Analysis of the role of energy storages in Belgium and Netherlands with TIMES

1. Energy Storage Mapping And Planning
Modelling Work Package
Vito/EnergyVille
Frank Meinke-Hubeny
Larissa Pupo Nogueira de Oliveira
Jan Duerinck
IER Stuttgart
Markus Blesl
Julia Welsch
ETSAP Workshop
CIEMAT – Madrid
17.11.2016

2. Overview and Background ESTMAP project
Frank Meinke-Hubeny, Vito/EnergyVille
Evaluation of the role of energy storages in Europe with TIMES PanEU
Markus Blesl and Julia Welsch, IER University of Stuttgart
Analysis of the role of energy storages in Germany with TIMES PanEU
Julia Welsch and Markus Blesl, IER University of Stuttgart
Analysis of the role of energy storages in Belgium and Netherlands with TIMES
Larissa P. N. de Oliveira and Jan Duerinck; Vito/EnergyVille
Overview of Powerfys Model results (Ecofys)
Frank Meinke-Hubeny, Vito/EnergyVille
Discussion

3. GRAND ENERGY CHALLENGES
• Establish a clean, low carbon energy system based on renewable resources
• Ensure continuation of stable and high quality energy services
• Keep energy generation cost efficient and affordable for all EU citizens

4. ENERGY STORAGE IS A KEY ENABLER
• Flexibility for an energy system in which electricity generation increases
• Mitigation of consequences from increasing share of intermittent energy
sources
• Solutions for declining base load and shift to decentralized generation

5. Energy Storage Mapping And Planning
Key knowledge and information on Europe’s energy storage potential
Spatial energy storage database for electricity, gas and heat technologies
Case demonstration of European energy systems analysis and planning
Contribute to Energy Storage development

7. TANKS
LAKES
RESERVOIRS
SALT
HOST ROCK
AQUIFERS
MODULAR
ESTMAP DATA SCOPE
PUMPED
HYDRO STORAGE
NATURAL GAS STORAGE
HYDROGEN STORAGE
HYDROGEN STORAGE
NATURAL GAS STORAGE
COMPRESSED AIR ENERGY STORAGE
NATURAL GAS STORAGE
THERMAL ENERGY STORAGE
COMPRESSED AIR ENERGY STORAGE
UNDERGROUND PUMPED HYDRO STORAGE
BATTERIES
FLYWHEEL
CAPACITATORS
LNG
HYDROGEN STORAGE
UNDERGROUND
THERMAL ENERGY STORAGE
Reservoirs
Technologies
Subsurface / Above ground
Existing / Potential
Electricity, Gas, Heat

8. Subsurface data collection

9. Above ground data collection (PHS)

10. Geographical energy storage database
> 4200 potential and proven natural energy storage capacities
> 700 planned and developed energy storage facilities
Number of potential
storage sites

11. Schematic overview of
interrelations in
Modelling WP

12. Flow of information for energy systems analysis and planning
DBase
ESTMAP
Geographical
database Salt
Formation
depth
height
area
Select potentially suitable
reservoirs for analysis input
Storage site and reservoirs
database
reservoir
characteristics
Salt
Formation
Define notional storage
facilities per technology
Site characterization
Feasibility determination
Reservoir properties
Generic technical design
parameters
Site-specific performance
parameters
Analysis input deck
Future potential capacities
+
Proven capacities in
existing facilities
intake
discharge
efficiency
capex
opex
etc.

13. GIS, TIMES and PowerFys have been combined to
demonstrate potential analysis on ESTMAP database
Database GIS mapping TIMES model PowerFys model
Description
• Compile a
database with
existing and future
potential energy
storage
• Integrate
contributions from
geological and
technical
institutes and
open source
information
• EU
• Calculate
connection costs
for future storage
facilities
• Develop storage
maps depicting
analysis results,
after TIMES and
PowerFys model
runs
TIMES PanEU:
• Optimize
configuration of
storage sites &
power plants
• Time resolution of
day, night and
peak time slices
• EU-28, NO, CH
• 2010 – 2050
TIMES regional:
• Time resolution of
280 (GER) and
60 (BE & NL) time
slices
• DE, BE & NL
• Optimize
operation of
energy storage
and power
generation assets
• Optimize storage
use
• Assess cross-
border electricity
flow & congestion
• Calculate marginal
energy costs
• Hourly resolution
• DE, BE and NL
• 2050
Outcomes
• Storage locations
• Storage
specifications
• Storage connection
costs
• Optimal
configuration of
storage sites and
power plants
• Hourly storage use
• Generation mix
• Marginal costs

