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MODELLING OF THE EU LONG-TERM STRATEGY TOWARDS A CARBON NEUTRAL ENERGY SYSTEM A. De Vita, Prof. P. Capros, G. Zazias, et al. Dresden, 12 April, 2019 The presentation reflects purely personal opinions M ODELLING SUITE FOR EU L ONG - TERM STRATEGY

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  1. MODELLING OF THE EU LONG-TERM STRATEGY TOWARDS A CARBON NEUTRAL ENERGY SYSTEM A. De Vita, Prof. P. Capros, G. Zazias, et al. Dresden, 12 April, 2019 The presentation reflects purely personal opinions

  2. M ODELLING SUITE FOR EU L ONG - TERM STRATEGY

  3. PRIMES energy system model PRIMES Overview PRIMES MODEL OVERVIEW AIM: • Simulate structural changes and long-term transitions Model structure: • Modular system: one module per sector • Microeconomic foundation with engineering representations Focus: • Market-related mechanisms • Representation of policy instruments for market, energy and emissions , for policy impact assessment Technology database: • Energy technology database has a standard format and is open access Temporal resolution : to 2070, in 5-year time steps Geographic resolution : 28 EU MS + 10 European non-EU countries Mathematically : concatenation of mixed-complementarity problems with equilibrium conditions and overall constraints (e.g. carbon constraint with associated shadow carbon value) - EPEC

  4. Going from 2°C to 1.5°C Remaining emissions in 2°C T HE C HALLENGE TOWARDS CARBON NEUTRALITY IN 2050 AND BEYOND • In 2050, 1100 Mt GHG (-80% compared to 1990 levels) are consistent with a 2°C GHG Emissions remaining in 2050 Non-CO2 1,400 trajectory Mt CO2-eq. Non-energy CO2 1,200 Power and Heat • By 2050, the remaining GHG (in a EUCO Energy branch 1,000 scenario) are 58% due to energy, of which: Transport 800 • 31% in transport 600 • 20% in stationary use Buildings Industry 400 • Power and heat and energy branch account 200 for 9% - • The challenge is to bring emissions close to zero -53% • ~80-85% in 2050 in a 2°C context -67% -76% -85% -81% -86% • ~92-94% in 2050 in a 1.5°C context -97% • Is it possible? • How? When? At which cost? GHG Emissions reduction 2005-2050

  5. No-regret options Disruptive options S TORYLINE A. Reduce energy demand in all sectors beyond conventional energy savings , e.g. circular economy, Prosumers sharing of vehicles, materials sequestering CO 2 B. Changes in the way users use energy , e.g. extreme Advanced electrification in industry and transport, direct use of sustainable distributed hydrogen biofuels C. Changes in the production and nature of energy Use nuclear and commodities , e.g.: CCS where i. e.g. mix hydrogen and biogas in gas distribution acceptable ii. replace fossil gas by renewable gas • Private transport in Electrification of urban environments iii. fossil liquids by synthetic fuels (electro-fuels from transport and heating • Heat pump in warmer hydrogen and captured or biogenic CO 2 ) climates D. Use and storage of CO 2 • Investment in renewables Enhanced renewable power i. establish circuits of CO 2 capturing • Reliable generation integration of ii. use and sequestering in storage areas, materials and/or renewables fuels, e.g. CO 2 captured in industrial processes used in Energy efficiency effort in ammonia or petrochemicals, replacing reforming of fossil buildings, equipment and fuels, biomass CCS and CO 2 capture from the air vehicles

  6. A LTERNATIVE P ATHWAYS -I LLUSTRATION

  7. Pros and cons LOGIC OF SCENARIOS Max Efficiency & Maximum Hydrogen as a Clean e-gas and e- Circular Economy Electrification carrier liquids Environment-friendly High efficiency in end-use Use of existing infrastructure PROS Can cover all end-uses including Reduces costs transport Convenience-cleanness Convenience in end-use: no Relaxes investment and disruption in transport Chemical storage of electricity resource constraints in the Can be self-produced supply side Chemical storage of electricity Less expensive and less Implies relatively small growth electricity intensive than e-fuels Positive economic and jobs of demand for electricity Competition among carriers impacts New infrastructure for Uncertainty about investment CO 2 capture from air and distribution and storage by individuals Not fully applicable in all end- biogenic not yet mature uses, including in transport Uncertainty about economies of CONS Uncertainty about needed Uncertainty about future costs scale of electrolyzers disruptive changes in industry Lack of competition in the of e-fuels, need for very and circular economy supply of energy carriers as lack Blue hydrogen is attractive but significant learning and of choice for consumers depends on geological storage economies of scale of the Difficulty in inducing large modal industry producing e-fuels shifts in transport Without chemical storage Not fully convenient in some electricity storage cannot be energy uses Too high increase of total power Low demand growth seasonal generation challenging the discourages investment in Uncertain success of learning- potential of resources technology progress by-doing for fuel cells

  8. Key features S CENARIO DEFINITION Scenarios Targets for 2030 GHG target 2050 Main feature Transport sector BaU after 2030 BaU after 2030 Baseline No Max electrification ELEC Max hydrogen H2 E-fuels GHG free P2X -80% at least CO 2 -60% at least Max Energy EE Efficiency Circular economy, CIRC Achieved bio-energy Combination of COMBO -88% at least CO 2 -75% at least ELEC, H2, P2X and EE Same as COMBO but more ambitious 1.5TECH decarbonisation -95% Min. use of fossils Same as COMBO, plus CIRC, and more 1.5LIFE ambitious decarbonisation

  9. Emissions for 1.5°C T YPICAL GHG EMISSION PROFILE Power • Including LULUCF emission GHG Emi mission ons (MtCO2 O2-eq. Industry sink, the 1.5°C scenarios Transport achieve carbon neutrality 5058 5058 Tertiary of the EU by 2050 and Residential beyond 4629 4629 Non-CO2 4347 4347 Carbon Remo moval Technologies 4024 4024 • The carbon removal Net emi missions technologies are BioCCS 3544 3544 and CCU for sequestration in materials 2855 2855 • Negative emissions , albeit small in magnitude, 1894 1894 compensate for remaining GHG emissions in 2050, notably as non-CO 2 1011 1011 emissions in agriculture 509 509 and few fossils in energy 190 190 demand sectors and small remaining industrial- 2005 2005 2010 2010 2015 2015 2020 2020 2025 2025 2030 2030 2035 2035 2040 2040 2045 2045 2050 2050 process emissions

  10. 3000 3000 Capacity and mix of power generation Bioma mass with CCS P OWER SECTOR GW GW 2500 2500 Fo Fossil fuels with CCS • The energy efficiency scenarios 2000 2000 imply a minimum increase in the 1500 1500 Fossil fuels without Fo volume of power generation CCS 1000 1000 Nuclear despite electrification. Among 500 500 the scenarios focusing on the Other renewables 0 supply sector, the maximum electricity scenario is the most Solar efficient regarding total Wind electricity generation. 2015 2015 2030 2030 2050 2050 • The e-fuel scenarios imply a 9000 9000 considerable increase in total TWh Biomass wi with CCS 8000 8000 power generation, up to almost 7000 7000 Fossil fuels with CCS a doubling of total volume. 6000 6000 • Both solar and wind deploy Fossil fuels without CCS 5000 5000 4000 4000 massively in all strategy Nuclear 3000 3000 scenarios. Sensitivity analysis 2000 2000 Other RES showed that ensuring sufficient 1000 1000 RES supply in the e-fuel Biomass wi without CCS 0 scenarios require unobstructed Hydro access to remotely located RES Solar from all places in the EU grid. 2010 2010 2015 2015 2030 2030 2050 2050 Wind

  11. RES and Storage P OWER SECTOR 90% • All decarbonisation scenarios foresee Shares in n pow ower gene neration on 80% huge deployment of RES in the power 70% sector (>80% in 2050) with variable RES 60% Renewables (all) getting a share above 70% in 2050. 50% Wind d & Solar • Storage occupies an increasing place in 40% Nuclear ensuring flexibility in the system; thus, 30% high development of electricity storage Fos ossil fuels 20% capacities in all strategy scenarios. 10% • Batteries alone are not sufficient, 0% 0% 2010 2015 2030 Baseline ne 2050 Deacarb. 2050 although the scenarios assume maximum integration of batteries in mobility, 900 350 TWh batteries in dispersed RES applications GW GW 800 300 and demand-response. 700 • The system will require significant 250 600 capacities of multi-day and seasonal 200 500 storage , which are possible via chemical 400 150 storage, primarily based on hydrogen. H2 & e-fue H2 uels 300 • The consumption of e-fuels in final 100 Batteries 200 demand provide considerably important 50 50 Pumping 100 indirect storage (not shown in the 0 0 figures) thanks to the fuel storage 2030 Baseline EE EE CIRC ELEC H2 H2 P2X COMBO 1.5TECH 1.5LIFE 2030 Baseline EE EE CIRC ELEC H2 H2 P2X COMBO 1.5TECH 1.5LIFE facilities in fuel distribution. • The simulations show that the system reaches economic optimality when 2050 2050 maximizing hydrogen and e-fuel consumption at times of high variable RES, with lowest marginal system costs, due to the excess of RES.

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