with Electricity or Biofuels Klaus Skytte and Rasmus Bramstoft DTU - - PowerPoint PPT Presentation

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with Electricity or Biofuels Klaus Skytte and Rasmus Bramstoft DTU - - PowerPoint PPT Presentation

Mar 30, 2024 145 likes •435 views

Decarbonising the Swedish Transport Sector with Electricity or Biofuels Klaus Skytte and Rasmus Bramstoft DTU Management Engineering Energy Economics and Regulation klsk@dtu.dk Agenda Research motivation STREAM model 2050 scenarios

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Decarbonising the Swedish Transport Sector with Electricity or Biofuels

Klaus Skytte and Rasmus Bramstoft DTU Management Engineering Energy Economics and Regulation klsk@dtu.dk

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DTU Management Engineering, Technical University of Denmark

Agenda

■ Research motivation ■ STREAM model ■ 2050 scenarios - reference, EVS and BIOS ■ Scenario results

■ Technological path towards the 2050 target?

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DTU Management Engineering, Technical University of Denmark

Research motivation Sweden

  • The current transport sector is highly dependent of fossil fuels and

therefore emit of greenhouse gases

  • Political targets in Sweden:
  • 2030: Fossil-fuel-independent vehicle fleet
  • 2050: No net greenhouse-gas emissions
  • Radical restructuring of fuel use and vehicle stock

■ Electric Vehicles or Biofuels?

Which costs? Interaction with the energy sectors?

  • Larger share of variable renewable energy sources

e.g. wind in the power supply

  • Need for flexibility?

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DTU Management Engineering, Technical University of Denmark

STREAM model

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DTU Management Engineering, Technical University of Denmark

Scenarios for 2050

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Carbon Neutral Scenario (CNS) from IEA/Nordic Energy Technology Perspectives Electric Vehicles Scenario (EVS) Biofuel Scenario (BIOS) Base year 2012

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DTU Management Engineering, Technical University of Denmark

Transport sector in the base year (2012)

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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Car Bus Train Aviation & ferries Trucks & cargo vans Train Shipping Aviation Fishery Agriculture Person Goods Fishery and agriculture Diesel Gasoline Electricity

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DTU Management Engineering, Technical University of Denmark 7

Reference 2050 Carbon Neutral Scenario - CNS

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Car Bus Train Aviation & ferries Trucks & cargo vans Train Shipping Aviation Fishery Agriculture Person Goods Fishery and agriculture UPGR Biogas Hydrogen Biodiesel Methanol Ethanol Natural Gas Diesel Gasoline Electricity

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DTU Management Engineering, Technical University of Denmark

Biofuel Scenario - BIOS

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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Car Bus Train Aviation & ferries Trucks & cargo vans Train Shipping Aviation Fishery Agriculture Person Goods Fishery and agriculture UPGR Biogas Hydrogen Biodiesel Methanol Ethanol Natural Gas Diesel Gasoline Electricity

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DTU Management Engineering, Technical University of Denmark

Electric Vehicles Scenario - EVS

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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Car Bus Train Aviation & ferries Trucks & cargo vans Train Shipping Aviation Fishery Agriculture Person Goods Fishery and agriculture UPGR Biogas Hydrogen Biodiesel Methanol Ethanol Natural Gas Diesel Gasoline Electricity

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DTU Management Engineering, Technical University of Denmark 10

Technology mix in the electricity sector

  • 100

100 200 300 400 500 600 700 800 Base year CNS EVS BIOS Electricity Production (PJ/year) Import Onshore Wind Offshore Wind Hydro Biomass Waste Incineration Nuclear Gasturbine Coal Plant

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DTU Management Engineering, Technical University of Denmark 11

Technology mix in the district heating sector

20 40 60 80 100 120 140 160 180 Base year CNS EVS BIOS District Heating Production (PJ/year) Biorefinery Heat pump Municipal waste Wood pellet boiler Oil boiler Natural gas boiler Coal boiler Biomass CHP Municipal waste CHP Natural Gas CHP Coal CHP

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DTU Management Engineering, Technical University of Denmark

Scenario Results - EVS

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Power generation and consumption with and without flexible demand in week 4 in year 2050

5000 10000 15000 20000 25000 30000 35000 1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101 105 109 113 117 121 125 129 133 137 141 145 149 153 157 161 165 Power (MW) - week 4 (EVS) Wind Hydro power Thermal power Unflexible electricity demand Flexible electricity demand

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DTU Management Engineering, Technical University of Denmark

Scenario Results - BIOS

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Power generation and consumption with and without flexible demand in week 4 in year 2050

5000 10000 15000 20000 25000 30000 35000 1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101 105 109 113 117 121 125 129 133 137 141 145 149 153 157 161 165 Power (MW) - week 4 (BIOS) Wind Hydro power Thermal power Unflexible electricity demand Flexible electricity demand

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DTU Management Engineering, Technical University of Denmark

Total annual system costs and the difference between the CNS and the EVS/BIOS (mill €)

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5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 CNS EVS BIOS Total Cost (mill. €/year) Energy Savings Capital Cost O&M Cost Fuel Cost CO2 Cost

  • 2000
  • 1500
  • 1000
  • 500

500 1000 1500 2000 Energy Savings Capital Cost O&M Cost Fuel Cost CO2 Cost Cost difference to CN-scenario (mill. €/year) EVS BIOS

