Feasible path toward 40–100% renewable energy shares for power supply in France by 2050: A prospective analysis

This paper explores the conditions under which renewable energy sources (RES) penetration could jeopardize power system reliability, as well as which flexibility options could help integrate high levels of RES. For this purpose, we used an energy-planning model from the TIMES family, which provides a realistic representation of power systems and plausible options for their long-term development, completed by a thermodynamic description of power systems to assess their reliability. We applied this model to the case of France and built contrasted scenarios, from 0% to 100% renewable energy penetration by 2050. We also tested different assumptions on Variable Renewable Energy (VRE) production, imports, demand flexibility and biomass potential. We show that high renewable energy penetration would need significant investments in new capacities, new flexibility options along with imports and demand-response, and that it is likely to deteriorate power system reliability if no technologies dedicated to this issue are installed.

[1]  Qi Zhang,et al.  An integrated model for long-term power generation planning toward future smart electricity systems , 2013 .

[2]  Modélisation MARKAL pour la planification énergétique long terme dans le contexte français , 2006 .

[3]  Galen Barbose Renewables Portfolio Standards in the United States: A Status Update , 2012 .

[4]  Nikolaos E. Koltsaklis,et al.  A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints , 2015 .

[5]  Nadia Maïzi,et al.  Increasing shares of intermittent sources in Reunion Island: Impacts on the future reliability of power supply , 2015 .

[6]  D. Revel,et al.  Contribution des Smart Grids à la transition énergétique : évaluation dans des scénarios long terme , 2014 .

[7]  Carlos Silva,et al.  High-resolution modeling framework for planning electricity systems with high penetration of renewables , 2013 .

[8]  Nadia Maïzi,et al.  Impacts of intermittent sources on the quality of power supply: The key role of reliability indicators , 2014 .

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

[10]  Competitive low carbon economy in 2050 , 2013 .

[11]  Vincent Mazauric,et al.  A global approach of electromagnetism dedicated to further long‐term planning , 2007 .

[12]  J. H. Nelson,et al.  High-resolution modeling of the western North American power system demonstrates low-cost and low-carbon futures , 2012 .

[13]  Nadia Maïzi,et al.  Expanding renewable energy by implementing Demand Response , 2014 .

[14]  G. Luderer,et al.  System LCOE: What are the Costs of Variable Renewables? , 2013 .

[15]  Markus Haller,et al.  Assessment of transformation strategies for the German power sector under the uncertainty of demand development and technology availability , 2015 .

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

[17]  H. Rogner,et al.  Incorporating flexibility requirements into long-term energy system models – A case study on high levels of renewable electricity penetration in Ireland , 2014 .

[18]  Willett Kempton,et al.  Cost-minimized combinations of wind power, solar power and electrochemical storage, powering the grid up to 99.9% of the time , 2013 .

[19]  Wind Power Feed-in Impacts on Electricity system , 2014 .

[20]  Santa Barbara,et al.  Dynamics and Control in Power Grids and Complex Oscillator Networks , 2013 .

[21]  Brian Ó Gallachóir,et al.  Soft-linking of a power systems model to an energy systems model , 2012 .

[22]  Shuping Dang,et al.  A source–grid–load coordinated power planning model considering the integration of wind power generation , 2016 .

[23]  Hans-Josef Allelein,et al.  Impacts of the transformation of the German energy system on the transmission grid , 2014 .

[24]  James Merrick,et al.  A Clean Energy Standard Analysis with the US-REGEN Model , 2014 .

[25]  Pierre Desprairies,et al.  World Energy Outlook , 1977 .

[26]  Nadia Maïzi,et al.  Future prospects for nuclear power in France , 2014 .

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

[28]  J. P. Deane,et al.  Assessing power system security. A framework and a multi model approach , 2015 .

[29]  Aie,et al.  World Energy Outlook 2013 , 2013 .

[30]  M. Burgos Payán,et al.  Estimating wind turbines mechanical constants , 2007 .

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

[32]  William D'haeseleer,et al.  Impact of the level of temporal and operational detail in energy-system planning models , 2016 .

[33]  Nadia Maïzi,et al.  Sustainable design of power systems: A fully magnetic multi-scale model devoted to grid stability , 2016 .

[34]  R. Kannan,et al.  A Long-Term Electricity Dispatch Model with the TIMES Framework , 2013, Environmental Modeling & Assessment.

[35]  Yasumasa Fujii,et al.  Long-term scenario analysis of nuclear energy and variable renewables in Japan's power generation mix considering flexible power resources , 2015 .

[36]  S. Pfenninger,et al.  Renewables, nuclear, or fossil fuels? Scenarios for Great Britain’s power system considering costs, emissions and energy security , 2015 .

[37]  R. Newman Promotion of the use of energy from renewable sources , 2014 .

[38]  Tansu Alpcan,et al.  A Game-Theoretic Analysis of Wind Generation Variability on Electricity Markets , 2014, IEEE Transactions on Power Systems.

[39]  Joachim Bertsch,et al.  Flexibility in Europe's power sector - an additional requirement or an automatic complement? , 2013 .

[40]  Lion Hirth,et al.  Carpe Diem: A Novel Approach to Select Representative Days for Long-Term Power System Models with High Shares of Renewable Energy Sources , 2014 .

[41]  Sang Yong Park,et al.  An analysis of the optimum renewable energy portfolio using the bottom–up model: Focusing on the electricity generation sector in South Korea , 2016 .

[42]  Vincent Mazauric,et al.  Expanding Renewable Energy by Implementing Dynamic Support through Storage Technologies , 2014 .