electric power

Public facilities Renewable energy

Figure 1 Future energy system [2]

Noon

PV Power Electricty Hot Water Heating

-StorageRemain Electricity ・・・Battery

Noon

Night

-StorageConvert to Heat ・・・Heat Pump Water Heater

Figure 2 Adjustment methods for generated energy and consumption

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In addition, it is necessary to consider the use of the EV battery, because it can be used more effectively than the stationary type battery. However, there is a problem that the cruising distance of EV is short because a battery is heavy with a high price. Therefore, in this study, we used AI - EV (Air-conditioner Integrated Electric Vehicle) which can use the battery more effectively. 2.3. AI-EV(Air-conditioner Integrated Electric Vehicle) A simple structure and operation image of AI-EV is shown in Figure 3 and 4 each. When using the airconditioner, the EVs cruising range is shortened because of the EV battery supplies electric power to the airconditioner. Therefore, the AI-EV uses a small engine which is operated with constant rotation for the airconditioner compressor load. The surplus engine power which is occurred by a changing air-conditioning load is used for power generation. Therefore, AI-EV is able to use battery more effectively. [3] [4] Engine Load

Fuel Electric Motor

Air Conditioner

Compressor

Battery

Generator

Engine Power [kW]

Small Engine

Surplus Power ⇒Power Generation

Required Compressor Power

Air-Conditioner Compressor Load

Time [sec] Figure 4 Operation image of AI-EV

Figure 3 Structure of AI-EV 2.4. Performance evaluation as a vehicle

Air-Conditioner Consumption Cruising Consumption 5 0

20

Cruising

Parking

Cruising

15 10

Battery Limit

5 0

1

2 2.5 1

0 50 100 150

120

2 3 4 Time [h]

5

1

Distance [km]

Figure 5 Cruising distance limit of EV

2

3

Battery Remaining Capacity Charge Discharge [kWh] [kWh] [kWh]

Battery Remaining Capacity Charge Discharge [kWh] [kWh] [kWh]

As the performances of EV and AI-EV, the difference of cruising distance limit is shown in Figure 5 and 6 each. In Figure 5 and 6, EV and AI-EV are assumed to be used for leisure. Additionally, both average running speeds are 50 km/h. Running hours are 3 hour and parking hours for sightseeing are 5 hour.

Air-Conditioner Consumption Cruising Consumption Charging

5 0 20

Cruising

Parking

Cruising

15

10 5 0

1

2

3

0 50 100 150

1

2 3 4 5 1 2 2.9 Time [h] 150 200 250 300

Distance [km]

290

Figure 6 Cruising distance limit of AI-EV

From Figure 5, the cruising distance limit of the EV is about 120 km according to a battery capacity. On the other hand, from Figure 6, the AI-EV can drive about 300 km with the same battery capacity because AI-EV can generate electricity during the parking and charge on-vehicle battery. [4]

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2.5. Novel energy system A studied energy system is shown in Figure 7. In this system, there are using two battery mounted vehicles. Renewable energy

Power System Home

ESPS11 E SPV11 η1 ESPS13

ESPVG1 ESPV13

AI-EV Daily use

HPWH η2 Ec1

University ESPVG2 η1

ESPS21

ESPV21

ESPV22 Ec2 , Ec3 Commuting

AI-EV

Electricity

PV2

ESPV12

Hc3

η3 η4

EPVST

PV1

Hc1 Hc2 ESPS12

Heat

ESG

AI-EV AI-EV

η2 ESPS22

Figure 7 Image of new energy system One of the vehicles is for a commuting, and the other is for a daily use. PV panel are installed at the home and car parking space of the workplace. Both vehicles are charged from PV basically. However they are charged from the conventional power system while PV cannot generate electricity during night or rainy days. When PV power cannot charge the battery mounted on the vehicles because it’s full, the surplus PV power is consumed by the HPWH. Generated hot water is stored in a tank and used in the morning, evening and night. 3. Evaluation method The energy balance of each system is calculated based on time series data every hour for one year. In addition, the data on energy generation and consumption, atmospheric temperature and water temperature is the actual value for every hour in 2014. [5] 3.1. Mathematical simulation method In this system, it is important to adjust the energy supply and demand by using the EV battery and HPWH. Therefore, the energy balance of the EV battery and HPWH are calculated using Eq. (1) -(7). These equations are the sequential calculation of t=1 to 8760 hour which means through the year. [6] 3

