Optimal operation of V2H and stationary storage batteries in a … · 2019-11-01 · Optimal...

Optimal operation of V2H and stationary storage batteries in a massive

PV penetrated consumer group

Takaya Sadatome，Yuzuru Ueda

Department of Electrical Engineering, Tokyo University of Science, Japan

3rd E-Mobility Power System Integration Symposium, Ireland Crowne Plaza Dublin Airport

October 14, 2019

Photovoltaic Systems and Renewable Energy Integration TOKYO UNIVERSITY OF SCIENCE 2019/8/9 1

Introduction｜Recent trends in prosumers

The self-consumption of the power from residential PV by using EVs

Residential PV（Photovoltaic） • Duration of Feed-in tariff is ten years.

• The number of expired PV will increase.

Storage system • Prosumers may start shifting to

a self-consuming lifestyle.

EV（Electric Vehicle） • EV batteries are used as home power

supply (Vehicle-to-home (V2H)).

• EV’s environmental performance

depends on the power supply


System model Prosumer → 534 houses in a prosumer group

𝒅𝒅𝒕𝒕,𝒏𝒏 = 𝒍𝒍𝒕𝒕,𝒏𝒏 + 𝒔𝒔𝒕𝒕,𝒏𝒏 + 𝒆𝒆𝒕𝒕,𝒏𝒏 − 𝒑𝒑𝒕𝒕,𝒏𝒏 = 𝒈𝒈𝒕𝒕,𝒏𝒏 + 𝒐𝒐𝒕𝒕,𝒏𝒏 𝒕𝒕：time（time interval：10 min.）， 𝒏𝒏：The number of houses and batteries（1～534）

SB

PV

EVLoad

Grid

𝒔𝒔𝒕𝒕,𝒏𝒏 𝒆𝒆𝒕𝒕,𝒏𝒏𝒍𝒍𝒕𝒕,𝒏𝒏

𝒑𝒑𝒕𝒕,𝒏𝒏

𝒈𝒈𝒕𝒕,𝒏𝒏

𝒅𝒅𝒕𝒕,𝒏𝒏

One Prosumer

other houses

𝒐𝒐𝒕𝒕,𝒏𝒏

Prosumer Group


Objective

• Propose the optimal battery operation to improve the self-consumption rate

in prosumer group

• Provide EV users convenience for driving

Peer-to-Peer transaction Prosumers （Group）

Electric Power

company


Battery operation outline

Single house operation

Group operation

Quick charge of EV

Use their own home appliance and batteries

Share surplus PV energy in group with others in the same group

Keep sufficient SOC of EV for driving …

…

…

Step1

Step2

Step3


Operation in each house

Prosumers consume PV power

1. by home appliance

2. by stationary battery or EV

Battery operation’s aim is the improvement of the self-consumption rate

0 2 4 6 8 10 12 14 16 18 20 22 24

time [h]

-4

-3

-2

-1

0

1

2

3

4

pow

er

[kW

]

before afterSingle house operation

Group operation

Quick charge of EV

Ensure EV user’s convenience

• SOC constraint of EV for

driving

Net demand get close to zero • Discharge during night

• Charge more PV energy

Two basic rules Step1

Step2

Step3


EV driving pattern SOC constraint (constraint time)

M T W T F S S

50km

Distance：150km (Sat.9am-Sun.9pm)

A1：Long-distance weekend leisure

82.5% (Sat.12am-9am)

M T W T F S S

150km


41% (Sat.7am-10am)

A2：Short-distance weekend leisure

Distance：50km (Mon. Wed. Fri. Sun. 10am-5pm)

41% (7am-10am) B1：Active use

M T W T F S S

50km

Distance：5km (Mon. Wed. Fri. Sun. 1pm-5pm)

22.5% (12pm-1pm) B2：Suburban use

M T W T F S S 5km

Distance：50km (Weekdays 7am-7pm)

C1：Long-distance commuting

41% (4am-7am) M T W T F S S

50km


C2：Short-distance commuting

26.5% (7am-8am) M T W T F S S

15km


EV constraint calculation SOC constraint (constraint time)

