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Analysis of different sector coupling paths for CO2 mitigation in the German transport sector

IEA-ETSAP
IEA-ETSAP

The document analyzes sector coupling paths for CO2 mitigation in the German transport sector using the TIMES-D model. It finds that the contribution of trolley trucks is highly dependent on the GHG reduction targets selected, with no use in the scenario with an 80% reduction by 2050 but full use in the 95% reduction scenario. E-mobility adoption also varies significantly between scenarios based on the long-term target, ranging from 21% to 75% of personal transport demand by 2050. Limiting simultaneous charging infrastructure use can regulate load but allowing flexibility could cause additional loads up to 40 GW.

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Felix Kattelmann, Markus Blesl
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Felix Kattelmann
Markus Blesl
Analysis of different
sector coupling paths for
CO2 mitigation in the
German Transport sector
Source: Forschungszentrum Jülich/Tricklabor for the Kopernikus project “Power-to-X”
Felix Kattelmann, Markus Blesl
1. Introduction
2. TIMES Model
• General modelling approach
• Implementation of trolley trucks
• E-Mobility
• Scenario Analyses
3. Results
4. Conclusion
74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 2
Outline
Felix Kattelmann, Markus Blesl
2015 2020 2030 2040 2050
overall GHG
emissions
-27.2% -40% -55% -70% -80% to -95%
74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 3
Motivation
German national targets for reducing the Greenhouse Gas emissions compared to 1990 [1]
• ambitious goals for GHG emission reductions
• almost complete decarbonisation of the entire German energy system necessary
• need of renewables in heat and transport sector
• potentials of renewables mostly in electricity sector
sector coupling
Felix Kattelmann, Markus Blesl
TIMES-D model
Felix Kattelmann, Markus Blesl
• depiction of the entire German energy system
• derived from the TIMES-PanEU model
• linear optimization: total system costs minimized
• complete competition between different
technologies assumed
• GHG emissions of the system are recorded
• division into 280 time segments of 3 hours each
• model horizon: 2010-2050
• determination of the economically optimal
energy supply structure for a given target
74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 5
General modelling approach
TIMES-D model
Felix Kattelmann, Markus Blesl
technology characteristics
• electrically powered trucks
• energy supply via pantograph and overhead lines
• construction of the necessary infrastructure over
motorways (as discussed) cost-intensive
74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 6
Implementation of Trolley Trucks
TIMES-D model
modelling
• one of multiple technologies in transport sector
• selection of technologies in model dependent on
process-costs (amongst other things) e.g. investment or
maintenance costs
• contribution to meeting the freight traffic demand
limited to 90%
picture: dpa/picture-alliance
Felix Kattelmann, Markus Blesl
• costs for complete electrification of motorways
distributed over assumed max. number of vehicles
• problem: clear differences in the utilisation of
motorways in Germany
• overhead lines over heavily used motorways can
power more vehicles than over low-frequented ones
• new implementation
• infrastructure costs distributed unevenly over
three stages
• stage 1: 1/3 of vehicles but 1/6 of infrastructure
• potential of one stage limited to 1/3 of the max.
overall contribution from Trolley Trucks
74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 7
Implementation of Trolley Trucks – more accurate modelling of infrastructure
TIMES-D model
stage 1 stage 2 stage 3
new implementation
vehicle
infra-
structure
previous
implementation
investment
cost
Trolley Trucks
1/6
2/6
3/6
Felix Kattelmann, Markus Blesl
• e-mobility: all electrically operated vehicles in transport sector (except for heavy goods traffic and trains)
• sufficient charging infrastructure has to be used to charge the batteries
• Power-to-grid possible
• one of multiple technology pathways in transport sector
74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 8
Modelling of e-mobility
TIMES-D model
charging
infrastructure
battery
Power-to-grid
electric vehicle
electricity grid
electricity grid
mobility demand
Felix Kattelmann, Markus Blesl
• gradual reduction of the system‘s GHG emissions
• three scenarios with great differences in the long-
term reduction targets
• Trolley Trucks: scenario S90 with and without
disaggregated infrastructure
• analysis of the charging infrastructure‘s influence
• share of simultaneously usable infrastructure
limited to 10%, 50% and 90%
scenario 2020 2030 2050
Reduction of
overall GHG
emissions
S80 -40% -55% -80%
