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

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 - reference, EVS and BIOS ■ Scenario results ■ Technological path towards the 2050 target? 2 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? 3 DTU Management Engineering, Technical University of Denmark

STREAM model 4 DTU Management Engineering, Technical University of Denmark

Scenarios for 2050 Carbon Neutral Scenario (CNS) from IEA/Nordic Energy Technology Perspectives Electric Vehicles Scenario (EVS) Biofuel Scenario (BIOS) Base year 2012 5 DTU Management Engineering, Technical University of Denmark

Transport sector in the base year (2012) 100% 90% 80% 70% 60% 50% Diesel Gasoline 40% Electricity 30% 20% 10% 0% Car Bus Train Aviation & Trucks & Train Shipping Aviation Fishery Agriculture ferries cargo vans Person Goods Fishery and agriculture 6 DTU Management Engineering, Technical University of Denmark

Reference 2050 Carbon Neutral Scenario - CNS 100% 90% 80% 70% UPGR Biogas Hydrogen 60% Biodiesel 50% Methanol Ethanol 40% Natural Gas Diesel 30% Gasoline 20% Electricity 10% 0% Car Bus Train Aviation & Trucks & Train Shipping Aviation Fishery Agriculture ferries cargo vans Person Goods Fishery and agriculture 7 DTU Management Engineering, Technical University of Denmark

Biofuel Scenario - BIOS 100% 90% 80% 70% UPGR Biogas Hydrogen 60% Biodiesel 50% Methanol Ethanol 40% Natural Gas 30% Diesel Gasoline 20% Electricity 10% 0% Car Bus Train Aviation & Trucks & Train Shipping Aviation Fishery Agriculture ferries cargo vans Person Goods Fishery and agriculture 8 DTU Management Engineering, Technical University of Denmark

Electric Vehicles Scenario - EVS 100% 90% 80% 70% UPGR Biogas Hydrogen 60% Biodiesel 50% Methanol Ethanol 40% Natural Gas 30% Diesel Gasoline 20% Electricity 10% 0% Car Bus Train Aviation & Trucks & Train Shipping Aviation Fishery Agriculture ferries cargo vans Person Goods Fishery and agriculture 9 DTU Management Engineering, Technical University of Denmark

Technology mix in the electricity sector 800 700 600 Import Electricity Production (PJ/year) 500 Onshore Wind Offshore Wind 400 Hydro Biomass Waste Incineration 300 Nuclear Gasturbine 200 Coal Plant 100 0 Base year CNS EVS BIOS -100 10 DTU Management Engineering, Technical University of Denmark

Technology mix in the district heating sector 180 160 140 Biorefinery District Heating Production (PJ/year) Heat pump 120 Municipal waste Wood pellet boiler 100 Oil boiler Natural gas boiler 80 Coal boiler Biomass CHP 60 Municipal waste CHP Natural Gas CHP 40 Coal CHP 20 0 Base year CNS EVS BIOS 11 DTU Management Engineering, Technical University of Denmark

Scenario Results - EVS 35000 30000 Power (MW) - week 4 (EVS) 25000 20000 15000 10000 5000 0 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 Wind Hydro power Thermal power Unflexible electricity demand Flexible electricity demand Power generation and consumption with and without flexible demand in week 4 in year 2050 12 DTU Management Engineering, Technical University of Denmark

Scenario Results - BIOS 35000 30000 Power (MW) - week 4 (BIOS) 25000 20000 15000 10000 5000 0 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 Wind Hydro power Thermal power Unflexible electricity demand Flexible electricity demand Power generation and consumption with and without flexible demand in week 4 in year 2050 13 DTU Management Engineering, Technical University of Denmark

Total annual system costs and the difference between the CNS and the EVS/BIOS (mill € ) 50000 2000 45000 1500 40000 Cost difference to CN-scenario 1000 35000 Total Cost (mill. € /year) 500 30000 (mill. € /year) 25000 0 20000 -500 15000 -1000 10000 -1500 5000 0 -2000 CNS EVS BIOS Energy Capital Cost O&M Cost Fuel Cost CO2 Cost Savings Energy Savings Capital Cost O&M Cost Fuel Cost CO2 Cost EVS BIOS 3.7% 1.9% 14 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% Biodiesel car EV car BIOS EVS CNS Bioenergy price CO2 price 0,00% 0,05% 0,10% 0,15% 0,20% 0,25% 0,30% Percentage change 15 DTU Management Engineering, Technical University of Denmark

Sensitivity analysis 16 DTU Management Engineering, Technical University of Denmark

In a Nordic content ■ Large deployment of wind ■ Need for flexibility - especially in DK ■ Flexible charging of EV and utilisation of heat pumps ■ Hours with excess wind generation which release hydro-power capacity ■ Reduce the need for additional capacity in the EVS scenario ■ Increase the value of Hydro power ■ Biomass resources in Finland and Sweden ■ Bio-fuels cheaper ■ depends on the development of 2nd and 3th generation bio-refineries 17 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% 18 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/ DTU Management Engineering, Technical University of Denmark

Resources available and used 600 500 Resources available and used (PJ) Base year 400 CNS EVS 300 BIOS 200 Available resources 100 0 20 DTU Management Engineering, Technical University of Denmark

Technology mix in the electricity sector 200 150 Import Electricity Production (TWh/year) Onshore Wind Offshore Wind 100 Hydro Biomass Waste Incineration 50 Nuclear Gasturbine Coal Plant 0 Base year CNS EVS BIOS -50 21 DTU Management Engineering, Technical University of Denmark

Electricity generation capacity 60 50 Electricity generation capacity (GW) Wind 40 Waste Bioenergy 30 Hydro Nuclear Natural Gas 20 Coal 10 0 Base year CNS EVS BIOS 22 DTU Management Engineering, Technical University of Denmark

Main data assumptions ■ Fuel and CO 2 prices by 2050: Fuel prices Natural Gas 6.02 € /GJ Nuclear - Uranium 4.00 € /GJ Biomass (Straw, 9.10 € /GJ woodwaste) Biomass (Energy crops ) 9.78 € /GJ Biomass (manure) 0.00 € /GJ Imported electricity 31.13 € /GJ Coal 1.58 € /GJ Oil 16.40 € /GJ CO 2 price 120.30 € /t CO 2 23 DTU Management Engineering, Technical University of Denmark

Main data assumptions Economic Structure/ growth Intensity (% pr. Year) factor Residential Yearly energy savings compared - electricity 2.0% 0.9 to frozen efficiency - heat 2.0% 0.5 Residential Tertiary Electricity appliances 2.13% - electricity 2.0% 0.9 Total Heat Supplied 1.90% - heat 2.0% 0.5 Tertiary Industry Electricity appliances 1.42% - electricity 2.0% 0.9 Total Heat Supplied 1.80% - proces heat 2.0% 0.9 Industry Transport Electricity appliances 1.42% - passenger 1.0% 1.0 Total Process energy 1.87% - freight 0.7% 1.0 - fishery 1.0% 1.0 - agriculture 1.0% 1.0 Discount rate for calculating capital costs 5% 24 DTU Management Engineering, Technical University of Denmark

Costs of cars implemented in STREAM 0,3 Vehicle + Operational Costs ( € /km) Ethanol 0,25 Biodiesel Methanol 0,2 UPGR Biogas EV >500 km 0,15 H2 FCV 0,1 2015 2020 2025 2030 2035 2040 2045 2050 25 DTU Management Engineering, Technical University of Denmark