🎓François COLLET Thesis Defense
Wednesday 10 December 2025 at 9h00
Phd Thesis JCA room, Cerfacs, Toulouse
Compound low-wind and cold events in the context of the adequacy between electricity supply and demand in France : evolution over the 21st century
SDU2E (Sciences de l’Univers, de l’Environnement et de l’Espace) – [Subject to defense authorization]
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With the integration of renewable energies into the electricity system, the sensitivity of the electricity generation to climate variability should increase. New types of climate events are therefore likely to pose risks to the stability of the power system, such as compound low-wind and cold events in winter. These compound events are associated with both low wind power production and high electricity demand, making it challenging to ensure the adequacy between electricity supply and demand. This thesis aims to investigate the future evolution of low-wind and cold events impacting the French power system in winter.
In the first chapter, the properties of compound low-wind and cold events are characterized using observations and atmospheric reanalyses data. These events are identified using indices that represent the current sensitivity of wind power generation and electricity demand to surface wind and temperature conditions. The occurrence of these compound events shows strong interannual variability, ranging from 0 to 13 days per winter over the 1951–2022 period. A large-scale atmospheric circulation pattern associated with a higher frequency of compound events, similar to the negative phase of the North Atlantic Oscillation, is identified. Finally, a decrease in the frequency of compound events is observed during the winters of the 1951–2022 period. This observed decrease is mainly due to a decrease in the frequency of cold days, which might be influenced by the low-frequency variability of the large scale atmospheric circulation.
In the second chapter, future projections from the latest generation of global climate models are used to characterize the future evolution of compound low-wind and cold events. Beforehand, the future evolution of near-surface wind speed in winter is assessed over Europe in global climate models. On average, near-surface wind speeds decrease by the end of the century, albeit with substantial regional variations, both in the magnitude and the sign of changes. Both the magnitude and sign of changes also vary across models. Two main processes contribute to these intermodel differences : the future changes in large-scale atmospheric circulation and the future changes in forest cover. A decrease in the frequency of compound events of about –40 %, –60 %, and –80 % is projected for the near-term, mid-term, and long-term future, respectively, compared to a recent reference period. This decrease is mainly driven by the future decrease in the number of cold days in winter, while future changes in low-wind days play a minor
role.
In the last chapter, it is shown using another approach that the properties and future evolution of compound low-wind and cold events are sensitive to the wind power capacity and to the temperature sensitivity of the electricity demand in France used in the compound event definition. Whereas compound events are associated with temperatures well below normal for the current wind power capacity, they may, under very low wind conditions, occur at above-normal temperatures for the higher wind power
capacity expected in 2050. Higher levels of wind power capacity may also reduce the future decrease in compound events frequency. These results suggest the importance of considering the future evolution of the wind power capacity and the temperature sensitivity of electricity demand when assessing the future evolution of compound low-wind and cold events.
Jury
| Philippe Drobinsky | CNRS/LMD | Reviewer |
| Juliette Mignot | IRD/LOCEAN | Reviewer |
| Sandrine Anquetin | CNRS/IGE | Examiner |
| Florian Pantillon | CNRS/LAERO | Examiner |
| Sylvie Parey | EDF/R&D | Examiner |
| Julien Boé | CNRS/UMR CECI | Thesis supervisor |
| Margot Bador | CNRS/UMR CECI | Thesis co-supervisor |
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