Grid Expansion under high VRE share using Grid-featured Japan TIMES model

1. Copyright 2018 FUJITSU RESEACH INSTITUTE
Grid Expansion under high VRE share using Grid-
featured Japan TIMES model
Hiroshi Hamasaki
Senior Research Fellow
Economic Research Centre
Fujitsu Research Institute, Tokyo, Japan
IEA-ETSAP Semi-Annual Workshop, Stuttgart, Germany

2. Contents
I. Motivations
II. Methodologies: Grid Featured TIMES-based Model
III. Simulations
IV. Role of Grid Expansion
V. Node Resolution is good, but…
VI. Conclusion
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VRE: Variable Renewable Energy Share
1

3. Ｉ. Motivations
 At COP 21 in Paris, on 12 December 2015, Parties to the UNFCCC
reached a landmark agreement, the Paris Agreement, to combat climate
change.
 The Paris Agreement aims to stabilise global average temperature well
below 2.0 degree
 Japan has a long term carbon mitigation target, 80% by 2050.
 To achieve target, renewable energy, especially VRE (Variable Renewable
Energy), is expected to paly a major role.
 Existing energy infrastructure, especially electricity grid, has not been built
to absorb high VRE share.
 In this research, we have built TIMES-based Japan model which include
grid features and GIS-based renewable energy potential information to
identify the importance of grid capacity expansion and electricity storage
under high carbon mitigation constraints.
 But…node resolution simulation requires in-depth understanding on energy
issue from system point of view.
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4. II. METHODOLOGIES:
GRID-FEATURED TIMES-
BASED JAPAN MODEL
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5. electricity
Overview of JMRT
H2
Automobile
FCV
Fuel Cell
Hydrogen Station
Energy
Storage
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Refinery, Steel etc.
Brown Coal
Renewables
Renewables
Sewage
Thermal
/Nuclear
Oil Field Refinery Petrol
Station
oil hydrogen heat
gas
4

6. REs Potential
Potential of Renewables
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Offshore Wind
Onshore Wind
Geothermal
Source: FRI, based on MoE Renewable
Potential Map
Ely GridRoad
• 1km2
mesh of renewable potential
data
• Each mesh point has unique data
including investment, availability
factor.
• Reflects existing infrastructure,
electricity grid and roads.
5

7. Potential of Renewables
(Geographic Information System)
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No. Lat. Lon.
Wind
speed
AF
Capital
Cost
O&M
1
2
3
Geothermal
Offshore Wind
Onshore Wind
GIS Data is from MOE Potential Survey
Enormous onshore wind
potential
Large center of
electricity consumption
1 km
mesh
6

8. Shifts to De-centralised Energy System
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Construction
Period
10 years
Construction
Period
1 years
Capacity
1,000kWNote: size of circle represents the capacity of PowerStation
Construction
Period
20 years
Capacity
1GW
7

9. Shift to Node Level Resolutions
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47
Prefectures
351
Nodes
8
450
Grids&

10. Electricity Demand by Node
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: Node

11. Renewable Potential by Node
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: Node
10

12. Population Change from 2010 till 2050
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Source: National Land Numerical Information download service,
http://nlftp.mlit.go.jp/ksj-e/index.html
100 = 2010 Data
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: Node

13. 16 Time Slices
Spring Summer Autumn Winter
April-June
July-
September
October-
December
January-
March
R S F W
Morning 7:00-10:00 M RM SM FM WM
Day 10:00-21:00 D RD SD FD WD
Night 21:00-24:00 E RE SE FE WE
Evening 24:00-7:00 N RN SN FN WN
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14. III. Scenarios
 VRE share is 50% in 2050
 This simulations try to identify following issues.
 Role of Grid Expansion
• How much grid expansion will be needed to achieve the target?
• Impacts of no grid expansion on electricity price and geological location of VRE
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Electricity Grid Expansion Yes No
13

15. IV. ROLE OF GRID EXPANSION
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16. Wind Turbine Capacity (GW), 2050
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With Grid ExpansionWithout Grid Expansion
15
Offshore Wind
Onshore Wind

17. Electricity Price by TS and Node, 2050
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(JPY/kWh)
5 15

18. Grid Connection Capacity, 2050
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GW
17
Without Grid Expansion
With Grid Expansion

19. Utilisation of Electricity Grid in Hokkaido
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Electricity Grid
Expansion
Yes No

20. Utilisation of Electricity Grid in Hokkaido
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Electricity Grid
Expansion
Yes No

21. Utilisation of Electricity Grid in Tohoku
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Electricity Grid
Expansion
Yes No

22. Utilisation of Electricity Grid in Tohoku
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Electricity Grid
Expansion
Yes No

23. V. NODE RESOLUTION IS
GOOD
BUT…
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24. Too Complex to Understand
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*https://chiefexecutive.net/ai-
separating-artificial-from-
intelligent/
Source:*
8MB/sec
1KB/sec
Source: Thomas, 2014,
https://blogs.sas.com/content/sascom/2014/04
/25/using-virtual-reality-understand-big-data/
1/8,000

25. When you come to Japan
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Power
Station
Chart
Scenario
Map

26. V. Conclusions
 Node level resolution of model reflects reality which is
geological distribution of energy consumption and renewable
energy potential and identify the burden of grid infrastructure
under high VRE share.
 4016electrity prices in one year
 Suitable for carbon-free hydrogen and electricity grid storage project.
 And EV project e,g, charging pattern management and identify grid
restriction to popularize EV.
 To make the most use of renewable energy potential, huge
grid connections from Hokkaido to Tokyo via Tohoku is
necessary to achieve 80% carbon mitigation target by 2050.
 No grid connection expansion results in electricity price
inequality by node.
 Node level resolution simulation results require in-depth
knowledge of energy from system views. Non-expert cannot
understand the simulation results of node-level model.
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27. Copyright 2018 FUJITSU RESEACH INSTITUTE26

28. Electricity Price, 2050
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(JPY/kWh)
Note: WN (Winter-Night)
With Grid ExpansionWithout Grid Expansion
27

29. 10 Grids and Grid Connections
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0.6GW
6GW
0.9GW
0.3GW
5.57GW
1.4GW
16.66GW
5.57GW
5.57GW
2.4GW
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30. Deck.gl
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