European electricity sector decarbonization under different levels of foresight

Abstract The European Union has set out to reduce the carbon intensity of its electricity generation substantially, as defined in the European Roadmap 2050. This paper analyses the impact of foresight towards decarbonization targets on the investment decisions in the European electricity sector using a specific model developed by the authors called dynELMOD. Incorporating the climate targets makes the investment into any additional fossil capacity uneconomic from 2025 onwards, resulting in a coal and natural gas phase-out in the 2040s. Limited foresight thus results in stranded investments of fossil capacities in the 2020s. Using a CO2 budgetary approach, on the other hand, leads to an even sharper emission reduction in the early periods before 2030, reducing overall costs. We also find that renewables carry the major burden of decarbonization; nuclear power (3rd or 4th generation) is unable to compete with other fuels and will, therefore, be phased out over time.

[1]  G. Pleßmann,et al.  How to meet EU GHG emission reduction targets? A model based decarbonization pathway for Europe's electricity supply system until 2050 , 2017 .

[2]  Alexander Zerrahn,et al.  A Greenfield Model to Evaluate Long-Run Power Storage Requirements for High Shares of Renewables , 2015 .

[3]  Jan Richter,et al.  DIMENSION - A Dispatch and Investment Model for European Electricity Markets , 2011 .

[4]  David B. Richardson,et al.  Electric vehicles and the electric grid: A review of modeling approaches, Impacts, and renewable energy integration , 2013 .

[5]  W. D’haeseleer,et al.  Myopic optimization models for simulation of investment decisions in the electric power sector , 2016, 2016 13th International Conference on the European Energy Market (EEM).

[6]  Paul L. Joskow,et al.  The Future of Nuclear Power After Fukushima , 2012 .

[7]  Florian Steinke,et al.  Grid vs. storage in a 100% renewable Europe , 2013 .

[8]  Roman Mendelevitch,et al.  European Scenarios of CO2 Infrastructure Investment , 2016 .

[9]  Thomas de Quincey.  [C] , 2000, The Works of Thomas De Quincey, Vol. 1: Writings, 1799–1820.

[10]  D. McCollum,et al.  Stranded on a low-carbon planet: Implications of climate policy for the phase-out of coal-based power plants , 2015 .

[11]  W. Schill,et al.  Long-run power storage requirements for high shares of renewables: Results and sensitivities , 2017 .

[12]  Adam Hawkes,et al.  Energy systems modeling for twenty-first century energy challenges , 2014 .

[13]  Clemens Gerbaulet,et al.  Power System Impacts of Electric Vehicles in Germany: Charging with Coal or Renewables? , 2015 .

[14]  Claudia Kemfert,et al.  On the economics of electrical storage for variable renewable energy sources , 2018, European Economic Review.

[15]  Christian Breyer,et al.  On the role of solar photovoltaics in global energy transition scenarios , 2016 .

[16]  Casimir Lorenz.  Balancing reserves within a decabonized European electricity System in 2050 — From market developments to model insights , 2017, 2017 14th International Conference on the European Energy Market (EEM).

[17]  François Lévêque,et al.  Revisiting the Cost Escalation Curse of Nuclear Power: New Lessons from the French Experience , 2013 .

[18]  K. Blok,et al.  Response to ‘Burden of proof: A comprehensive review of the feasibility of 100% renewable-electricity systems’ , 2017, Renewable and Sustainable Energy Reviews.

[19]  Daniel M. Kammen,et al.  Energy storage deployment and innovation for the clean energy transition , 2017, Nature Energy.

[20]  Dietmar Lindenberger,et al.  The role of grid extensions in a cost-efficient transformation of the European electricity system until 2050 , 2013 .

[21]  Garvin A. Heath,et al.  End of Life Management: Solar Photovoltaic Panels , 2016 .

[22]  I. MacGill,et al.  Comparing least cost scenarios for 100% renewable electricity with low emission fossil fuel scenarios in the Australian National Electricity Market , 2014 .

[23]  David Kleinhans,et al.  A European Perspective: Potential of Grid and Storage for Balancing Renewable Power Systems , 2016 .

[24]  C. Breyer,et al.  Global energy storage demand for a 100% renewable electricity supply , 2014 .

[25]  David Kleinhans,et al.  Integration of Renewable Energy Sources in future power systems: The role of storage , 2014, 1405.2857.

[26]  Casimir Lorenz,et al.  dynELMOD: A Dynamic Investment and Dispatch Model for the Future European Electricity Market , 2017 .

[27]  M. A. Cameron,et al.  The United States can keep the grid stable at low cost with 100% clean, renewable energy in all sectors despite inaccurate claims , 2017, Proceedings of the National Academy of Sciences.

[28]  Michaela Fürsch,et al.  Decarbonizing Europe's power sector by 2050 — Analyzing the economic implications of alternative decarbonization pathways , 2013 .