2

𝑘𝑘=1

𝑖𝑖=1

𝐸𝐸𝐵𝐵 (𝑡𝑡 + 1) = 𝐸𝐸𝐵𝐵 (𝑡𝑡) − ∑ 𝐸𝐸𝐶𝐶 𝑘𝑘 (𝑡𝑡) + ∑ 𝐸𝐸𝑆𝑆𝑆𝑆𝑆𝑆 𝑖𝑖𝑖𝑖=2 (𝑡𝑡) + 𝐸𝐸𝑆𝑆𝑆𝑆 (𝑡𝑡) 𝐼𝐼𝐼𝐼

𝐸𝐸𝐵𝐵 (𝑡𝑡 + 1) < 𝐸𝐸𝐵𝐵𝐵𝐵 (𝑡𝑡 + 1)

𝑡𝑡ℎ𝑒𝑒𝑒𝑒

< The heat balance of the HPWH tank> 3

𝐸𝐸𝑆𝑆𝑆𝑆𝑆𝑆 𝑖𝑖𝑖𝑖=2 (t) =

𝐸𝐸𝐵𝐵𝐵𝐵 (𝑡𝑡 + 1) − 𝐸𝐸𝐵𝐵 (𝑡𝑡 + 1) 𝜂𝜂2

𝐻𝐻𝐵𝐵 (𝑡𝑡 + 1) = 𝐻𝐻𝐵𝐵 (𝑡𝑡) − ∑ 𝐻𝐻𝐻𝐻𝑙𝑙 (𝑡𝑡) + 𝐶𝐶𝐶𝐶𝐶𝐶(𝑡𝑡) ∙ 𝜂𝜂1 ∙ 𝐸𝐸𝑆𝑆𝑆𝑆𝑆𝑆 𝑖𝑖=1𝑗𝑗=3 (𝑡𝑡)

𝐼𝐼𝐼𝐼

𝑙𝑙=1

𝐻𝐻𝐵𝐵 (𝑡𝑡 + 1) < 𝐻𝐻𝐵𝐵𝐵𝐵 (𝑡𝑡 + 1)

𝑡𝑡ℎ𝑒𝑒𝑒𝑒

3

𝐸𝐸𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑖𝑖 (𝑡𝑡) = ∑ 𝐸𝐸𝑆𝑆𝑆𝑆𝑆𝑆 𝑖𝑖𝑖𝑖 (𝑡𝑡) + 𝐸𝐸𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑖𝑖 (𝑡𝑡) 𝑗𝑗=1

(1)

(2)

𝐸𝐸𝑆𝑆𝑆𝑆𝑆𝑆 𝑖𝑖=1𝑗𝑗=3 (t) = 𝐸𝐸𝑆𝑆𝑆𝑆

(3)

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5

𝐸𝐸𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 (𝑡𝑡) = ∑ 𝐸𝐸𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑖𝑖 (𝑡𝑡)

(4)

𝐸𝐸𝑇𝑇 𝑖𝑖 (𝑡𝑡) = 𝐸𝐸𝐷𝐷 𝑖𝑖 (𝑡𝑡) − 𝜂𝜂1 ∙ 𝐸𝐸𝑆𝑆𝑆𝑆𝑆𝑆 𝑖𝑖𝑖𝑖=1 (𝑡𝑡) − 𝐸𝐸𝑆𝑆𝑆𝑆𝑆𝑆 𝑖𝑖𝑖𝑖=2 (𝑡𝑡) − 𝜂𝜂1 ∙ 𝐸𝐸𝑆𝑆𝑆𝑆𝑆𝑆 𝑖𝑖𝑖𝑖=3 (𝑡𝑡) − 𝜂𝜂3 ∙ 𝜂𝜂4 ∙ 𝐸𝐸𝐶𝐶 𝑘𝑘=1 (𝑡𝑡)