S90 -40% -55% -90%
S95 -40% -58% -95%
74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 9
scenario analyses
TIMES-D model
Felix Kattelmann, Markus Blesl
Results
Felix Kattelmann, Markus Blesl 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 11
Freight Traffic – potential of the Trolley Truck
Results
• huge discrepancy between
the scenarios:
• entire possible demand
provided by Trolley
Trucks in S95
• no usage at all in S80
• deployment of trolley
trucks highly dependent
on the selection of GHG
reduction targets
0
100,000
200,000
300,000
400,000
500,000
600,000
S80 S90 S95 S80 S90 S95 S80 S90 S95 S80 S90 S95
2035 2040 2045 2050
Freightdemandintkm
Years
Meeting the demand of freight transport
Trolley Truck
Rest
Felix Kattelmann, Markus Blesl
• share of electricity:
• 30% (disaggregated
infrastructure)
• 21% (base)
• usage of Trolley Trucks
depends strongly on the
modelling of
infrastructure
74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 12
Freight Traffic – influence of disaggregated infrastructure modelling
Results
0
100
200
300
400
500
600
700
800
900
1000
base
S90
base
S90
base
S90
base
S90
base
S90
2030 2035 2040 2045 2050
FinalenegryconsumptioninPJ
Years
Final energy consumption in heavy road freight
traffic
Hydrogen
Electricity
Natural Gas
Diesel
Biofuels
Felix Kattelmann, Markus Blesl
• 13.3 GW additional load in S90
• 18 GW additional load in S95
• load directly dependent on
driving behaviour
74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 13
Freight Traffic
Results
0
2
4
6
8
10
12
14
16
18
20
ElectricalloadinGW
day of the week
Overall electrical load from trolley trucks in 2050
S80
S90
S95
Monday Tuesday Wednesday Thursday Friday Saturday
Felix Kattelmann, Markus Blesl
• no difference between the
scenarios until 2035
• contribution of electric vehicles
varies between 21% (scenario
S80) and 75% (S95) in 2050
• choice of the long-term target
has a major impact on the
utilization of electric vehicles
74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 14
E-Mobility
Results
0
100,000
200,000
300,000
400,000
500,000
600,000
700,000
800,000
900,000
1,000,000
S80 S90 S95 S80 S90 S95 S80 S90 S95 S80 S90 S95 S80 S90 S95 S80 S90 S95
2025 2030 2035 2040 2045 2050
Demandofpersonaltransportinpkm
Years
Meeting the personal transport demand
Rest
Electric Vehicles
Felix Kattelmann, Markus Blesl
• higher electricity consumption in
2050 due to electrification of all
sectors
• in the S95 scenario e-mobility
accounts for 10% of the total power
consumption in 2050 (280 PJ)
• S95: 190 PJ more by e-mobility
compared to S80
74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 15
E-Mobility
Results
0
500
1000
1500
2000
2500
S80 S90 S95 S80 S90 S95 S80 S90 S95
2030 2040 2050
ElectrictiyconsumptioninPJ
Years
Electricity Consumption by sector
E-Mobility
Remaining Transport
Supply
Residential
Industry
Comercial
Agriculture
Felix Kattelmann, Markus Blesl 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 16
E-Mobility – electrical load caused by charging
Results
huge peaks for 50% availability
Felix Kattelmann, Markus Blesl 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 17
E-Mobility – residual load and load by charging
Results
Felix Kattelmann, Markus Blesl
Conclusion
Felix Kattelmann, Markus Blesl
• contribution of the Trolley Truck heavily dependent on the choice of emission reduction targets with no
usage at all in the S80 scenario
• maximal electrical load of trolley trucks is 18 GW, likely to vary significantly between different regions
• significant influence of detailed modelling of infrastructures on the results of Trolley Truck analyses
• GHG emission reduction targets with major impact on the utilisation of e-mobility (varying between 21%
and 75%)
• the load caused by charging electric vehicles can be regulated by limiting the simultaneousness of the
charging infrastructure
• by not limiting the simultaneousness e-mobility can serve as a very useful flexibility option, causing large
additional loads of around 40 GW however
74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 19
Conclusion
Felix Kattelmann, Markus Blesl
[1] BMWi, “Die Energie der Zukunft - Vierter Monitoring-Bericht zur Energiewende,” Bundesministerium für
Wirtschaft und Energie (BMWi), Tech. Rep., 2015.
[2] Bundesministerium für Wirtschaft und Energie, “Energieffizienz in Zahlen,” Tech. Rep., 2017.
[3] M. Wietschel et al., “Machbarkeitsstudie zur Ermittlung der Potentiale des Hybrid-Oberleitungs-Lkw,”
Fraunhofer ISI, Tech. Rep., 2017.
[4] B. Lenz, “Shell Lkw-Studie - Fakten, Trends und Perspektiven im Straßengüterverkehr bis 2030,” Deutsches
Zentrum für Luft- und Raumfahrt, Tech. Rep., 2010.
74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 20
References
Felix Kattelmann, Markus Blesl
e-mail
phone +49 (0) 711 685-
fax +49 (0) 711 685-
Universität Stuttgart
Thank you!
