Modelling challenges for Hydrogen and Synfuel pathways in Europe

1. IER
Modeling Hydrogen
Pathways in Europe
in TIMES PanEU
IEA-ETSAP Workshop
New York
02.12.2022
Drin Marmullaku
Prof. Markus Blesl

2. 01 Motivation
Agenda
12/18/2022
IER Universität Stuttgart 2
02 Hydrogen Modeling
03 Frist Preliminary Results
04 Conclusion & Next Steps

3. 01 Motivation
Agenda
12/18/2022
IER Universität Stuttgart 3
02 Hydrogen Modeling
03 Frist Preliminary Results
04 Conclusion & Next Steps

4. 12/18/2022
IER Universität Stuttgart 4
The way to climate neutrality in Germany by 2045 and the role of zero-emission energy carrier
Motivation
2020 2030 2045
▪ Strong dependence on fossil imports
▪ 75% of primary energy consumption
through imports
▪ 35 % Oil
▪ 25 % Natural Gas
▪ 8 % Coal
▪ 6 % Uranium
▪ Green hydrogen and e-fuels do not play a
significant role
▪ Decline of fossil imports
▪ Climate-neutral hydrogen and its imports
are low compared to total energy
consumption
▪ Few supply options and infrastructures
for H2 and e-fuels
▪ Expansion of the H2 infrastructure in
progress
▪ Entire energy demand covered by
domestic or imported zero-emission
energy sources
▪ Substantial need for imports due to
limited renewable energy potential
▪ „In the course of the increase in H2
imports from 2030, it can be assumed
that a robust H2 infrastructure will exist
by 2045, both within Germany and the
EU as well as for imports “ [European
Hydrogen Backbone, 2020]
Status Quo Intermediate Stage Target

5. 12/18/2022
IER Universität Stuttgart 5
Demand for Hydrogen and E-Fuels in Germany
Motivation
0
100
200
300
400
500
2030 2045 2030 2045 2030 2045
TWh
E-Fuel-Demand
Import
BDI, 2021b
Prognos, Wuppertal-
Institut et al., 2021
dena, 2021
57
305
158
4
198
0
100
200
300
400
500
2030 2045 2030 2045 2030 2045
TWh
Hydrogen Demand
BDI, 2021b Prognos, Wuppertal-
Institut et al., 2021
dena, 2021
43
237
63
265
66
458
Domestic
▪ Increasing demand for H2 and E-Fuels
▪ Most of the H2 and E-Fuel demand is covered by imports
▪ Import options limited in 2030 due to lack of European infrastructure and supply options
→ Early analysis of national and international supply options and infrastructure

6. 01 Motivation
Agenda
12/18/2022
IER Universität Stuttgart 6
02 Hydrogen Modeling
03 Frist Preliminary Results
04 Conclusion & Next Steps

7. 12/18/2022
IER Universität Stuttgart 7
TIMES-PanEU Energy System Model: Overview
Methodology
▪ Bottom-Up Model, model language GAMS
▪ Multi-regional (EU27 + UK, CH, NO)
▪ Time horizon 2010-2050
▪ All relevant sectors and full competition between technologies and energy carriers
▪ Trade between regions and non-EU countries
→ detailed energy system analysis for Germany/Europe possible

8. 12/18/2022
IER Universität Stuttgart 8
Times PanEU – Hydrogen Trade
Hydrogen Modeling
Module 1:
endogenous H2
trade within EU
Module 2:
exogenous H2
trade with Non-
EU
TIMES PanEU
• TIMES PanEU – H2INFRA

9. 12/18/2022
IER Universität Stuttgart 9
Hydrogen Module: Generell Overview
Interactions
Supply
Central
Production
Decentral
Production
Import/
Export
Delivery
Infrastructure
Demand
H2-Technologies
• „Chicken-Egg Problem“
• Competition between different emission-free
energy carriers
*simplified overview of the hydrogen model

10. 12/18/2022
IER Universität Stuttgart 10
Hydrogen Trade
FR
ES
Trade
Process
H2 Production
(central)
Transmission Grid Distribution Grid
Fuel Tech
Trade
Process
H2 Production
(central)
Transmission Grid Distribution Grid
Fuel Tech
GER
H2 Production
(central)
Transmission Grid Distribution Grid
Fuel Tech
Methodology: Uniliteral Trade between EU Regions
H2
H2TRADE
H2
H2TRADE
H2
→ Own consumption and conduction
possible

11. 12/18/2022
IER Universität Stuttgart 11
Trade Parameters
Modeling of Unilateral Trade Process: Hydrogen Pipeline
capacity
Investment
k1
k2
small medium
k0
large
Investment
▪ Pipeline costs at „medium“ capacities for reference scenario
▪ Pipeline cost at low capacities are underestimated
▪ Pipeline costs at large capacities are overestimated
▪ Unrealistic small capacities can be built
▪ Lumpy Investments → high increase of solution time (MIP)
Distance matrix
▪ Linking all regions with their neighbor regions (>120 links)
▪ Distance = Beeline between region centers
▪ Detour factor 1.4, based on [6]
Data
Danish Energy Agency
2030 2050 2030 2050
Capacity Investment Fixed O+M
GW Euro/MW/m Euro/MW/km/year
small 0,5-1 0,70 0,70 0,25 0,2
medium 1-4 0,40 0,40 0,25 0,2
large >6 0,20 0,20 0,25 0,2

