How costs affect deployment of low carbon technologies - analysis with JRC-EU-TIMES


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How costs affect deployment of low carbon technologies - analysis with JRC-EU-TIMES

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How costs affect deployment of low carbon technologies - analysis with JRC-EU-TIMES

  1. 1. Joint Research Centre the European Commission's in-house science service How costs affect deployment of low carbon technologies - analysis with JRC-EU- TIMES Wouter Nijs Institute for Energy and Transport - Energy Technology Policy Outlook Unit
  2. 2. • Energy research and innovation R&I are key for achieving a low-carbon transition and a fundamental building block of the Energy Union. • Objective of this research Provide insights for better targeting of R&I efforts by exploring the impact of techno-economic assumptions of low carbon energy supply technologies (in PPT: focus on RES-e and CCS) Introduction and rationale
  3. 3. Model landscape JRC IET - Energy Technology Policy Outlook Unit (ETPO) Energy System Optimisation (JRC-EU-TIMES) Asset Optimisation Price Taker Models (SPIRIT) Energy Services Demand (GEM-E3) Power System Unit Commitment (Dispa-SET) Weather / Demand Statistical Models 3 Land use & forestry (LUISA, CBM, GFTM) Regional Holistic Global Equilibrium (RHOMOLO) IET model Other JRC Hydrology (LISFLOOD) Global Energy (TIMES-TIAM) BIO- MASS2 WATER- FLEX3 ERIBE- LAND1 1) Project IET/IES/IPTS 2) Project IET/IES/IPTS 3) Proposal IET/IES (tbd) JRCTIMESTRADE
  4. 4. • Technology rich bottom up energy system optimisation (partial equilibrium) model based on the TIMES model generator of the IEA for EU28, CH, IS, NO + Western Balkans • Designed for analysing the role of energy technologies and their innovation for meeting Europe's energy and climate change related policy objectives • Model owned and operated by the JRC • Model horizon: 2010-2050 (2075) Available at: ory/handle/111111111/30469 JRC-EU-TIMES in a nutshell
  5. 5. Objective • Minimise total energy system costs Constraints • Demand and supply balances by country and sector • Capacity limits • Renewable and emission targets • … Energy service demands Resource availabilities and costs Sectoral costs and price proxies (by country, energy carrier, technology) Supply and demand technologies Emissions Techno- economic assumptions Modelling approach Material and energy flows AlignedtolatestEU EnergyReference Scenarios Policies (GHG and energy target, subs.) ETRI
  6. 6. JRC-EU-TIMES model extensions Improved RES-e potentials Other improvementsModel coupling Recalibration and model updates Coupling with other JRC models Updated biomass potential Updated solar potential with explicit representation of land use Updated wind potential Such as • Monte Carlo runs • Include retrofit options • Include biogas blending New base year 2010+ Explicit representation of insulation options in buildings
  7. 7. Bioenergy in the JRC-EU-TIMES Potentials • Agriculture (CAPRI) • Roundwood and forestry residues (EFISCEN + now: CBM GFTM) • Waste (Eurostat statistics linked to population and GDP) Scenarios • Differ in land use, agricultural practices, and protected areas. Source: "The JRC-EU-TIMES model. Bioenergy potentials for EU and neighbouring countries." Model result Biomass demand is high and almost insensitive under a 80% CO2 reduction target and the assumption of carbon neutrality. 2050 potentials (PJ)
  8. 8. Assumptions on energy and climate targets
  9. 9. • Investing 12 B€ per year in PV R&D could be cost- effective if this reduces PV cost to 450-500 €/kW, cet. paribus • PV cost is vital for PV deployment and for the energy system cost in a cost optimal low carbon energy system How do costs affect PV deployment in EU28 ? SET Plan Conference 2015
  10. 10. Every 100€/kW PV cost reduction adds 30GW in 2030 and 85GW in 2050
  11. 11. A bigger exercise: 50 scenarios !
  12. 12. The case of Geothermal: CAPEX evolution and share in power production
  13. 13. No CCS leads to double Geothermal generation Geothermal power production in 2050 (TWh) Most countries still well below 50% of the economic potential that is based on 100 EUR/MWh LCOE
  14. 14. Further demonstration of the outputs • Electricity production in TWh • Installed capacity in GW • CAPEX requirements in EUR billion • Energy related CO2 emissions in Mt for scenarios: CAP, NOCCS, NOPEC + technology sensitivities
  15. 15. Conclusions (1) • Technology interactions, sensitivities and possible future investments are valuable outputs for targeting of R&I efforts • Capital intensive technologies are more sensitive • Technology interactions and competition are crucial, even in a low carbon energy system • Key technologies exist for cross technology sensitivity within the power sector: CCS, Bio-CCS and geothermal. • Without CCS, the indirect use of power (Power2Gas) from variable RES becomes important • Breakthrough levels have been defined for ocean and CSP
  16. 16. Conclusions (2) • Using savings in the total energy system cost as a proxy for a possible R&I budget is powerful although partial: • Ceteris paribus (other techs don't move) • No link between R&I and technology improvement. • When results of JRC-EU-TIMES were deviating from isolated cost analysis, the cause was often different commodity prices • Uncovered but on the wish list: • Extend analysis to demand technologies and storage • Combinations to overcome single technology sensitivity.
  17. 17. Thank you for your attention! • • +31 22456 5481 2.+31 22456 5037 4.+31 22456 5150
  18. 18. Stay in touch JRC Science Hub: Twitter: @EU_ScienceHub YouTube: JRC Audiovisuals Facebook: EU Science Hub – Joint Research Centre LinkedIn: Joint Research Centre (JRC) - European Commission's Science Service
  19. 19. • Assessing the impacts of technology improvements on the deployment of marine energy in Europe with an energy system perspective • Assessing the role of electricity storage in EU28 until 2050 • Decarbonised pathways for a low carbon EU28 power sector until 2050 • The effect of limited renewable resources on the electricity generation in a low- carbon europe • How far away is hydrogen? Its role in the medium and long-term decarbonisation of the European energy system • Improved representation of the European power grid in long term energy system models: case study of JRC-EU-TIMES • The JRC-EU-TIMES model - Assessing the long-term role of the SET Plan Energy technologies • The JRC-EU-TIMES model. Bioenergy potentials for EU and neighbouring countries • Supporting the deployment of selected low-carbon technologies in Europe: Implications of techno-economic assumptions. An energy system perspective with the JRC-EU-TIMES model Recent publications