M T W T F S S

50km



82.5% (Sat.12am-9am)

M T W T F S S

150km


41% (Sat.7am-10am)




M T W T F S S

50km



M T W T F S S 5km




50km



26.5% (7am-8am) M T W T F S S

15km

electric consumption of EV

Constraint value

Constraint time

SOC constraint = lower limit SOC of EV

+𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑝𝑝𝑝𝑝𝑝𝑝𝐸𝐸𝐸𝐸 𝐸𝐸𝐸𝐸𝑟𝑟𝑟𝑟𝐸𝐸𝐸𝐸𝐸𝐸𝑟𝑟 𝑓𝑓𝑝𝑝𝐸𝐸 𝑟𝑟𝐸𝐸𝐸𝐸𝑑𝑑𝐸𝐸𝑑𝑑𝑑𝑑 ÷ 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝐸𝐸𝑝𝑝𝑑𝑑𝑐𝑐𝑟𝑟𝑐𝑐𝑝𝑝𝐸𝐸𝐸𝐸𝑝𝑝𝑑𝑑 𝑝𝑝𝑓𝑓 𝐸𝐸𝐸𝐸

𝐶𝐶𝐶𝐶𝑝𝑝𝐶𝐶𝐸𝐸𝐸𝐸𝐸𝐸𝐶𝐶 𝑝𝑝𝑓𝑓 𝐸𝐸𝐸𝐸 𝑏𝑏𝐶𝐶𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐶𝐶

Required energy for driving ÷ electric consumption of EV

Capacity of EV battery ＋

𝐶𝐶𝑝𝑝𝑑𝑑𝑐𝑐𝐸𝐸𝐸𝐸𝐶𝐶𝐸𝐸𝑑𝑑𝐸𝐸 𝐸𝐸𝐸𝐸𝑐𝑐𝐸𝐸 =𝑆𝑆𝑆𝑆𝐶𝐶 𝐸𝐸𝑝𝑝𝑑𝑑𝑐𝑐𝐸𝐸𝐸𝐸𝐶𝐶𝐸𝐸𝑑𝑑𝐸𝐸 − 𝑆𝑆𝑆𝑆𝐶𝐶 𝑓𝑓𝑑𝑑𝑟𝑟𝑑𝑑𝑝𝑝𝑓𝑓 𝐸𝐸𝐸𝐸

𝑀𝑀𝐶𝐶𝑀𝑀 𝑝𝑝𝑟𝑟𝐸𝐸𝑝𝑝𝑟𝑟𝐸𝐸 𝑝𝑝𝑓𝑓 𝐸𝐸𝐸𝐸 𝐸𝐸𝑑𝑑𝑑𝑑𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 Constraint time =

SOC Constraint － SOC of EV

Max output of EV inverter


Operation of two batteries

SOC Constraint of EV battery for driving (DC) → One more SOC case

EV battery had four cases

(SOC Constraint)

Stationary battery had three cases

𝐷𝐷𝐶𝐶 𝐷𝐷𝐶𝐶



12 combinations of two batteries operation.

One charge / discharge pattern was assigned to each case.

five kinds of patterns were prepared for each of charge operation and discharge operation.

EV battery had four cases

(SOC Constraint)

Stationary battery had three cases




Charge operation

Discharge operation

「ES」・・・ EV battery → Stationary battery








• Stationary battery has no power • Saving EV power → EV is discharged until DC Discharge

