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Embedding power system’s reliability within a long-term Energy System Optimization Model: Linking high renewable energy integration and future grid stability for France by 2050

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  • Seck, Gondia Sokhna
  • Krakowski, Vincent
  • Assoumou, Edi
  • Maïzi, Nadia
  • Mazauric, Vincent

Abstract

The aim of this article is to take into account short-term power grid operation conditions in long-term prospective analysis in the case of France. It is the first time that the integration of system adequacy and transient stability has been achieved in prospective studies for an electro intensive country, following studies conducted on Reunion Island. The methodology relies on a quantitative assessment of the French power sector’s reliability through an endogenous definition of a reliability indicator related to kinetic reserves into an Energy System Optimization Model (ESOM), TIMES-FR model. The result gives an overview of how the stability of the grid is maintained with an increasing share of renewables using additional back-up and flexible options. We observe that it is technically possible to achieve around 65% of Variable Renewable Energy sources (VREs) in the installed capacity without impairing the reliability of the system. In more detail, the maximum VRE in total hourly power production that complies with the reliability constraint was assessed as around 84% in the 100 EnR scenario. However, in order to guarantee this system reliability, the cumulated new installed capacity, in a scenario with 100% renewable energy sources (RES) in the power mix, would represent the double of the Business-As-Usual (BAU) scenario over the period 2013–2050. Therefore, major upstream planning would be needed, and that more flexible options i.e. demand-response, storage technologies and interconnections or substitute or additional plants should be considered to satisfy the reliability constraint at any time by providing extra inertia to the system. This modelling exercise shows the importance of power exchanges with neighbours with higher share of RE in the power production.

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  • Seck, Gondia Sokhna & Krakowski, Vincent & Assoumou, Edi & Maïzi, Nadia & Mazauric, Vincent, 2020. "Embedding power system’s reliability within a long-term Energy System Optimization Model: Linking high renewable energy integration and future grid stability for France by 2050," Applied Energy, Elsevier, vol. 257(C).
    • Handle: RePEc:eee:appene:v:257:y:2020:i:c:s0306261919317246
    DOI: 10.1016/j.apenergy.2019.114037
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    15. Gul, Eid & Baldinelli, Giorgio & Bartocci, Pietro & Shamim, Tariq & Domenighini, Piergiovanni & Cotana, Franco & Wang, Jinwen & Fantozzi, Francesco & Bianchi, Francesco, 2023. "Transition toward net zero emissions - Integration and optimization of renewable energy sources: Solar, hydro, and biomass with the local grid station in central Italy," Renewable Energy, Elsevier, vol. 207(C), pages 672-686.
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    17. Nikita Belyak & Steven A. Gabriel & Nikolay Khabarov & Fabricio Oliveira, 2023. "Renewable Energy Expansion under Taxes and Subsidies: A Transmission Operator's Perspective," Papers 2302.10562, arXiv.org, revised Apr 2024.
    18. Heras, Jorge & Martín, Mariano, 2020. "Social issues in the energy transition: Effect on the design of the new power system," Applied Energy, Elsevier, vol. 278(C).
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    20. Connor Scott & Mominul Ahsan & Alhussein Albarbar, 2021. "Machine Learning Based Vehicle to Grid Strategy for Improving the Energy Performance of Public Buildings," Sustainability, MDPI, vol. 13(7), pages 1-22, April.
    21. Oskouei, Morteza Zare & Mohammadi-Ivatloo, Behnam & Abapour, Mehdi & Shafiee, Mahmood & Anvari-Moghaddam, Amjad, 2021. "Privacy-preserving mechanism for collaborative operation of high-renewable power systems and industrial energy hubs," Applied Energy, Elsevier, vol. 283(C).
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    23. Serrano-Arévalo, Tania Itzel & López-Flores, Francisco Javier & Raya-Tapia, Alma Yunuen & Ramírez-Márquez, César & Ponce-Ortega, José María, 2023. "Optimal expansion for a clean power sector transition in Mexico based on predicted electricity demand using deep learning scheme," Applied Energy, Elsevier, vol. 348(C).
    24. Pietzcker, Robert C. & Osorio, Sebastian & Rodrigues, Renato, 2021. "Tightening EU ETS targets in line with the European Green Deal: Impacts on the decarbonization of the EU power sector," Applied Energy, Elsevier, vol. 293(C).
    25. Brumana, Giovanni & Franchini, Giuseppe & Ghirardi, Elisa & Perdichizzi, Antonio, 2022. "Techno-economic optimization of hybrid power generation systems: A renewables community case study," Energy, Elsevier, vol. 246(C).

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