(5)

𝑖𝑖=1



𝐼𝐼𝐼𝐼

𝐸𝐸𝑇𝑇 𝑖𝑖 > 0

𝑡𝑡ℎ𝑒𝑒𝑒𝑒



𝐸𝐸𝑆𝑆𝑆𝑆𝑆𝑆 𝑖𝑖 (𝑡𝑡) = 𝐸𝐸𝑇𝑇 𝑖𝑖 (𝑡𝑡)

(6)

0.2𝐸𝐸𝐵𝐵𝐵𝐵𝐵𝐵 ≦ 𝐸𝐸𝐵𝐵 (𝑡𝑡) ≦ 𝐸𝐸𝐵𝐵𝐵𝐵𝐵𝐵

(7)

𝐻𝐻𝐵𝐵𝐵𝐵 (𝑡𝑡) ≦ 𝐻𝐻𝐵𝐵 (𝑡𝑡) ≦ 𝐻𝐻𝐵𝐵𝐵𝐵𝐵𝐵

Where， t:time[h](t=0-8760), i:place of PV [-] (i=1:Home, 2:University), j:destination of PV power supply [-] (j=1:place of PV, 2:vehicle, 3:HPWH), ESPVij:electric power supply from PV(i) to j [kWh], ESPS i:electric power supply from Power System(i) [kWh], ESPSij:electric power supply from Power System(i) to j [kWh], ESG:Generated engine power by AI-EV [kWh], Ecl:electric power consumption by l [kWh] (l=1: vehicle⇒ Home, 2: driving, 3: air-conditioner), ESH:rated power output of HPWH [kWh], Hcm:Heat consumption by m [MJ] (m=1: hot water supply, 2: floor heating, 3: heat radiation from tank), E B:electricic power in the battery [kWh] , EBca:battery capacity [kWh], EBN:necessary amount of electric power in battery[MJ], HB:the hot water in tank [MJ], HBca:heat pump tank capacity [MJ], HBN:necessary amount of heat in tank [MJ], COP:electricity ⇔heat conversion efficiency [-], ESPVGi:amount of PV power generatrion [kWh] , EPVSTi:amount of PV(i) power surplus[kWh], EPVSTi:amount of total PV power surplus[kWh], ETi:amount of electricity shortage [kWh], EDi:electricity demand of i [kWh], η1 - η9：As shown in Table 2. 3.2. Performances of each equipment and efficiency In calculated conditions, the performances of PV, EV, AI-EV and HPWH are shown in Table 1. The workplace is Okayama Prefectural University, the commuting distance is 28km/day. In all apparatuses, hourly generated and consumed energy are calculated based on the actual data continuously. For example, the HPWH boils hot water by using the heat pump cycle according to the supply water temperature and air temperature. So, these temperature changes are considered too. The conversion efficiencies which are obtained by the experiments are shown in Table 2. Then, CO2 emission coefficients are following: Gasoline 2.62 kg-CO2/ℓ, Electricity 0.579 kg-CO2/kWh, LPG 3.48 kg-CO2/kg and LNG 2.70 kg-CO2/kg [7] Table 1 Performances of equipment [8] 【Photovoltaic Power Generation】 Maximum power 240 W Output per unit area 190 W/m2 【EV and AI-EV】 EV 13 / 40 Battery capacity kWh Commuting / Daily use AI-EV 13 / 21 Power consumption rate 9.1 km/kWh Displacement of engine (AI-EV) 120 cc Fuel of engine (AI-EV) LNG 【Heat Pump Water Heater】 Heating capacity 6 kW Boiling-up temperature 65℃ Storage tank capacity 460 ℓ

Table 2 Performances of efficiency [9] 【Conversion Efficiency】 Unit：% η1 : PSC Execution Efficiency 88 η2 : AC/DC Converter Efficiency 90 94 η3 : DC/DC Converter Efficiency 94 η4 : From Charge to Discharge Efficiency η5 : Motor Efficiency 99 η6 : Power Transmission Efficiency 95 95 η7 : : Power Split Efficiency 85 η8 : DC/AC Converter Efficiency η9 : Power Generation Efficiency 90