Ⅰ and Ⅱ：EV is preferentially charged for SOC Constraint of EV for driving（DC）

Ⅲ and Ⅳ ： Stationary is first charged

Ⅳ：EV is full → Only stationary is charged

Charge


Operation in prosumer group

𝑐𝑐𝑃𝑃𝑡𝑡 = �𝑐𝑐𝑝𝑝𝑡𝑡,𝑛𝑛

𝑁𝑁

𝑛𝑛=1

Surplus power

𝑐𝑐𝐿𝐿𝑡𝑡 = �𝑐𝑐𝐸𝐸𝑡𝑡,𝑛𝑛

𝑁𝑁

𝑛𝑛=1

Shortage power

𝑐𝑐𝐷𝐷𝑡𝑡 = 𝑐𝑐𝐿𝐿𝑡𝑡 − 𝑐𝑐𝑃𝑃𝑡𝑡 Net demand

Total amount in prosumer group Group operation


Quick charge of EV

𝒔𝒔𝒑𝒑𝒕𝒕,𝟏𝟏

𝒔𝒔𝒍𝒍𝒕𝒕,𝟒𝟒

𝒔𝒔𝒍𝒍𝒕𝒕,𝟑𝟑

𝒔𝒔𝒑𝒑𝒕𝒕,𝟐𝟐

Sharing surplus PV power in prosumer group

Step1

Step2

Step3



the ratio of shortage in each house and shortage in consumer group

𝒔𝒔𝑷𝑷𝒕𝒕 × 𝒔𝒔𝒍𝒍𝒕𝒕,𝒏𝒏𝒔𝒔𝑳𝑳𝒕𝒕

proportional distribution

Distributed power consumed by 1. each electrical load. 2. each EV batteries.

𝒔𝒔𝒑𝒑𝒕𝒕,𝟏𝟏

𝒔𝒔𝒍𝒍𝒕𝒕,𝟒𝟒

𝒔𝒔𝒍𝒍𝒕𝒕,𝟑𝟑

𝒔𝒔𝒑𝒑𝒕𝒕,𝟐𝟐

Step1

Step2

Step3

Group operation


Quick charge of EV

Sharing surplus PV power in prosumer group



Quick charge

• If EV battery does not reach SOC Constraint of EV battery for

driving, this step is executed.

• Get the SOC of EV up to more than SOC Constraint of EV

battery for driving.

Charging operation by SOC Constraint of EV battery for driving

Step1

Step2

Step3


Quick charge of EV

Group operation


Evaluation｜Self-consumption

Self-consumption rate：𝑺𝑺𝑺𝑺

𝑃𝑃：Total PV generation per year

𝐺𝐺：Total power from prosumer to the distributed grid

𝑑𝑑：Number of house

𝑆𝑆𝑅𝑅 =𝑃𝑃𝑎𝑎 − 𝐺𝐺𝑎𝑎

𝑃𝑃𝑎𝑎× 100 𝑆𝑆𝑅𝑅𝑛𝑛 =

𝑃𝑃𝑛𝑛𝑎𝑎 − 𝐺𝐺𝑛𝑛𝑎𝑎

𝑃𝑃𝑛𝑛𝑎𝑎× 100

In the prosumer group In each house


Evaluation｜EV driving by PV

EV environmental performance：𝑬𝑬𝑷𝑷

𝐸𝐸𝑛𝑛𝑟𝑟𝑟𝑟𝑛𝑛：The total EV’s electric consumption during driving

𝐸𝐸𝑛𝑛𝐺𝐺：The total EV’s purchased power for driving

𝑑𝑑：Number of house

𝐸𝐸𝑃𝑃𝑛𝑛 =𝐸𝐸𝑛𝑛𝑟𝑟𝑟𝑟𝑛𝑛 − 𝐸𝐸𝑛𝑛𝐺𝐺

𝐸𝐸𝑛𝑛𝑟𝑟𝑟𝑟𝑛𝑛× 100

• The ratio of PV energy and the purchased power from the grid.

• Larger this value is, better environment performance of EV is.


Evaluation｜Self-consumption

CO2 emissions：𝑪𝑪𝑬𝑬

𝐶𝐶𝑆𝑆2𝑐𝑐： CO2 emissions， 𝑃𝑃：Electric energy， 𝐷𝐷 ：Driving distance

Content coefficient

Case Value

Generation PV power [g-CO2/kWh] 32.5

Thermal power [g-CO2/kWh] 690

Driving EV (running by the PV power) [g-CO2/kWh] Equal to PV power

EV (running by the thermal power) [g-CO2/kWh] Equal to thermal power Gasoline Vehicle (GV) [g-CO2/km] 101

• The electric consumption of EVs is 6 km/kWh (0.67 kWh/km).

