Trade-Offs between Geographic Scale, Cost, and Infrastructure Requirements for Fully Renewable Electricity in Europe

Summary The European potential for renewable electricity is sufficient to enable fully renewable supply on different scales, from self-sufficient, subnational regions to an interconnected continent. We not only show that a continental-scale system is the cheapest, but also that systems on the national scale and below are possible at cost penalties of 20% or less. Transmission is key to low cost, but it is not necessary to vastly expand the transmission system. When electricity is transmitted only to balance fluctuations, the transmission grid size is comparable to today’s, albeit with expanded cross-border capacities. The largest differences across scales concern land use and thus social acceptance: in the continental system, generation capacity is concentrated on the European periphery, where the best resources are. Regional systems, in contrast, have more dispersed generation. The key trade-off is therefore not between geographic scale and cost, but between scale and the spatial distribution of required generation and transmission infrastructure.

[1]  Bruno Sudret,et al.  Global sensitivity analysis using polynomial chaos expansions , 2008, Reliab. Eng. Syst. Saf..

[2]  S. Pfenninger,et al.  Using bias-corrected reanalysis to simulate current and future wind power output , 2016 .

[3]  Jaeger-Waldau Arnulf,et al.  ETRI 2014 - Energy Technology Reference Indicator projections for 2010-2050 , 2014 .

[4]  G. Giebel,et al.  Europe's onshore and offshore wind energy potential : An assessment of environmental and economic constraints , 2009 .

[5]  Loic Le Gratiet,et al.  Metamodel-based sensitivity analysis: polynomial chaos expansions and Gaussian processes , 2016, 1606.04273.

[6]  Tom Brown,et al.  Optimal heterogeneity in a simplified highly renewable European electricity system , 2017, 1706.00463.

[7]  Antonella Battaglini,et al.  Regional integration to support full renewable power deployment for Europe by 2050 , 2011 .

[8]  Tom Brown,et al.  The role of hydro power, storage and transmission in the decarbonization of the Chinese power system , 2018, Applied Energy.

[9]  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.

[10]  Stefan Pfenninger,et al.  Calliope: a multi-scale energy systems modelling framework , 2018, J. Open Source Softw..

[11]  M. Jacobson,et al.  World estimates of PV optimal tilt angles and ratios of sunlight incident upon tilted and tracked PV panels relative to horizontal panels , 2018, Solar Energy.

[12]  Martino Pesaresi,et al.  GHS population grid, derived from GPW4, multitemporal (1975, 1990, 2000, 2015) , 2015 .

[13]  Mark Z. Jacobson,et al.  100% Clean and Renewable Wind, Water, and Sunlight All-Sector Energy Roadmaps for 139 Countries of the World , 2017 .

[14]  Johan Lilliestam,et al.  Shades of green: Centralisation, decentralisation and controversy among European renewable electricity visions , 2016 .

[15]  Stefan Pfenninger,et al.  Dealing with multiple decades of hourly wind and PV time series in energy models: A comparison of methods to reduce time resolution and the planning implications of inter-annual variability , 2017 .

[16]  Tom Brown,et al.  The role of spatial scale in joint optimisations of generation and transmission for European highly renewable scenarios , 2017, 2017 14th International Conference on the European Energy Market (EEM).

[17]  Jeff Dean,et al.  Time Series , 2009, Encyclopedia of Database Systems.

[18]  A. Patt,et al.  WACC the Dog: The Effect of Financing Costs on the Levelized Cost of Solar PV Power , 2013 .

[19]  J. Lilliestam,et al.  Home-made or imported: On the possibility for renewable electricity autarky on all scales in Europe , 2019, Energy Strategy Reviews.

[20]  Tom Brijs,et al.  An overview of large-scale stationary electricity storage plants in Europe: Current status and new developments , 2015 .

[21]  Tobias S. Schmidt,et al.  A dynamic analysis of financing conditions for renewable energy technologies , 2018, Nature Energy.

[22]  Albert Moser,et al.  Optimal Allocation and Capacity of Energy Storage Systems in a Future European Power System with 100% Renewable Energy Generation , 2014 .

[23]  C. Amante,et al.  ETOPO1 arc-minute global relief model : procedures, data sources and analysis , 2009 .

[24]  Wolf Fichtner,et al.  Cost-potentials for large onshore wind turbines in Europe , 2015 .

[25]  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 .

[26]  Estimating the cost of capital for renewable energy projects , 2020 .