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3.3. Calculated condition The four different systems shown in Table 3 were compared with the conventional system using gasoline vehicles by CO2 emissions and economic efficiency. Table 3 Calculated cases with PV power generation capacity PV (University PV EV AI-EV HP water heater

[m2]

/ Home PV

[m2])

Case1 Case2 Case3 Case4 with (12.5/4.5) with (12.5/15.5) with (12.5/28.5) with (12.5/27.5) with without with without without without without with without with with with

The PV power generation capacity according to a panel area is decided by the rate of the generated surplus PV power (=surplus PV power/all of the generated PV power)≦3%, in order to achieve effective utilization of PV power. Therefore, as shown in Table 3, PV panel area is different with each case. The economic efficiency is evaluated by IRR (Internal Rate of Return) which is calculated by the market prices in 2014 in Japan as shown in Table 4. Table 4 Calculated conditions for IRR 【Apparatus Unit Price】 PV & Primary Cost 250 thousand yen/kW DC/AC Inverter 40 thousand yen/kW Charging Control Unit 200 thousand yen/unit Difference of Vehicle Price 500 thousand yen/unit Difference of Water Heater Price 450 thousand yen/unit Difference of Cooker Price 100 thousand yen/unit

【Energy Unit Price】 Electricity (University Rates) 20.0 yen/kWh Electricity (Home Rates) 27.5 yen/kWh Gasoline 160.0 yen/ℓ Kerosene 100.0 yen/ℓ LPG 360.0 yen/kg LNG 220.0 yen/kg

4. Result CO2 emissions of each case in comparison with a conventional system are shown in Figure 8.

CO2 emissions [t-CO2/year]

IRR [%] 8 6

4 2 0

Kerosene 0.4

5.4

LPG 1.2 Gasoline 1.7

Δ48%

1.8 Electricity

LNG

2.9 Conventional system (Base)

2.7 Δ19%

3.9 0.3

7.3 Δ75%

Δ79%

1.7 1.1

3.0 PV&EV (Case1)

1.8 2.7 PV&HPWH (Case2)

0.3

0.5

1.5 1.3 PV&EV&HPWH PV&AI-EV&HPWH (Case3) (Case4)

Figure 8 Comparison of CO2 emissions Case1 is able to reduce CO2 emissions by 48% in comparison with the base system. Case2 is able to reduce CO2 emissions by 19% in comparison with the base system. Case3 is the system which combined Case2 with Case1. However, CO2 reduction effect is 79% that are bigger than 67% which added up each effect of Csae1 and Csae2. This is because ability for adjustment of the supply and demand became big as a result that EV and HPWH varying

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in a consumption form of the energy are using together. Case4 reduce CO2 emissions by 75% because AI-EV in Case4 uses a fuel which rises CO2 emissions by 4%. If AI-EV uses renewable fuel such as bio-fuel, the reduction rate of CO2 emissions is the same as Case3. On the other hand, in regard to IRR, IRR of Case4 is 7.3% of approximately 2 times of Case3. 5. Consideration

Demand [kWh/month]

Supply [kWh/month]

The reason that CO2 can greatly reduce in Case3 and Case4 is considered. The hourly energy supply and demand balances of May and December when adjusting by using AI-EV and HPWH are shown in Figure 9 and 10 each. Figure 10 Hourly energy balance at home in December. 0 ：AI-EV→Home ：PV→Home Storage ：PV→AI-EV ：PV→HPWH Tank Supply ：Power System ：AI-EV Generated Power ：HPWH Tank → Hot Water Losses ：Surplus 200 By using 150 HP Tank By using 100 AI-EV Battery 50 0 -50 -100 -150 -200

Demand ：Home Power ：Hot Water ：AI-EV Traveling

0

3

6

9 12 Time [h]

15

18

21

24

Figure 9 Hourly energy balance at home in May ：PV→Home Storage ：AI-EV→Home ：Power System ：HPWH Tank → Hot Water Losses

Supply

Supply [kWh/month]