IER Institute for Energy Economics
and Rational Energy Use
Felix Kattelmann
87845
87873
Institute for Energy Economics and Rational Energy Use
felix.kattelmann@ier.uni-stuttgart.de
Heßbrühlstr. 49a
70565 Stuttgart
Germany
This work is part of the ENavi project, financed by
the Federal Ministry of Education and Research of
Germany.

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Analysis of different sector coupling paths for CO2 mitigation in the German transport sector

  • 1. Felix Kattelmann, Markus Blesl Click to edit Master subtitle style Felix Kattelmann Markus Blesl Analysis of different sector coupling paths for CO2 mitigation in the German Transport sector Source: Forschungszentrum Jülich/Tricklabor for the Kopernikus project “Power-to-X”
  • 2. Felix Kattelmann, Markus Blesl 1. Introduction 2. TIMES Model • General modelling approach • Implementation of trolley trucks • E-Mobility • Scenario Analyses 3. Results 4. Conclusion 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 2 Outline
  • 3. Felix Kattelmann, Markus Blesl 2015 2020 2030 2040 2050 overall GHG emissions -27.2% -40% -55% -70% -80% to -95% 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 3 Motivation German national targets for reducing the Greenhouse Gas emissions compared to 1990 [1] • ambitious goals for GHG emission reductions • almost complete decarbonisation of the entire German energy system necessary • need of renewables in heat and transport sector • potentials of renewables mostly in electricity sector sector coupling
  • 4. Felix Kattelmann, Markus Blesl TIMES-D model
  • 5. Felix Kattelmann, Markus Blesl • depiction of the entire German energy system • derived from the TIMES-PanEU model • linear optimization: total system costs minimized • complete competition between different technologies assumed • GHG emissions of the system are recorded • division into 280 time segments of 3 hours each • model horizon: 2010-2050 • determination of the economically optimal energy supply structure for a given target 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 5 General modelling approach TIMES-D model
  • 6. Felix Kattelmann, Markus Blesl technology characteristics • electrically powered trucks • energy supply via pantograph and overhead lines • construction of the necessary infrastructure over motorways (as discussed) cost-intensive 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 6 Implementation of Trolley Trucks TIMES-D model modelling • one of multiple technologies in transport sector • selection of technologies in model dependent on process-costs (amongst other things) e.g. investment or maintenance costs • contribution to meeting the freight traffic demand limited to 90% picture: dpa/picture-alliance
  • 7. Felix Kattelmann, Markus Blesl • costs for complete electrification of motorways distributed over assumed max. number of vehicles • problem: clear differences in the utilisation of motorways in Germany • overhead lines over heavily used motorways can power more vehicles than over low-frequented ones • new implementation • infrastructure costs distributed unevenly over three stages • stage 1: 1/3 of vehicles but 1/6 of infrastructure • potential of one stage limited to 1/3 of the max. overall contribution from Trolley Trucks 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 7 Implementation of Trolley Trucks – more accurate modelling of infrastructure TIMES-D model stage 1 stage 2 stage 3 new implementation vehicle infra- structure previous implementation investment cost Trolley Trucks 1/6 2/6 3/6
  • 8. Felix Kattelmann, Markus Blesl • e-mobility: all electrically operated vehicles in transport sector (except for heavy goods traffic and trains) • sufficient charging infrastructure has to be used to charge the batteries • Power-to-grid possible • one of multiple technology pathways in transport sector 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 8 Modelling of e-mobility TIMES-D model charging infrastructure battery Power-to-grid electric vehicle electricity grid electricity grid mobility demand
  • 9. Felix Kattelmann, Markus Blesl • gradual reduction of the system‘s GHG emissions • three scenarios with great differences in the long- term reduction targets • Trolley Trucks: scenario S90 with and without disaggregated infrastructure • analysis of the charging infrastructure‘s influence • share of simultaneously usable infrastructure limited to 10%, 50% and 90% scenario 2020 2030 2050 Reduction of overall GHG emissions S80 -40% -55% -80% S90 -40% -55% -90% S95 -40% -58% -95% 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 9 scenario analyses TIMES-D model
  • 10. Felix Kattelmann, Markus Blesl Results