[27]  R. Jonsson,et al.  ENSPRESO - an open, EU-28 wide, transparent and coherent database of wind, solar and biomass energy potentials , 2019, Energy Strategy Reviews.

[28]  Tom Brown,et al.  PyPSA-Eur: An open optimisation model of the European transmission system , 2018, Energy Strategy Reviews.

[29]  A. Hawkes,et al.  Projecting the Future Levelized Cost of Electricity Storage Technologies , 2019, Joule.

[30]  Thiel Christian,et al.  The JRC-EU-TIMES model. Bioenergy potentials for EU and neighbouring countries , 2015 .

[31]  D. Gesch,et al.  Global multi-resolution terrain elevation data 2010 (GMTED2010) , 2011 .

[32]  Diego Luca de Tena,et al.  Integrated modelling of variable renewable energy-based power supply in Europe , 2017 .

[33]  Adrian Stämpfli,et al.  Energy autarky: A conceptual framework for sustainable regional development , 2011 .

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

[35]  Willett Kempton,et al.  Electric power from offshore wind via synoptic-scale interconnection , 2010, Proceedings of the National Academy of Sciences.

[36]  Stefano Marelli,et al.  UQLab: a framework for uncertainty quantification in MATLAB , 2014 .

[37]  Bernhard Lehner,et al.  Global river hydrography and network routing: baseline data and new approaches to study the world's large river systems , 2013 .

[38]  Geoffrey T. Parks,et al.  Multi-fidelity non-intrusive polynomial chaos based on regression , 2016 .

[39]  Hannes Isaak Reuter,et al.  An evaluation of void‐filling interpolation methods for SRTM data , 2007, Int. J. Geogr. Inf. Sci..

[40]  T. Allaoui,et al.  The transition towards a sustainable energy system in Europe: What role can North Africa's solar resources play? , 2019, Energy Strategy Reviews.

[41]  Lukas H. Meyer,et al.  Summary for Policymakers , 2022, The Ocean and Cryosphere in a Changing Climate.

[42]  Anjali Awasthi,et al.  Solar PV Power Plants Site Selection , 2018 .

[43]  Sven Rahmann,et al.  Genome analysis , 2022 .

[44]  Hugo Lucas,et al.  International Renewable Energy Agency , 2021, Permanent Missions to the United Nations, No. 309.

[45]  P. Joskow Transmission Capacity Expansion Is Needed to Decarbonize the Electricity Sector Efficiently , 2020 .

[46]  Martin Greiner,et al.  The benefits of cooperation in a highly renewable European electricity network , 2017, 1704.05492.

[47]  Martin Greiner,et al.  Validation of Danish wind time series from a new global renewable energy atlas for energy system analysis , 2014, 1409.3353.

[48]  Sven Rahmann,et al.  Snakemake--a scalable bioinformatics workflow engine. , 2012, Bioinformatics.

[49]  Johan Lilliestam,et al.  The potential and usefulness of demand response to provide electricity system services , 2017 .

[50]  T. Brown,et al.  Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system , 2018, Energy.

[51]  Morten Boje Blarke,et al.  SuperGrid or SmartGrid: Competing strategies for large-scale integration of intermittent renewables? , 2013 .

[52]  Michel Bierlaire,et al.  Characterization of input uncertainties in strategic energy planning models , 2017 .

[53]  N. Nakicenovic,et al.  Summary for policymakers , 1963 .

[54]  D. Stolten,et al.  The techno-economic potential of offshore wind energy with optimized future turbine designs in Europe , 2019 .

[55]  Martin Junginger,et al.  Is a 100% renewable European power system feasible by 2050? , 2019, Applied Energy.

[56]  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 .

[57]  S. Pfenninger,et al.  Balancing Europe’s wind power output through spatial deployment informed by weather regimes , 2017, Nature climate change.

[58]  S. Pfenninger,et al.  Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data , 2016 .

[59]  Genevieve Saur,et al.  Lifecycle Cost Analysis of Hydrogen Versus Other Technologies for Electrical Energy Storage , 2009 .

[60]  Brian Vad Mathiesen,et al.  Smart Energy Systems for coherent 100% renewable energy and transport solutions , 2015 .

[61]  Christian Breyer,et al.  Flexible electricity generation, grid exchange and storage for the transition to a 100% renewable energy system in Europe , 2019, Renewable Energy.

[62]  J. Lilliestam,et al.  Development of SuperSmart Grids for a more efficient utilisation of electricity from renewable sources , 2009 .

[63]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .