01_JRC-EU-TIMES Full model

Link to zipped Excel files

Methodology report for comparing the JRC-EU-TIMES and EnergyPLAN

JRC-EU-TIMES model outputs for the 14 MS and the EU for the project Heatroadmap 2050

Energy Technology Reference Indicators

Technical report with detailed description of the methodology

Technical report describing the first set of biomass potentials included in the model

ENSPRESO - an open data, EU-28 wide, transparent and coherent database of wind, solar and biomass energy potentials

Technical report on inputs for heating and cooling sector

Technical report describing wind potentials inputs

European Meteorological derived High Resolution RES generation time series, used for parametrisation of variable RES in JRC-EU-TIMES

The JRC Integrated Database of the European Energy System

Power-to-Methane (PtM) can provide flexibility to the electricity grid while aiding decarbonization of other sectors. This study focuses specifically on the methanation component of PtM in 2050. Scenarios with 80–95% CO2 reduction by 2050 (vs. 1990) are analyzed and barriers and drivers for methanation are identified. PtM arises for scenarios with 95% CO2 reduction, no CO2 underground storage and low CAPEX (75 €/kW only for methanation). Capacity deployed across EU is 40 GW (8% of gas demand) for these conditions, which increases to 122 GW when liquefied methane gas (LMG) is used for marine transport. The simultaneous occurrence of all positive drivers for PtM, which include limited biomass potential, low Power-to-Liquid performance, use of PtM waste heat, among others, can increase this capacity to 546 GW (75% of gas demand). Gas demand is reduced to between 3.8 and 14 EJ (compared to ∼20 EJ for 2015) with lower values corresponding to scenarios that are more restricted. Annual costs for PtM are between 2.5 and 10 bln€/year with EU28’s GDP being 15.3 trillion €/year (2017). Results indicate that direct subsidy of the technology is more effective and specific than taxing the fossil alternative (natural gas) if the objective is to promote the technology. Studies with higher spatial resolution should be done to identify specific local conditions that could make PtM more attractive compared to an EU scale.

Hydrogen represents a versatile energy carrier with net zero end use emissions. Power-to-Liquid (PtL) includes the combination of hydrogen with CO2 to produce liquid fuels and satisfy mostly transport demand. This study assesses the role of these pathways across scenarios that achieve 80–95% CO2 reduction by 2050 (vs. 1990) using the JRC-EU-TIMES model. The gaps in the literature covered in this study include a broader spatial coverage (EU28+) and hydrogen use in all sectors (beyond transport). The large uncertainty in the possible evolution of the energy system has been tackled with an extensive sensitivity analysis. 15 parameters were varied to produce more than 50 scenarios. Results indicate that parameters with the largest influence are the CO2 target, the availability of CO2 underground storage and the biomass potential. Hydrogen demand increases from 7 mtpa today to 20–120 mtpa (2.4–14.4 EJ/yr), mainly used for PtL (up to 70 mtpa), transport (up to 40 mtpa) and industry (25 mtpa). Only when CO2 storage was not possible due to a political ban or social acceptance issues, was electrolysis the main hydrogen production route (90% share) and CO2 use for PtL became attractive. Otherwise, hydrogen was produced through gas reforming with CO2 capture and the preferred CO2 sink was underground. Hydrogen and PtL contribute to energy security and independence allowing to reduce energy related import cost from 420 bln€/yr today to 350 or 50 bln€/yr for 95% CO2 reduction with and without CO2 storage. Development of electrolyzers, fuel cells and fuel synthesis should continue to ensure these technologies are ready when needed. Results from this study should be complemented with studies with higher spatial and temporal resolution. Scenarios with global trading of hydrogen and potential import to the EU were not included.

Data on the potential generation of energy from wind, solar and biomass is crucial for analysing their development, as it sets the limits on how much additional capacity it is feasible to install. This paper presents the methodologies used for the development of ENSPRESO, ENergy System Potentials for Renewable Energy SOurces, an EU-28 wide, open dataset for energy models on renewable energy potentials, at national and regional levels for the 2010–2050 period. In ENSPRESO, coherent GIS-based land-restriction scenarios are developed. For wind, resource evaluation also considers setback distances, as well as high resolution geo-spatial wind speed data. For solar, potentials are derived from irradiation data and available area for solar applications. Both wind and solar have separately a potential electricity production which is equivalent to three times the EU's 2016 electricity demand, with wind onshore and solar requiring 16% and 1.4% of total land, respectively. For biomass, agriculture, forestry and waste sectors are considered. Their respective sustainable potentials are equivalent to a minimum 10%, 1.5% and 1% of the total EU primary energy use. ENSPRESO can enrich the results of any energy model (e.g. JRC-EU-TIMES) by improving its analyses of the competition and complementarity of energy technologies.

This report provides an outlook for a set of Low Carbon Energy Technologies as well as background on how JRC-EU-TIMES baseline and decarbonisation scenarios are derived. The results help inform decision makers on the technology choices through which the EU can meet its climate and energy goals under different global energy scenarios. The report also provides background for the technology specific results in the technology and market reports produced under the same AA.