12. 01 Motivation
Agenda
12/18/2022
IER Universität Stuttgart 12
02 Hydrogen Modeling
03 Frist Preliminary Results
04 Conclusion & Next Steps

13. 12/18/2022
IER Universität Stuttgart 13
Scenariodesign
Reference Scenario
▪ Pipeline Costs „medium“
→ Parameters for Pipelinesize medium
Scenario „High Cost“
▪ Pipeline Costs „high“
→ Parameters for Pipelinesize small
Scenario „Low Cost“
▪ Pipeline Costs „low“
→ Parameters for Pipelinesize large
1. Calculation Scenario‘s
2. Adjusting trade links
a) Trade links with capacity > 0,5 GW = 1
b) All links with capacity < 0,5 GW = 0 (nearly 0.15 m as the smallest diameter for natural gas pipelines [6])
3. Calculation Scenario‘s
4. Postprocessing Trade Results
Process
Data
Danish Energy Agency
2030 2050 2030 2050
Pipeline-
size
Capacity Investments Fixed O+M
GW Euro/MW/m Euro/MW/km/year
small 0,5-1 0,70 0,70 0,25 0,2
medium 1-4 0,40 0,40 0,25 0,2
large >6 0,20 0,20 0,25 0,2
EU carbon emission target: -55% reduction in 2030 and net zero emissions in 2050

14. 12/18/2022
IER Universität Stuttgart 14
Results
Reference Scenario: H2 Production
2030 2035 2040 2045 2050
• Hydrogen ramp-up starts in 2035/40
• Largest H2 producers: GER, SE, NO, UK, FR
• Hydrogen production mainly via electrolyser
*26 GW
*Capacity Electrolyser

15. 12/18/2022
IER Universität Stuttgart 15
Results
Reference Scenario: H2 Trade and Pipeline Capacity
Energy
Trade
Capacity
2030 2035 2040 2045 2050
2030 2035 2040 2045 2050

16. 12/18/2022
IER Universität Stuttgart 16
Results
Scenario Comparison
Annual EU H2 Trade Volume compared to the reference scenario
-80%
-60%
-40%
-20%
0%
20%
40%
60%
80%
100%
120%
140%
2 0 3 0 2050
Low Costs Ref. High Costs
+ 116 %
+ 16 %
- 26 %
- 53 %
Aggregated EU H2 Trade Capacity compared to the reference scenario
-60%
-40%
-20%
0%
20%
40%
60%
80%
100%
2030 2 0 5 0
Low Costs Ref. High Costs
+ 12 %
- 28 %
+ 92 %
- 48 %
→ Scenario „Low Cost“: Fast ramp-up for hydrogen trade
→ Scenario „High Cost“: Slow ramp-up for hydrogen trade

17. 01 Motivation
Agenda
12/18/2022
IER Universität Stuttgart 17
02 Hydrogen Modeling
03 Frist Preliminary Results
04 Conclusion & Next Steps

18. Conclusion
• Including H2 and synfuel/syngas imports from Non-EU Regions
• Extending Industry H2 Technologies
• Validation of H2 technologies for methanol, ammonia, aromates, olefins
• H2 demand expect to increase (strong impact on H2 infrastructure)
• Highest H2 Production via Electrolysers in Germany
• Highest H2 Import Demand in Germany
• High Exports from the „North-Corridor“ (NO, SE)
• Sensitivity analysis on investment show a strong influence on H2 Trade
• Lower costs leads to faster hydrogen ramp-up
• High costs leads to a slower hydrogen ramp-up
12/18/2022
IER Universität Stuttgart 18
Conclusion & Next Steps
Next Steps

19. [1] Staffell et al. (2019) The role of hydrogen and fuel cells in the global energy system
[2] Deutsche Energie-Agentur GmbH (Hrsg.) (dena, 2021). dena-Leitstudie Aufbruch Klimaneutralität
[3] Prognos, Öko-Institut, Wuppertal-Institut (2021): Klimaneutrales Deutschland 2045. Wie Deutschland seine Klimaziele schon vor 2050 erreichen kann
[4] Zusammenfassung im Auftrag von Stiftung Klimaneutralität, Agora Energiewende und Agora Verkehrswende
[5] Bundesverband der Deutschen Industrie (BDI) (2021): KLIMAPFADE 2.0. Ein Wirtschaftsprogramm für Klima und Zukunft.
[6] Çağlayan, Dilara Gülçin (2020): A robust design of a renewable European energy system encompassing a hydrogen infrastructure. Unter Mitarbeit von Detlef Stolten und
Andreas Jupke. Aachen: Universitätsbibliothek der RWTH Aachen.
12/18/2022
IER Universität Stuttgart 19
Sources

20. Thank you for your attention!
IER Institut für Energiewirtschaft
und Rationelle Energieanwendung
Drin Marmullaku
Institute of energey economics and rational energyuse (IER)
University Stuttgart
Drin.marmullaku@ier.uni-stuttgart.de
T: +49 711 685-87827
IER UniversitätStuttgart 12/18/2022