  • 11. Felix Kattelmann, Markus Blesl 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 11 Freight Traffic – potential of the Trolley Truck Results • huge discrepancy between the scenarios: • entire possible demand provided by Trolley Trucks in S95 • no usage at all in S80 • deployment of trolley trucks highly dependent on the selection of GHG reduction targets 0 100,000 200,000 300,000 400,000 500,000 600,000 S80 S90 S95 S80 S90 S95 S80 S90 S95 S80 S90 S95 2035 2040 2045 2050 Freightdemandintkm Years Meeting the demand of freight transport Trolley Truck Rest
  • 12. Felix Kattelmann, Markus Blesl • share of electricity: • 30% (disaggregated infrastructure) • 21% (base) • usage of Trolley Trucks depends strongly on the modelling of infrastructure 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 12 Freight Traffic – influence of disaggregated infrastructure modelling Results 0 100 200 300 400 500 600 700 800 900 1000 base S90 base S90 base S90 base S90 base S90 2030 2035 2040 2045 2050 FinalenegryconsumptioninPJ Years Final energy consumption in heavy road freight traffic Hydrogen Electricity Natural Gas Diesel Biofuels
  • 13. Felix Kattelmann, Markus Blesl • 13.3 GW additional load in S90 • 18 GW additional load in S95 • load directly dependent on driving behaviour 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 13 Freight Traffic Results 0 2 4 6 8 10 12 14 16 18 20 ElectricalloadinGW day of the week Overall electrical load from trolley trucks in 2050 S80 S90 S95 Monday Tuesday Wednesday Thursday Friday Saturday
  • 14. Felix Kattelmann, Markus Blesl • no difference between the scenarios until 2035 • contribution of electric vehicles varies between 21% (scenario S80) and 75% (S95) in 2050 • choice of the long-term target has a major impact on the utilization of electric vehicles 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 14 E-Mobility Results 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 900,000 1,000,000 S80 S90 S95 S80 S90 S95 S80 S90 S95 S80 S90 S95 S80 S90 S95 S80 S90 S95 2025 2030 2035 2040 2045 2050 Demandofpersonaltransportinpkm Years Meeting the personal transport demand Rest Electric Vehicles
  • 15. Felix Kattelmann, Markus Blesl • higher electricity consumption in 2050 due to electrification of all sectors • in the S95 scenario e-mobility accounts for 10% of the total power consumption in 2050 (280 PJ) • S95: 190 PJ more by e-mobility compared to S80 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 15 E-Mobility Results 0 500 1000 1500 2000 2500 S80 S90 S95 S80 S90 S95 S80 S90 S95 2030 2040 2050 ElectrictiyconsumptioninPJ Years Electricity Consumption by sector E-Mobility Remaining Transport Supply Residential Industry Comercial Agriculture
  • 16. Felix Kattelmann, Markus Blesl 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 16 E-Mobility – electrical load caused by charging Results huge peaks for 50% availability
  • 17. Felix Kattelmann, Markus Blesl 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 17 E-Mobility – residual load and load by charging Results
  • 18. Felix Kattelmann, Markus Blesl Conclusion
  • 19. Felix Kattelmann, Markus Blesl • contribution of the Trolley Truck heavily dependent on the choice of emission reduction targets with no usage at all in the S80 scenario • maximal electrical load of trolley trucks is 18 GW, likely to vary significantly between different regions • significant influence of detailed modelling of infrastructures on the results of Trolley Truck analyses • GHG emission reduction targets with major impact on the utilisation of e-mobility (varying between 21% and 75%) • the load caused by charging electric vehicles can be regulated by limiting the simultaneousness of the charging infrastructure • by not limiting the simultaneousness e-mobility can serve as a very useful flexibility option, causing large additional loads of around 40 GW however 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 19 Conclusion
  • 20. Felix Kattelmann, Markus Blesl [1] BMWi, “Die Energie der Zukunft - Vierter Monitoring-Bericht zur Energiewende,” Bundesministerium für Wirtschaft und Energie (BMWi), Tech. Rep., 2015. [2] Bundesministerium für Wirtschaft und Energie, “Energieffizienz in Zahlen,” Tech. Rep., 2017. [3] M. Wietschel et al., “Machbarkeitsstudie zur Ermittlung der Potentiale des Hybrid-Oberleitungs-Lkw,” Fraunhofer ISI, Tech. Rep., 2017. [4] B. Lenz, “Shell Lkw-Studie - Fakten, Trends und Perspektiven im Straßengüterverkehr bis 2030,” Deutsches Zentrum für Luft- und Raumfahrt, Tech. Rep., 2010. 74th ETSAP Meeting, Stuttgart 07.11.2018IER University of Stuttgart 20 References
  • 21. Felix Kattelmann, Markus Blesl e-mail phone +49 (0) 711 685- fax +49 (0) 711 685- Universität Stuttgart Thank you! IER Institute for Energy Economics and Rational Energy Use Felix Kattelmann 87845 87873 Institute for Energy Economics and Rational Energy Use felix.kattelmann@ier.uni-stuttgart.de Heßbrühlstr. 49a 70565 Stuttgart Germany This work is part of the ENavi project, financed by the Federal Ministry of Education and Research of Germany.