𝐶𝐶𝐸𝐸 = 𝐶𝐶𝑆𝑆2𝑐𝑐 × 𝑃𝑃 𝐶𝐶𝐸𝐸 = 𝐶𝐶𝑆𝑆2𝑐𝑐 × 𝐷𝐷

Electricity Vehicle

→ →


Evaluation｜Cost

Content Unit price [JPY/kWh]

PV power generated from residential PV 𝐶𝐶𝑃𝑃 14 The power from the other prosumers 𝐶𝐶𝑂𝑂𝑟𝑟 23

The power sent to the other prosumers 𝐶𝐶𝑂𝑂𝑠𝑠 14

The power from the distributed grid 𝐶𝐶𝐺𝐺𝑟𝑟 26

The power sent to the distributed grid 𝐶𝐶𝐺𝐺𝑠𝑠 11

Power procurement cost：𝑪𝑪

𝐶𝐶 = 𝐶𝐶𝑃𝑃 ∙ 𝑃𝑃𝑛𝑛𝑎𝑎 + 𝐶𝐶𝑂𝑂𝑟𝑟 ∙ 𝑆𝑆𝑟𝑟𝑛𝑛𝑎𝑎 − 𝐶𝐶𝑂𝑂𝑠𝑠 ∙ 𝑆𝑆𝑠𝑠𝑛𝑛

𝑎𝑎 + 𝐶𝐶𝐺𝐺𝑟𝑟 ∙ 𝐺𝐺𝑟𝑟𝑛𝑛𝑎𝑎 − 𝐶𝐶𝐺𝐺𝑠𝑠 ∙ 𝐺𝐺𝑠𝑠𝑛𝑛

𝑎𝑎

• The fuel consumption of GVs is 23km/L.

• Gasoline cost is 139 JPY/L.


Used data

PV generation （Time interval : 10 min） building 534 houses in Tokyo

time August 1, 2016 〜 July 31, 2017 Electrical Load （Time interval : 10 min）

building 534 houses in Tokyo time August 1, 2016 〜 July 31, 2017

Data of the system

Specification of batteries EV Stationary battery

40 kWh Capacity 5 kWh 3 kW Output of Inverter 3 kW 90 % Efficiency 90 %


Case study

Case Content

Operation Vehicle 1 As a group EV (V2H) 2 Each house EV (V2H) 3 Each house GV

• Share PV energy in prosumer group (Case 1)

• If prosumer has EV, prosumers use V2H system (Case 1&2)

• All prosumers have stationary battery

• Don’t consider transmission loss


Result ｜ Net demand

12/09 12/10 12/11

Date

-4

-3

-2

-1

0

1

2

3

4

5

6

Pow

er

[kW

]Case 0:Net demand Case 1:Group ope. (EV)

Case 2:Individual ope. (EV) Case 3:Individual ope. (GV)

12/09 12/10 12/11

date

20

30

40

50

60

70

80

SO

C[%

]

Group(EV) Individual(EV)

Driving

Date

Driving Constraint

(EV)

The driving pattern “A-1” Constraint time (EV battery) ： Fri.12am-Sat.9am SOC Constraint (EV battery) ： 82.5%

Driving time ： Sat.9am-Sun.9pm Driving distance ： 150km

• 1st day：Sharing PV energy in group operation • 2nd day：EV was charged by power from grid

Peak power

EV was charged by more PV energy

(Fri.) (Fri.) (Fri.)



• The self-consumption rates were over 90% in more than half of prosumers when prosumers were operated as a group.

• The median value was 91.7% in case 1 and improved by 3.9% than that of case 2.

12

3

30 40 50 60 70 80 90

100

SCR [%]SCR [%]

30 40 50 60 70 80 90 100

1

2

3

Case

Case

Case

80 82 84 86 88 90 92 94 96 98

100PV charge rate of EV [%]PV charge rate of EV [%]

100 80 90 92 94 96 98 82 84 86 88

1

2 Case

Case

Case1：Group operation (EV) Case2：Individual operation (EV) Case3：Individual operation (GV)



Case Self-consumption rate [%]

EV environmental performance [%]

CO2 emissions [t-CO2]

Electricity Cost [million JPY]

Vehicle Cost [thousands JPY/month]

1 93.2 91.7 1101 2.74 9.87 2 81.0 87.8 1281 2.68 10.1 3 59.8 - 3005 7.06 235

• The self-consumption rates was improved by 1.15 times.