Fuel cell electric vehicles (FCEV) currently have the challenge of high CAPEX mainly associated to the fuel cell. This study investigates strategies to promote FCEV deployment and overcome this initial high cost by combining a detailed simulation model of the passenger transport sector with an energy system model. The focus is on an energy system with 95% CO2 reduction by 2050. Soft-linking by taking the powertrain shares by country from the simulation model is preferred because it considers aspects such as car performance, reliability and safety while keeping the cost optimization to evaluate the impact on the rest of the system. This caused a 14% increase in total cost of car ownership compared to the cost before soft-linking. Gas reforming combined with CO2 storage can provide a low-cost hydrogen source for FCEV in the first years of deployment. Once a lower CAPEX for FCEV is achieved, a higher hydrogen cost from electrolysis can be afforded. The policy with the largest impact on FCEV was a purchase subsidy of 5 k€ per vehicle in the 2030–2034 period resulting in 24.3 million FCEV (on top of 67 million without policy) sold up to 2050 with total subsidies of 84 bln€. 5 bln€ of R&D incentives in the 2020–2024 period increased the cumulative sales up to 2050 by 10.5 million FCEV. Combining these two policies with infrastructure and fuel subsidies for 2030–2034 can result in 76 million FCEV on the road by 2050 representing more than 25% of the total car stock. Country specific incentives, split of demand by distance or shift across modes of transport were not included in this study.

The optimization energy system model JRC-EU-TIMES is used to support energy technology R & D design by analysing power technologies deployment till 2050 and their sensitivity to different decarbonisation exogenous policy routes. The policy routes are based on the decarbonised scenarios of the EU Energy Roadmap 2050 combining energy efficiency, renewables, nuclear or carbon capture and storage (CCS). A "reference" and seven decarbonised scenarios are modelled for EU28. We conclude on the importance of policy decisions for the

configuration of the low carbon power sector, especially on nuclear acceptance and available sites for new RES plants. Differently from typical analysis focussing on technology portfolio for each route, we analyse the deployment of each technology across policy routes, for optimising technology R & D. R & D priority should be given to those less-policy-sensitive technologies that are in any case deployed rapidly across the modelled time horizon (e.g. PV), but also to those deployed up to their technical potentials and typically less sensitive to

exogenous policy routes. For these ‘no regret’ technologies (e.g. geothermal), R & D efforts should focus on increasing their technical potential. For possibly cost-effective technologies very sensitive to the policy routes (e.g. CSP and marine), R & D efforts should be directed to improving their techno-economic performance.

This paper assesses how different levels of geographical disaggregation of wind and photovoltaic energy resources could affect the outcomes of an energy system model by 2020 and 2050. Energy system models used for policy making typically have high technology detail but little spatial detail. However, the generation potential and integration costs of variable renewable energy sources and their time profile of production depend on geographic characteristics and infrastructure in place. For a case study for Austria we generate spatially highly resolved synthetic time series for potential production locations of wind power and PV. There are regional differences in the costs for wind turbines but not for PV. However, they are smaller than the cost reductions induced by technological learning from one modelled decade to the other. The wind availability shows significant regional differences where mainly the differences for summer days and winter nights are important. The solar availability for PV installations is more homogenous. We introduce these wind and PV data into the energy system model JRC-EU-TIMES with different levels of regional disaggregation. Results show that up to the point that the maximum potential is reached disaggregating wind regions significantly affects results causing lower electricity generation from wind and PV.

Marine energy could play a significant role in the long-term energy system in Europe, and substantial resources have been allocated to research and development in this field. The main objective of this paper is to assess how technology improvements affect the deployment of marine energy in the EU. To do so the linear optimization, technology-rich model JRC-EU-TIMES is used. A sensitivity analysis is performed, varying technology costs and conversion efficiency under two different carbon-emissions paths for Europe: a current policy initiative scenario and a scenario with long-term overall CO2 emission reductions. We conclude that, within the range of technology improvements explored, wave energy does not become cost-competitive in the modelled horizon. For tidal energy, although costs are important in determining its deployment, conversion efficiency also plays a crucial role. Ensuring the cost-effectiveness of tidal power by 2030 requires efficiency improvements by 40% above current expectations or cost reductions by 50%. High carbon prices are also needed to improve the competitiveness of marine energy. Finally, our results indicate that investing 0.1–1.1 BEuro2010 per year in R&D and innovation for the marine power industry could be cost-effective in the EU, if leading to cost reduction or efficiency improvements in the range explored.

Hydrogen is a promising avenue for decarbonising energy systems and providing flexibility. In this paper, the JRC-EU-TIMES model – a bottom-up, technology-rich model of the EU28 energy system– is used to assess the role of hydrogen in a future decarbonised Europe under two climate scenarios, current policy initiative (CPI) and long-term decarbonisation (CAP). Our results indicate that hydrogen could become a viable option already in 2030 – however, a long-term CO2 cap is needed to sustain the transition. In the CAP scenario, the share of hydrogen in the final energy consumption of the transport and industry sectors reaches 5% and 6% by 2050. Low-carbon production technologies dominate, and electrolysers provide flexibility by absorbing electricity at times of high availability of intermittent sources. Hydrogen could also play a significant role in the industrial and transport sectors, while the emergence of stationary hydrogen fuel cells for hydrogen-to-power would require significant cost improvements, over and above those projected by the experts.

We analyse the impact of the current and an alternative stricter EU CO2 car legislation on transport related CO2 emissions, on the uptake of electric vehicles (EV), on the reduction of oil consumption, and on total energy system costs beyond 2020. We apply a TIMES based energy system model for Europe. Results for 2030 show that a stricter target of 70g CO2/km for cars could reduce total transport CO2 emissions by 5% and oil dependence by more than 2% compared to the current legislation. The stricter regulatory CO2 car target is met by a deployment of more efficient internal combustion engine cars and higher shares of EV Total system costs increase by less than 1%. The analysis indicates that EV deployment and the decarbonisation of the power system including higher shares of variable renewables can be synergistic. Our sensitivity analysis shows that the deployment of EV would sharply increase between 2020 and 2030 at learning rates above 12.5%, reaching shares above 30% in 2030. Finally, the study highlights that, besides legislating cars, policies for other transport sectors and modes are needed to curb transport related CO2 emission growth by 2030.