3.7% 1.9%

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DTU Management Engineering, Technical University of Denmark

Clarify sensitivities of main assumptions

Sensitivity analysis for the three 2050 scenarios. The figure show the percentage change caused by changing the parameters by 1%

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0,00% 0,05% 0,10% 0,15% 0,20% 0,25% 0,30% CO2 price Bioenergy price EV car Biodiesel car Percentage change BIOS EVS CNS

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DTU Management Engineering, Technical University of Denmark

Sensitivity analysis

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DTU Management Engineering, Technical University of Denmark

In a Nordic content

■ Large deployment of wind ■ Need for flexibility - especially in DK

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Flexible charging of EV and utilisation of heat pumps

■ Hours with excess wind generation

which release hydro-power capacity

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Reduce the need for additional capacity in the EVS scenario

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Increase the value of Hydro power

■ Biomass resources in Finland and Sweden

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Bio-fuels cheaper ■

depends on the development of 2nd and 3th generation bio-refineries

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DTU Management Engineering, Technical University of Denmark

Main findings

■ EVS achieves the lowest socio-economic cost of the system in

2050 – 3.7% lower than CNS

■ BIOS achieves the highest socio-economic cost of the system

in 2050 – 1.9% higher than CNS

■ Higher penetration of wind in EVS efficiently integrated by

demand side flexibility e.g. flexible charging of EV and utilisation of heat pumps

■ Effective utilisation of excess heat generation from biorefinery

processes in the Swedish district heating network in CNS and BIOS

■ Sensitive parameters that can point to another best

performing scenario:

■ BIOS is best if the costs of biodiesel cars are reduced by > 54% ■ EVS is no longer best if the costs of EV increases by 30%

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DTU Management Engineering, Technical University of Denmark

Thank you for your interest

Klaus Skytte

Head of Energy Economics and Regulation System Analysis Division DTU Management Engineering Technical University of Denmark

klsk@dtu.dk, http://www.sys.man.dtu.dk/

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DTU Management Engineering, Technical University of Denmark

Resources available and used

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100 200 300 400 500 600 Resources available and used (PJ) Base year CNS EVS BIOS Available resources

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DTU Management Engineering, Technical University of Denmark 21

Technology mix in the electricity sector

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50 100 150 200 Base year CNS EVS BIOS Electricity Production (TWh/year) Import Onshore Wind Offshore Wind Hydro Biomass Waste Incineration Nuclear Gasturbine Coal Plant

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DTU Management Engineering, Technical University of Denmark 22

Electricity generation capacity

10 20 30 40 50 60 Base year CNS EVS BIOS Electricity generation capacity (GW) Wind Waste Bioenergy Hydro Nuclear Natural Gas Coal

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DTU Management Engineering, Technical University of Denmark

Main data assumptions

■ Fuel and CO2 prices by 2050:

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Fuel prices Natural Gas 6.02 €/GJ Nuclear - Uranium 4.00 €/GJ Biomass (Straw, woodwaste) 9.10 €/GJ Biomass (Energy crops ) 9.78 €/GJ Biomass (manure) 0.00 €/GJ Imported electricity 31.13 €/GJ Coal 1.58 €/GJ Oil 16.40 €/GJ CO2 price 120.30 €/t CO2

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DTU Management Engineering, Technical University of Denmark

Main data assumptions

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Yearly energy savings compared to frozen efficiency

Residential Electricity appliances 2.13% Total Heat Supplied 1.90% Tertiary Electricity appliances 1.42% Total Heat Supplied 1.80% Industry Electricity appliances 1.42% Total Process energy 1.87% Economic growth (% pr. Year) Structure/ Intensity factor Residential

  • electricity

2.0% 0.9

  • heat

2.0% 0.5 Tertiary

  • electricity

2.0% 0.9

  • heat

2.0% 0.5 Industry

  • electricity

2.0% 0.9

  • proces heat

2.0% 0.9 Transport

  • passenger

1.0% 1.0

  • freight

0.7% 1.0

  • fishery

1.0% 1.0

  • agriculture

1.0% 1.0 Discount rate for calculating capital costs 5%

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DTU Management Engineering, Technical University of Denmark

Costs of cars implemented in STREAM

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0,1 0,15 0,2 0,25 0,3 2015 2020 2025 2030 2035 2040 2045 2050 Vehicle + Operational Costs (€/km) Ethanol Biodiesel Methanol UPGR Biogas EV >500 km H2 FCV

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DTU Management Engineering, Technical University of Denmark

Model structure in STREAM

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Final Energy Demand

  • Electricity
  • Heating
  • Process Heating
  • Transport

Base year

Energy Demand – Frozen efficiency

  • Electricity
  • Heating
  • Process Heating
  • Transport

2050

STREAM Model Final Energy Demand

  • Electricity
  • Heating
  • Process Heating
  • Transport

2050

Outputs

  • Energy balance
  • Fuel consumption
  • GHG emissions
  • Costs

2050 Energy intensity Economic growth Energy savings Allocation of transport work; Utilization degree & Stock density Define share of technologies in the generation of:

  • Electricity
  • Heating
  • Process Heating
  • Transport

Other input data

  • Technological data & cost
  • Fuel prices
  • GHG emission factors
  • Time series
  • Flexibility

Statistical data User defined Results Model

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DTU Management Engineering, Technical University of Denmark

Sensitivity analysis

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