14. Scenario Definitions
2030 2050
Combined binding
emissions target
(2030)
Renewable target
2030
Combined emissions
target (2050)
Renewable target
2050*
% vs. 1990
% gross final energy
consumption
% vs. 1990
% gross final energy
consumption
EU -40% 27% -80% 75%*
Sources: (COM, 2013 (169)) and (COM, (2011) 885)
Note: * based on 'High Renewable Energy Sources (RES)' scenario, Roadmap 2050
Baseline Scenario
PV Scenario
• Predefined PV generation capacity : 50% higher compared to the baseline results in 2050
BattCost Scenario
Baseline Scenario BattCost Scenario
Investment costs Investment costs
2010 2050 2010 2050
Battery Lithium Ion Input 100
€
𝑘𝑘
30
€
𝑘𝑘
100
€
𝑘𝑘
60
€
𝑘𝑘
Battery Lithium Ion Storage 752
€
𝑘𝑘𝑘
85
€
𝑘𝑘𝑘
752
€
𝑘𝑘𝑘
170
€
𝑘𝑘𝑘
Battery Lithium Ion Output 100
€
𝑘𝑘
30
€
𝑘𝑘
100
€
𝑘𝑘
60
€
𝑘𝑘
General Assumption
• Spirit of a true ‘Energy Union’ till 2050
• Guidance from EU policy H2020, Roadmaps 2030 and 2050

15. Further information about ESTMAP …
• Vito, IER
• Project Flyer
• Website (http://estmap.eu)
Frank Meinke-Hubeny frank.meinke-hubeny@vito.be
Larissa Pupo Nogueira de Oliveira larissa.oliveira@vito.be
Jan Duerinck jan.duerinck@vito.be

16. Overview and Background ESTMAP project
Frank Meinke-Hubeny, Vito/EnergyVille
Evaluation of the role of energy storages in Europe with TIMES PanEU
Markus Blesl and Julia Welsch, IER University of Stuttgart
Analysis of the role of energy storages in Germany with TIMES PanEU
Julia Welsch and Markus Blesl, IER University of Stuttgart
Analysis of the role of energy storages in Belgium and Netherlands with TIMES
Larissa P. N. de Oliveira and Jan Duerinck; Vito/EnergyVille
Overview of Powerfys Model results (Ecofys)
Frank Meinke-Hubeny, Vito/EnergyVille
Discussion

17. Belgium and Netherlands TIMES Model -
Methodology: Temporal resolution
Jan Duerinck

18. Belgium and Netherlands TIMES Model -
Methodology and Results
Larissa Pupo Nogueira de Oliveira

19. Methodology
Main Structure for Storage Processes
BE & NL: disaggregated approach DE & PanEU: aggregated approach~FI_Process
Sets Region TechName TechDesc Tact Tcap Tslvl
*Process Set Membership
Region
Name
Technology
Name Technology Description
Activity
Unit
Capacity
Unit
TimeSlice
level of
Process
Activity
.ELE.CEN.TCH.STGTSS. BE STGSPH1L1 FFAC_PHS_1LAKE_001 - Storage PJa PJa DAYNITE
.ELE.CEN.TCH.STGTSS. NL STGSLCSA245 FFAC_LCCAES_SALT_245 - Storage PJa PJa DAYNITE
.ELE.CEN.TCH.STGTSS. NL STGSLCSA246 FFAC_LCCAES_SALT_246 - Storage PJa PJa DAYNITE
.ELE.CEN.TCH.STGTSS. NL STGSLCSA247 FFAC_LCCAES_SALT_247 - Storage PJa PJa DAYNITE
.ELE.CEN.TCH.STGTSS. NL STGSLCSA248 FFAC_LCCAES_SALT_248 - Storage PJa PJa DAYNITE
.ELE.CEN.TCH.STGTSS. NL STGSLCSA249 FFAC_LCCAES_SALT_249 - Storage PJa PJa DAYNITE
…
.PRE.CEN.TCH.STGTSS. NL STGSUGRE307 FFAC_UGS_RES_307 - Storage PJa PJa DAYNITE
.PRE.CEN.TCH.STGTSS. NL STGSUGRE308 FFAC_UGS_RES_308 - Storage PJa PJa DAYNITE
.PRE.CEN.TCH.STGTSS. NL STGSUGRE309 FFAC_UGS_RES_309 - Storage PJa PJa DAYNITE
.PRE.CEN.TCH.STGTSS. NL STGSUGRE310 FFAC_UGS_RES_310 - Storage PJa PJa DAYNITE
.PRE.CEN.TCH.STGTSS. NL STGSUGRE311 FFAC_UGS_RES_311 - Storage PJa PJa DAYNITE
…
.PRE.CEN.TCH.STGTSS. NL STGSUGSA245 FFAC_UGS_SALT_245 - Storage PJa PJa DAYNITE
.PRE.CEN.TCH.STGTSS. NL STGSUGSA246 FFAC_UGS_SALT_246 - Storage PJa PJa DAYNITE
.PRE.CEN.TCH.STGTSS. NL STGSUGSA247 FFAC_UGS_SALT_247 - Storage PJa PJa DAYNITE
.PRE.CEN.TCH.STGTSS. NL STGSUGSA248 FFAC_UGS_SALT_248 - Storage PJa PJa DAYNITE
…
.PRE.CEN.TCH.STGTSS. NL STGSH2SA245 FFAC_H2_SALT_245 - Storage PJa PJa DAYNITE
.PRE.CEN.TCH.STGTSS. NL STGSH2SA246 FFAC_H2_SALT_246 - Storage PJa PJa DAYNITE
.PRE.CEN.TCH.STGTSS. NL STGSH2SA247 FFAC_H2_SALT_247 - Storage PJa PJa DAYNITE
.PRE.CEN.TCH.STGTSS. NL STGSH2SA248 FFAC_H2_SALT_248 - Storage PJa PJa DAYNITE
.PRE.CEN.TCH.STGTSS. NL STGSH2SA249 FFAC_H2_SALT_249 - Storage PJa PJa DAYNITE
.PRE.CEN.TCH.STGTSS. NL STGSH2SA250 FFAC_H2_SALT_250 - Storage PJa PJa DAYNITE
~FI_Process
Sets TechName TechDesc Tact Tcap Tslvl
.ELE.CEN.TCH.STGTSS. EUSTGPSN01 Pump Storage PJ PJa Daynite
.ELE.CEN.TCH.STGTSS. EUSTGPSN01_S Pump Storage Seasonal PJ PJa Season
.ELE.CEN.TCH.STGTSS. EUSTGCAESADIA01 CAES adiaba (salt caverns) PJ PJa Daynite
.ELE.CEN.TCH.STGTSS. EUSTGCAESDIA01 CAES diabat (salt caverns) PJ PJa Daynite
.ELE.CEN.TCH.STGTSS. EUSTGCAESADIA01_O CAES adiabat (tanks) PJ GW Daynite
-Database can be used with both approaches!
- In addition to the exercise of evaluating
regions with different dimensions and
potentials.

20. Methodology
Storage Potential Database
Pump Storage – one reservoir Pump Storage – two reservoir
Country
Potential
[GWh]
Connecting
Cost �
€
𝒌𝒌𝒌𝒌
�
Country
Potential
[GWh]
Connecting
Cost �
€
𝒌𝒌𝒌𝒌
�
AT 409 6,2 IE 30 5,9
BE 0 - IT 1.626 6,7
BG 378 6,9 LT 0 -
CH 0 - LU 0 -
CY 51 5,7 LV 0 -
CZ 183 6,5 MT 0 -
DE 297 6 NL 0 -
DK 0 - NO 6.616 23,5
EE 0 - PL 47 5
ES 0 - PT 1.229 4,4
FI 104 8 RO 0 -
FR 1.913 5,2 SE 1.098 11,6
GR 288 11,6 SI 18 5,6
HR 291 7,5 SK 0 -
HU 3 5,5 UK 1.702 8,4
Country
Potential
[GWh]
Connecting
Cost �
€
𝒌𝒌𝒌𝒌
�
Country
Potential
[GWh]
Connecting
Cost �
€
𝒌𝒌𝒌𝒌
�
AT 16 6,2 IE 0 -
BE 0 - IT 86 7,7
BG 0 - LT 0 -
CH 0 - LU 0 -
CY 0 - LV 0 -
CZ 3 6 MT 0 -
DE 5 15,2 NL 0 -
DK 0 - NO 212 11,7
EE 0 - PL 0 -
ES 0 - PT 28 5,6
FI 0 - RO 0 -
FR 49 2,9 SE 0 -
GR 0 - SI 0 -
HR 0 - SK 0 -
HU 0 - UK 85 4

21. Methodology
Storage Potential Database
Compressed Air Natural Gas
Country
Potential
[GWh]
Connecting
Cost �
€
𝒌𝒌𝒌𝒌
�
Country
Potential
[GWh]
Connecting
Cost �
€
𝒌𝒌𝒌𝒌
�
BG 5,4 6 NL 30 7,7
DE 575 7,9 PL 3 16,6
DK 32 8,6 GR 19 21,7
RO 22 8,4
Country
Potential
reservoir
[million m
3
]
Potential
cavern
[million m
3
]
Country
Potential
reservoir
[million m
3
]
Potential
cavern
[million
m
3
]
AT 9.264 0 GR 0,002 4.000
BG 0 1.460 IT 8.863 0
DE 172.000 221.000 HU 29.011 0
DK 0 12.000 NL 65.250 12.000
DE 0 0 PL 2.000 4.000
DK 0 0 RO 3.000 8.000
HR 25 0 SI 306 0
UK 34 0,004

22. Optimized electricity output of power plants in Belgium
-20
0
20
40
60
80
100
120
Statistics
Base
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
2010 2015 2020 2025 2030 2035 2040 2045 2050
TWh
Net Electricity ElectricityStorage(excl.PumpHydro)
Netimports
Others/Wastenon-ren.
Hydrogen
OtherRenewables
Biomass/Wasteren.
Solar
Windoffshore
WindOnshore
Hydro(incl.PumpStorage)
Nuclear
GasCCS
Gasw/oCCS
Oil
LigniteCCS
Lignitew/oCCS
CoalCCS
Coalw/oCCS
• Major transition in the years from 2020 to 2030, during phase out of nuclear generation
• Nuclear phase out is compensated mainly through
• Increase in gas generation plant output,
• Decline in energy demand and
• Massive increase in net energy import from neighbouring countries

23. Optimized electricity capacity of power plants in Belgium
0
5
10
15
20
25
30
35
40
45
50
Statistics
Base
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
2010 2015 2020 2025 2030 2035 2040 2045 2050
GW
Capacity
ElectricityStorage(excl.PumpStorage)
Others/Wastenon-ren.
OtherRenewables
Biomass/WasteRen.
Solar
Wind
Hydro(incl.PumpStorage)
Nuclear
NaturalGas
Oil
Lignite
Coal
• Overall capacity increases from 2030 to 2050
• Most growth can be attributed to the increasing wind generation capacity
• ‘Imposed’ higher PV generation capacity (MorePV scenario) results in a reduction of 2 GW of
wind capacity (14 GW in baseline scenario to 12 GW in MorePV scenario)
• Majority of additional PV capacity does not replace other RES capacity, but is added to
overall capacity

24. 0
1
2
3
4
5
6
7
8
9
10 Statistics
Base
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
2010 2015 2020 2025 2030 2035 2040 2045 2050
GWh
Storage Content
Pump Storage
Optimized amount and types of storage sites in Belgium
• New capacity in electrical storage output does not play a role in Belgium in the model results
• Storage is limited to the existing pumped hydro storage with a steady 6.5 GWh of storage content

25. Optimized electricity output of power plants in Netherlands
-20
30
80
130
180
230
Statistics
Base
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
2010 2015 2020 2025 2030 2035 2040 2045 2050
TWh
Net Electricity ElectricityStorage(excl.PumpHydro)
Netimports
Others/Wastenon-ren.
Hydrogen
OtherRenewables
Biomass/Wasteren.
Solar
Windoffshore
WindOnshore
Hydro(incl.PumpStorage)
Nuclear
GasCCS
Gasw/oCCS
Oil
LigniteCCS
Lignitew/oCCS
CoalCCS
Coalw/oCCS
• Netherlands largely differs from the Belgium - only 4 TWh originate from nuclear generation
• Majority of generated by gas and coal plants in base year
• Transition to a more RES based energy system starts with offshore wind energy, in later years
onshore wind and solar generation
• Net transfer capacity from the year 2035 onwards (approx. 12 TWh in 2035,
increasing to 19-20 TWh in 2040, 21 TWh in 2045 approximately)

26. Optimized electricity capacity of power plants in Netherlands
0
10
20
30
40
50
60
70
80
90
100
Statistics
Base
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
2010 2015 2020 2025 2030 2035 2040 2045 2050
GW
Capacity
ElectricityStorage(excl.PumpStorage)
Others/Wastenon-ren.
OtherRenewables
Biomass/WasteRen.
Solar
Wind
Hydro(incl.PumpStorage)
Nuclear
NaturalGas
Oil
Lignite
Coal
• Transition to a more RES based energy system starts with
• Growing share of offshore wind energy,
• Onshore wind and solar generation in later years

27. Optimized amount and types of storage sites in Netherlands
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Statistics
Base
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
2010 2015 2020 2025 2030 2035 2040 2045 2050
GWh
Storage Content
Battery Redox Flow
Battery Lead Acid
Battery Lithium Ion
CAES Adiabatic
CAES Diabatic
Pump Storage
• Reliance on import goes hand in hand with no investments in storage capacities
• Exception being results in the MorePV scenario
• Lithium-ion storage content in the year 2050 of 0.28 GWh

28. Optimized amount and types of storage sites in Netherlands
• Hydrogen storage is chosen in the Dutch context
• For 2050 H2 storage of approximately 13 GWh in the Base and BattCost scenario
• 18 GWh in the MorePV scenario
• Potential sites for hydrogen storage are based on the ESTMAP database.
0
2
4
6
8
10
12
14
16
18
20
Statistics
Base
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
Base
MorePV
BatteryCost
2010 2015 2020 2025 2030 2035 2040 2045 2050
GWh
H2 Storage Content
H2 Storage

29. Germany, Belgium & Netherlands Model -
PowerFys dispatch model (Ecofys)
Frank Meinke-Hubeny

30. Schematic representation of
the inputs and outputs of the PowerFys model

31. PowerFys –
Adaptation of the load variation curve
Snapshot of the first week of January 2050, Germany

32. date
05-Jun 06-Jun 07-Jun 08-Jun
MW
10
4
-2
0
2
4
6
8
10
12
20160720_Baseline_update_v2 - DE+NL+BE elektra
Storage release
RE
Oil
OilCC
Coal
Lignite
Gas
GasCC
curt. RE
Storage filling
Curtailment
Load
PowerFys
Example of power dispatch for a three-day period in June

33. PowerFys
Destination of surplus renewables
% of total renewable generation
0 2 4 6 8 10 12 14 16 18 20
TOTAL
BE
NL
DE
20160720_Baseline_update_v2 - Surplus Renewables
avoided curtailment - to export
avoided curtailment - to storage
curtailment

34. TIMES analysis in the context of large scale energy storage
Challenges / Critical self-reflection
• Underestimation of LSES demand due to low time slice
resolution and ‘last moment investments (e.g. >2040)
• Avoidance of ‘marginally expensive’ technologies, like
storage, due to ‘perfect foresight’
• Secondary business cases or ‘irrational behaviour’ only
implemented as exogenous input
• Interaction with electricity market price difficult to
model
• Transmission capacity investments are used in multi-
region models and compete (or replace?) storage in
small countries (like Belgium)

35. TIMES analysis in the context of large scale energy storage
Lessons learned
• Various storage technologies play a role in the outcomes
– the mix is important and country-specific
• Not a ‘one solution fits all’ result
• ‘Competition’ among technologies play a key role
- see GER example
• Need for a better understanding of the energy systems:
Power - Heat – Storage - Flexibility/DSM
• Transmission capacity and willingness for an Energy
Union have a significant impact on small countries (BE)
• Knowledge of current and future technologies is key
(solar, wind, storage, …): Technical, Economic, Potential
aspects