• EV was charged by the more PV energy in the case of group operation than the individual operation.

• CO2 emissions decreased.

• Electricity Cost increased slightly, but total electricity cost decreased.

Case1：Group operation (EV) Case2：Individual operation (EV) Case3：Individual operation (GV)


Conclusion

Acknowledgment A part of this study was supported by CREST JST (issue number: JPMJCR15K1). We would like to thank everyone who supported this study.

• Proposed battery operation method to improve the self-consumption rate in group. • SOC Constraint (EV battery) contributed to EV user convenience. • Operating prosumers as a group

Case Self-consumption rate [%]

EV driving performance [%]

CO2 emissions [t-CO2]

Electricity Cost [million JPY]

Vehicle Cost [thousands JPY/month]

1 93.2 91.7 1101 2.74 9.87 2 81.0 87.8 1281 2.68 10.1 3 59.8 - 3005 7.06 235

Table. Result Summary


Reference [1] Takaya Sadatome, Yuzuru Ueda, “Examination of improvement effect of self-consumption rate by introducing V2H system”, Grand Renewable Energy 2018 Proceedings.,

[2] National road and street traffic situation survey, “FY2015 National road and street traffic situation survey / General traffic survey / summary table”, [Online]. Available: http://www.mlit.go.jp/road/census/h27/ (in Japanese)

[3] New Energy and Industrial Technology Development Organization, ”NEDO PV-Powered Vehicle Strategy Committee Interim Report”, January 2018. [Online]. Available: https://www.nedo.go.jp/content/100885778.pdf.

[4] Ministry of the Environment, Ministry of Economy, Trade, and Industry, Japan, “Emission factor by electric power company (for the calculation of greenhouse gas emissions of specified emitters) -FY2016 results-”, 18. Dec. 2017. [Online]. Available: https://www.env.go.jp/press/files/jp/109569.pdf (in Japanese)

[5] New Energy and Industrial Technology Development Organization, ”Solar power development strategy (NEDO PV Challenges)”, September 2014.

[6] The website of the Tokyo Electric Power Company (TEPCO), Japan, “About consignment fee equivalent, etc.”, 18. Dec. 2017. [Online]. Available: http://www.tepco.co.jp/ep/private/plan2/chargelist06.html (in Japanese).


Reference [7] New Energy and Industrial Technology Development Organization, “Photovoltaic power generation roadmap for 2030”, 18. Dec. 2017. [Online]. Available: https://www.nedo.go.jp/content/100086787.pdf (in Japanese).

[8] The International Renewable Energy Agency, ”2017 renewable energy generation costs”, 2018. [Online]. Available: https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2018/Jan/IRENA_2017_Power_Costs_Summary_2018_JP_29052018.pdf?la=en&hash=BD0500DD2BE7C3779063E74F1248493D74AB98D6

[9] Eiki Arai, Yuzuru, Ueda, “Development of simple estimation model for aggregated residential load by using temperature data in multi-region,” 4th International Conference on Renewable Energy Research and Applications, #233, Italy, Nov. 22-25 (2015))

[10] S. Nishikawa and K. Kato “Demonstrative research on grid interconnection of clustered photovoltaic power generation systems” in Proc. 3rd WCPEC 2003, pp. 2652 2654.

