Sustainable Technology and Economic Pathways for Electrified mobility systems in EU-27 by 2030: mid-term status

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Sustainable Technology and Economic Pathways for Electrified mobility systems in EU-27 by 2030: mid-term status EV-STEP 06FEBRUARY 2014 Edi Assoumou, ARMINES CMA, FR Markus Blesl, IER Stuttgart, DE Poul Erik Grohnheit, RISOE-DTU, DK Frédéric Ghersi, SMASH, FR

Outline Mid-term status and overview of R&D activities Pan European TIMES model IMACLIM-P model Complementary analyses 2

Mid-term status: consortium life o EV-STEP s aim(kd1): long-term socio-economic analysis of electric mobility in Europe by 2030 and 2050. o An enriching collaborative experience o With some challenges other the past period Organizational challenges Effective start Managing key persons departure and replacement Scientific challenges Models updates to EU-28 Evolution of the state of the art related to electromobility MID-TERM STATUS: CONSORTIUM AND R&D ACTIVITIES 3

Mid-term status: R&D activities in KD1 o EV-STEP s core focus: o Technical assessment TIMES pan EU 28 Updated transport and mobility description Preliminary scenarios runs o Economic impact IMACLIM-P EU 28 Linkage specification o Complementary analyses Local scale differences in mobility patterns MID-TERM STATUS: CONSORTIUM AND R&D ACTIVITIES Negative electricity prices 4

Outline Mid-term status and overview of R&D activities Pan European TIMES model IMACLIM-P model Complementary analyses 5

The Pan-European TIMES model o A technology oriented bottom-up model with: PAN EU MODEL 31 regions (EU 28 + NO, CH, IS) Time horizon: 2000-2050 12 time slices (4 seasonal, 3 day levels) GHG: CO2, CH4, N2O, SF6 Others pollutants: SO2, NOx, CO, NMVOC, PM2.5, PM10 o Providing a partial equilibrium of the energy systems and based on a cost minimization approach 6

Improved transport concepts in PEM Technology Battery electric vehicle (BEV) Fuel cell vehicle (FCEV) Fuel cell hybrid electric vehicle (FCHEV) Hybrid electric vehicle (HEV) Plug-in-Hybrid (PHEV) Fuel Energy storage Engine Characteristic Electricity Battery Electric engine Vehicle movement with electric engine and electricity as fuel Hydrogen Hydrogen Electric engine Electricity for vehicle storage movement produced by (gaseous at 700 fuel cell from hydrogen bar or liquid at -253 C) Hydrogen Petrol/Gaso line (Diesel) Petrol/Gaso line (Diesel), Electricity Hydrogen storage (gaseous at 700 bar or liquid at -253 C), Battery Fuel tank, battery Fuel tank, battery Electric engine Combustion engine, electric engine Combustion engine, electric engine Same as FCEV, in addition a bigger battery for temporary storage of power, to balance the dynamic Inertia of the fuel cell Depending on the variety possibility to boost, recuperation of brake energy, purely electric drive Possibility of battery charging via electricity grid, combustion engine as an range-extender PAN EU MODEL 7

Improved transport concepts in PEM Passenger car 2010 2030 2050 Technical data Fuel Propulsion technologie/ Gasoline Drive technologie Combustion engine, electric engine Consumption [GJ/100km]* 0.0 0.0 0.0 Urban/ in town 0.192 0.159 0.135 Extra urban/ out of town 0.176 0.140 0.119 Combined 0.181 0.146 0.125 Lifetime/ Durability [a] 12 12 12 Economical data Investment costs [ /veh] 22.321 21.433 21.313 Fixed costs [ /(veh*a)] 446 429 426 Enviromental data CO2-emissions [g/km] 131 105 90 CH4-emissions [g/km] 0.008 0.008 0.006 CO emissions [g/km] 0.833 0.763 0.625 NOx-emissions [g/km] 0.067 0.052 0.042 NMVOC emissions [g/km] 0.075 0.046 0.037 Particle emissions [g/km] 0.000 0.000 0.000 Passenger car 2010 2030 2050 Fuel Propulsion technologie/ Drive technologie Consumption Technical data Electricity Electric engine [GJ/100km]* 0.0 0.0 0.0 Urban/ in town 0.055 0.049 0.044 Extra urban/ out of town 0.083 0.075 0.066 Combined 0.073 0.066 0.059 Lifetime/ Durability [a] 12 12 12 Economical data Investment costs [ /veh] 37.663 27.456 24.453 Fixed costs [ /(veh*a)] 753 549 489 Enviromental data CO2-emissions [g/km] CH4-emissions [g/km] CO emissions [g/km] NOx-emissions [g/km] NMVOC emissions [g/km] Particle emissions [g/km] PAN EU MODEL 8

Ev-step s assumptions and scenarios map o 5 scenarios to be fine-tuned PAN EU MODEL REF: a reference scenario with only ETS as instrument REF+: REF scenario with a renewable target for electricity EV_current: REF+ with national EV targets. EV_ambitious: REF+ with EVI sales shares for 2050 Em_Obj: A scenario with only 2050 CO2 target o Underlying social economical assumptions 2010 2015 2020 2025 2030 2040 2050 Population m 497 499 500 500 499 491 476 0,1% 0,0% 0,0% 0,0% -0,2% -0,3% GDP 12 2007 12,0 13,5 15,1 16,5 17,9 20,9 24,5 2,4% 2,1% 1,8% 1,7% 1,6% 1,6% 9

4000 3500 Preliminary results: Ev_current CO2 EU-28 International Aviation PAN EU MODEL Emissions of CO2 [Mio t] 3000 2500 2000 1500 1000 500 Transport (without int. Aviation Agriculture Commercial Residential Industry Conversion, production 0 10

18000.0 Preliminary results: Ev_current FEC transport PAN EU MODEL 16000.0 14000.0 12000.0 10000.0 8000.0 6000.0 4000.0 Navigation Aviation Train freight Train passenger Motorcycle Truck Bus Car 2000.0 0.0 2010 2015 2020 2025 2030 2035 2040 2045 2050 11

Preliminary results: Ev_current FEC transport FEC of Car in PJ Electricity PAN EU MODEL 8000 Natural Gas Biogas 7000 Hydrogen compressed 6000 Hydrogen liquified Methanol fossil 5000 Methanol bio Dimethyleter fossil 4000 Dimethyleter bio 3000 FT-Fuel fossil FT-Fuel bio 2000 Ethanol Biodiesel 1000 LPG 0 2010 2015 2020 2025 2030 2035 2040 2045 2050 Gasoline Diesel 12

Preliminary results: Ev_current Elec supply EU28 3500 Electricity storage (excl. pump storage) Net Imports PAN EU MODEL Net electricity [TWh] 3000 2500 2000 1500 1000 Others / Waste non-ren. /Ind. Waste Heat Other Renewables Biomass / Waste ren. Solar Wind offshore Wind onshore Hydro (incl. pump storage) Nuclear Gas CCS Gas w/o CCS Oil 500 Lignite CCS Lignite w/o CCS 0 2010 2015 2020 2025 2030 2035 2040 2045 2050 Coal CCS Coal w/o CCS 13

Outline Mid-term status and overview of R&D activities Pan European TIMES model IMACLIM-P model Complementary analyses 14

The IMACLIM-P model o A recursive, computable general equilibrium model: Exogenous growth through labour productivity improvements with constant savings rate IMACLIM-P MODEL Endogenously split between domestic and imported goods EU28 as a whole, horizon and time steps consistent with PEM Balanced economic flows of 11 goods, labour and capital Exogenous firms input and households consumption trade-offs 15

Data requirements Building hybrid input-output tables that reconcile national accounting and energy balance data IMACLIM-P MODEL o 2008 national accounting data: main source EUROSTAT EU27 tables only at basic prices. Need to build tables at purchaser s prices from 27 MS tables (! Quite unexpected workload) Croatia imported from GTAP database, year 2004, scaled up according to GDP (EUROSTAT) o 2008 energy data: main source IEA Detailed EU28 energy balances Energy price data from ENERDATA and EUROSTAT 16

The IMACLIM-P model: work progress o Modelling KLEM structure of the model operational IMACLIM-P MODEL o Data collection and formatting EU28 energy balance treated Data of automobile production and imports collected IO tables constructed for all MSs o Linkage with PEM: Specification of goods and inheritance of trade-offs 17

Outline Mid-term status and overview of R&D activities Pan European TIMES model IMACLIM-P model Complementary analyses 18

Local differences in mobility patterns o Challenge1: mobility patterns & load curve Illustration of a potential 10% Ev case impact on hourly load curve COMPLEMENTARY ANALYSES Source: JRC 2013, Pasaoglu et al, Projections for Electric Vehicle Load Profiles in Europe Based on Travel Survey Data More crucial at local level 19

Geographic variabilities in mobility patterns o Ev-step s response: the RECAM platform Test case for Paris IDF region Mobility Scheduling Macro mobility data Driving Patterns Model Command System Decentralized Command Signals Constrained command signals (on/off) COMPLEMENTARY ANALYSES Outputs Power constraints Max KW Peak (t) Max KW non Recharging Decision Charging infrastructure Optimal Charging Number of Ok trips % trip satisfaction P(t,trip) & CostEV(trip) SOC (t) Energy System Energy system projection Electrcity costs and CO2 contents Charging behavior Minimum SOC Weekly number of charging events 20

Negative electricity prices o Challenge2: Electric vehicle and renewable Country scale illustration with negative prices in Germany COMPLEMENTARY ANALYSES Source: Quarterly Report on European Electricity Markets DG Energy 2013 o Ev-step s response: a dedicated test case for Germany with a 8760 time slices TIMES model Source: Johannes Mayer 2014, Fraunhofer Institute for Solar Energy Systems; Data: EEX 21