250 200

：PV→AI-EV ：PV→HPWH Tank ：AI-EV Generated Power ：Surplus

By using Power system

150 100

50

Demand [kWh/month]

0 -50

-100

Demand ：Home Power ：Hot Water ：AI-EV Traveling

-150 -200

-250

0

3

6

9 12 Time [h]

15

18

21

24

Figure 10 Hourly energy balance at home in December In May, the amount of generated PV electricity is the most in a year. From Figure 9, it is clarified that generated

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PV electricity in a daytime can be adjusted to hot water and electricity demand at night by using EV batteries and the hot water storage tank. As the reason for that, EV battery can use as a stationary battery because the average parking time of privately-owned car is above 95% of a year. On the other hand, in December, the amount of generated PV electricity is the lowest in a year. From Figure 10, it is clarified that electricity supplied from power system increases much because the quantity of generated PV power is lower than the consumption. Therefore, in order to further reduce CO2 emissions, it is necessary to adjust energy supply and demand among seasons. The quantity of the renewable fuels necessary for the adjustment among seasons in Case4 is less than 20% of present consumption when all energy is substituted by renewable energy. Regarding this point, some countries that E10 (a fuel mixture of 10% anhydrous ethanol and 90% gasoline) has been already achieved such as USA can be possible to actualize economically. 6. Conclusion In this paper, some new energy systems which combine PV, EVs and Heat Pump Water Heater (HPWH) are compared and studied. In these systems, PV power is stored as electricity in the EV battery and as thermal energy in the HPWH. The results are as follows: ・In order to use renewable energy effectively, two storage methods which are EV battery and the hot water are effective to adjust the generated energy and consumption. ・A novel new system which is combined PV, AI-EV and HPWH, is able to reduce CO 2 emissions by more than 75% with high economic efficiency: IRR (Internal Rate of Return) =7.3% ・The quantity of the renewable fuels necessary for the adjustment among seasons in the new system is less than 20% of present fossil fuel consumption when all energy is substituted by renewable energy. ・In order to expand the new system, a new concept vehicle by using bio-fuel such as AI-EV is effective. 7. Reference [1] H. Chisaka, T. Nakagawa, “A NOVEL SYSTEM INTEGRATED WITH SOLAR POWER, ADVANCED E LECTRIC VEHICLE AND HOME HEAT PUMPS”, Proceedings of the ASME 2016 Power and Energy Conference, Power Energy2016, pp.26-30, (2016). [2] N. Kose, T. Nakagawa, “Effective Method of Renewable Energy by Using Electric Vehicle and Evaluation by the HEX Model”, Journal of Japan Society of energy and Resources, Vol.34, No.4, pp.18-26, (2013). [3] T. Nakagawa, Y. Notoji, S. shibata, “A Novel Concept of Air-conditioner-Integrated Electric Vehicle for the Future Smart Community”, Heat Transfer Engineering, Vol. 37, No. 17, pp.1498-1506, (2016). [4]T. Hirose, T. Nakagawa, “Evaluation of Air-conditioner and engine generator integrated Electric Vehicle”, Transa ctions of Automotive Engineering of Japan, Vol.43, No.3, pp.679-685, (2017). [5]Japan Meteorological Agency, “Climate Statistics”, (2014), http://www.data.jma.go.jp/obd/stats/etrn/index.php [6]T. Nakagawa, H. Chisaka, Y. Notoji, “A novel SMART energy system for using biomass energy efficiency”, Rene wable Energy, POWER2013-98137, Vol.116, pp.492-499, (2018). [7]Ministry of the Environment, “Publication of electric power companies-specific emission factors at 2014”, (201 5), http://www.env.go.jp/press/101746.html [8] S. Shibata, T. Nakagawa, “Mathematical Model of Electric Vehicle Power Consumption for Traveling and Air-conditioning”, Journal of Energy and Power Engineering, Vol.9, pp.269-275, (2015). [9] T. Nakagawa, Y. Mitsumoto, “Evaluation of Two-Way Energy System Through the Use of PV and EV”, Jo urnal of the Japan Institute of Energy, Vol. 93, No. 8, pp.716-723, (2014).