Supplement


Near-future system

1. Effective use of PV energy by stationary battery and V2H

2. Peer-to-peer (P2P) electric power transactions

3. Prosumers are aggregated into prosumer’s group

Stationary battery

EV （V2H）

Aggregator

P2P


EV driving pattern

Pattern Type Driving time Driving

distance Constraint time

(EV battery) Driving constraint

(EV battery)

A. Weekend


Sat.9am-Sun.9pm

150km Sat,12am-9am 82.5%


Sat.10am-Sun.8pm

50km Sat,7am-10am 41%

B. Weekday/weekend (Mon., Wed., Fri., Sun.)

B1：Active use 10am-5pm 50km 7am-10am 41%

B2：Suburban use 1am-5pm 5km 12pm-1m 22.5%

C. Weekday


7am-7pm 50km 4am-7am 41%


8am-6pm 15km 7am-8am 26.5%

Table.1 EV driving pattern[1][2]

The difference in driving patterns provides the opportunity for the group's EVs to be charged with energy from residential PV.


EV constraint calculation SOC constraint (constraint time)

M T W T F S S

50km



82.5% (Sat.12am-9am)

M T W T F S S

150km


41% (Sat.7am-10am)




M T W T F S S

50km



M T W T F S S 5km




50km



26.5% (7am-8am) M T W T F S S

15km

electric consumption of EV

Constraint value

Constraint time

SOC constraint = lower limit SOC of EV

+𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑝𝑝𝑝𝑝𝑝𝑝𝐸𝐸𝐸𝐸 𝐸𝐸𝐸𝐸𝑟𝑟𝑟𝑟𝐸𝐸𝐸𝐸𝐸𝐸𝑟𝑟 𝑓𝑓𝑝𝑝𝐸𝐸 𝑟𝑟𝐸𝐸𝐸𝐸𝑑𝑑𝐸𝐸𝑑𝑑𝑑𝑑 ÷ 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝐸𝐸𝑝𝑝𝑑𝑑𝑐𝑐𝑟𝑟𝑐𝑐𝑝𝑝𝐸𝐸𝐸𝐸𝑝𝑝𝑑𝑑 𝑝𝑝𝑓𝑓 𝐸𝐸𝐸𝐸


Electric power required for driving ÷ electric consumption of EV

Capacity of EV battery ＋

𝐶𝐶𝑝𝑝𝑑𝑑𝑐𝑐𝐸𝐸𝐸𝐸𝐶𝐶𝐸𝐸𝑑𝑑𝐸𝐸 𝐸𝐸𝐸𝐸𝑐𝑐𝐸𝐸 =𝑆𝑆𝑆𝑆𝐶𝐶 𝐸𝐸𝑝𝑝𝑑𝑑𝑐𝑐𝐸𝐸𝐸𝐸𝐶𝐶𝐸𝐸𝑑𝑑𝐸𝐸 − 𝑆𝑆𝑆𝑆𝐶𝐶 𝑓𝑓𝑑𝑑𝑟𝑟𝑑𝑑𝑝𝑝𝑓𝑓 𝐸𝐸𝐸𝐸

𝑀𝑀𝐶𝐶𝑀𝑀 𝑝𝑝𝑟𝑟𝐸𝐸𝑝𝑝𝑟𝑟𝐸𝐸 𝑝𝑝𝑓𝑓 𝐸𝐸𝐸𝐸 𝐸𝐸𝑑𝑑𝑑𝑑𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 Constraint time =

SOC Constraint － SOC of EV

Max output of EV inverter


Constraint value

𝑆𝑆𝑆𝑆𝐶𝐶 𝐸𝐸𝑝𝑝𝑑𝑑𝑐𝑐𝐸𝐸𝐸𝐸𝐶𝐶𝐸𝐸𝑑𝑑𝐸𝐸 = 𝑆𝑆𝑆𝑆𝐶𝐶𝑚𝑚𝑚𝑚𝑛𝑛𝐸𝐸𝐸𝐸 +𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑝𝑝𝑝𝑝𝑝𝑝𝐸𝐸𝐸𝐸 𝐸𝐸𝐸𝐸𝑟𝑟𝑟𝑟𝐸𝐸𝐸𝐸𝐸𝐸𝑟𝑟 𝑓𝑓𝑝𝑝𝐸𝐸 𝑟𝑟𝐸𝐸𝐸𝐸𝑑𝑑𝐸𝐸𝑑𝑑𝑑𝑑 ÷ 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝐸𝐸𝑝𝑝𝑑𝑑𝑐𝑐𝑟𝑟𝑐𝑐𝑝𝑝𝐸𝐸𝐸𝐸𝑝𝑝𝑑𝑑 𝑝𝑝𝑓𝑓 𝐸𝐸𝐸𝐸


𝐶𝐶𝑝𝑝𝑑𝑑𝑐𝑐𝐸𝐸𝐸𝐸𝐶𝐶𝐸𝐸𝑑𝑑𝐸𝐸 𝐸𝐸𝐸𝐸𝑐𝑐𝐸𝐸 =𝑆𝑆𝑆𝑆𝐶𝐶 𝐸𝐸𝑝𝑝𝑑𝑑𝑐𝑐𝐸𝐸𝐸𝐸𝐶𝐶𝐸𝐸𝑑𝑑𝐸𝐸 − 𝑆𝑆𝑆𝑆𝐶𝐶 𝑝𝑝𝑓𝑓 𝐸𝐸𝐸𝐸𝑀𝑀𝐶𝐶𝑀𝑀 𝑝𝑝𝑟𝑟𝐸𝐸𝑝𝑝𝑟𝑟𝐸𝐸 𝑝𝑝𝑓𝑓 𝐸𝐸𝐸𝐸 𝐸𝐸𝑑𝑑𝑑𝑑𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸

Constraint time

EV constraint calculation


Step I Charge / Discharge pattern

Combination are 12（＝3×4） patterns

A lower limit

B middle amount

C upper limit

Ⅰ lower limit

Ⅳ upper limit

Ⅱ below constraint before driving

Ⅲ above constraint

before driving

The SOC level of the EV battery（4 cases）

The SOC level of the stationary battery（3 cases）

𝐷𝐷𝐶𝐶 𝐷𝐷𝐶𝐶 𝐷𝐷𝐶𝐶 𝐷𝐷𝐶𝐶


Charge case EV

Ⅰ Ⅱ Ⅲ Ⅳ

stationary A 1 1 4 3 B 1 1 4 3 C 2 2 2 5

Discharge case EV

Ⅰ Ⅱ Ⅲ Ⅳ

stationary A 10 10 7 7 B 8 8 9 9 C 8 8 9 9

12 combinations of two batteries operation.

One charge / discharge pattern was assigned to each case.

five kinds of patterns were prepared for each of charge operation and discharge operation.

Step II Charge / Discharge pattern


Method of using batteries are 5 combinations

Step III Charge / Discharge pattern

No use stationary battery is used

EV battery is used Both batteries is used (Stationary is prioritized)

Both batteries is used (EV is prioritized)


Charge or discharge Pattern Operation

Charge

1 EV battery → Stationary battery 2 EV battery 3 Stationary battery 4 Stationary battery → EV battery 5 No operation

discharge

6 EV battery → Stationary battery 7 EV battery 8 Stationary battery 9 Stationary battery → EV battery

10 No operation

Battery operation is above 10 kinds of operation

Step IV Charge / Discharge pattern


Step V Charge / Discharge pattern

Condition for charge and discharge patterns

Pattern EV battery Stationary battery

Charge

Dis charge



12/09 12/10 12/11

Date

-4

-3

-2

-1

0

1

2

3

4

5

6

Pow

er

[kW

]Case 0:Net demand Case 1:Group ope. (EV)

Case 2:Individual ope. (EV) Case 3:Individual ope. (GV)

12/09 12/10 12/11

date

20

30

40

50

60

70

80

SO

C[%

]

Group(EV) Individual(EV)

driving

Date

The driving pattern “A-1” Constraint time (EV battery) ： Fri.12am-Sat.9am Driving constraint (EV battery) ： 82.5%

Driving time ： Sat.9am-Sun.9pm Driving distance ： 150km

Surplus power

Case 1 Group operation

Case 2 Individual operation

Effective use of PV energy by group operation

• 1st day：Sharing PV energy in group operation • 2nd day：EV was charged by power from grid

Peak power

EV was charged by more PV energy

Date post:	03-Aug-2020
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Optimal operation of V2H and stationary storage batteries in a … · 2019-11-01 · Optimal...

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