[29]  Heinz Stigler,et al.  ATLANTIS: techno-economic model of the European electricity sector , 2016, Central Eur. J. Oper. Res..

[30]  M. Haller,et al.  Fluctuating renewables in a long-term climate change mitigation strategy , 2011 .

[31]  M. Haller,et al.  Decarbonization scenarios for the EU and MENA power system: Considering spatial distribution and short term dynamics of renewable generation , 2012 .

[32]  Patrick Jochem,et al.  Reducing computing time of energy system models by a myopic approach , 2014 .

[33]  Mark Z. Jacobson,et al.  100% clean and renewable wind, water, and sunlight (WWS) all-sector energy roadmaps for the 50 United States , 2015 .

[34]  W. Winiwarter,et al.  EU Reference Scenario 2016 - Energy, transport and GHG emissions Trends to 2050. , 2016 .

[35]  Paul Denholm,et al.  Grid flexibility and storage required to achieve very high penetration of variable renewable electricity , 2011 .

[36]  Christoph Weber,et al.  The future of the European electricity system and the impact of fluctuating renewable energy – A scenario analysis , 2014 .

[37]  P. Alam.  ‘W’ , 2021, Composites Engineering.

[38]  Albert Moser,et al.  Large-scale Integration of Renewable Energies and Impact on Storage Demand in a European Renewable Power System of 2050☆ , 2015 .

[39]  Mark Z. Jacobson,et al.  A Monte Carlo approach to generator portfolio planning and carbon emissions assessments of systems with large penetrations of variable renewables. , 2011 .

[40]  P. Alam.  ‘A’ , 2021, Composites Engineering: An A–Z Guide.

[41]  W. Winiwarter,et al.  EU Energy, Transport and GHG Emissions: Trends to 2050, Reference Scenario 2013 , 2013 .

[42]  Arnulf Grubler,et al.  The costs of the French nuclear scale-up: A case of negative learning by doing , 2010 .

[43]  Brigitte Knopf,et al.  Quantifying the Long�?Term Economic Benefits of European Electricity System Integration , 2014 .

[44]  Pao-Yu Oei,et al.  Emission Pathways Towards a Low-Carbon Energy System for Europe: A Model-Based Analysis of Decarbonization Scenarios , 2018 .

[45]  M. A. Cameron,et al.  Matching demand with supply at low cost in 139 countries among 20 world regions with 100% intermittent wind, water, and sunlight (WWS) for all purposes , 2018, Renewable Energy.

[46]  F. Kunz,et al.  Current and Prospective Costs of Electricity Generation until 2050 , 2013 .

[47]  P. Alam.  ‘K’ , 2021, Composites Engineering.

[48]  Gorjan Alagic,et al.  #p , 2019, Quantum information & computation.

[49]  Tom Brown,et al.  Cost-Optimal Power System Extension under Flow-Based Market Coupling , 2014 .

[50]  Dominik Möst,et al.  Renewable energy sources in European energy supply and interactions with emission trading , 2010 .

[51]  F. Graf,et al.  Renewable Power-to-Gas: A technological and economic review , 2016 .

[52]  Brian Vad Mathiesen,et al.  Smart Energy Europe: The technical and economic impact of one potential 100% renewable energy scenario for the European Union , 2016 .

[53]  F. Cebullaa,et al.  Electrical energy storage in highly renewable European energy systems : capacity requirements , spatial distribution , and storage dispatch , 2017 .

[54]  Tobias Naegler,et al.  Electrical energy storage in highly renewable European energy systems: Capacity requirements, spatial distribution, and storage dispatch , 2017 .

[55]  Alexander Zerrahn,et al.  On the Representation of Demand-Side Management in Power System Models , 2015 .

[56]  Lion Hirth,et al.  The Optimal Share of Variable Renewables: How the Variability of Wind and Solar Power affects their Welfare-optimal Deployment , 2012 .

[57]  Christian von Hirschhausen,et al.  Designing a Model for the Global Energy System—GENeSYS-MOD: An Application of the Open-Source Energy Modeling System (OSeMOSYS) , 2017 .

[58]  F. Johnsson,et al.  Linkages between demand-side management and congestion in the European electricity transmission system , 2014 .

[59]  Pantelis Capros,et al.  Description of models and scenarios used to assess European decarbonisation pathways , 2014 .

[60]  Martin Greiner,et al.  Storage and balancing synergies in a fully or highly renewable pan-European power system , 2012 .

[61]  Wolf-Peter Schill,et al.  Power System Impacts of Electric Vehicles in Germany: Charging with Coal or Renewables? , 2015 .

[62]  I. Keppo,et al.  Short term decisions for long term problems – The effect of foresight on model based energy systems analysis , 2010 .

[63]  W. Schill,et al.  Power-to-heat for renewable energy integration: A review of technologies, modeling approaches, and flexibility potentials , 2018 .