Modeling Prospective Reserve Requirements: A Probabilistic Framework Applied to the French Power System

ENTSO-E [1], which emphasizes the importance of integrating prospective flexibility needs assessments into routine prospective studies conducted by TSOs. To achieve this objective, we propose a novel methodology tailored for evaluating future reserve needs and illustrate its applicability through a national-scale prospective study for the French power system in 2036– 2037.

The methodology is built on RTE’s existing flexibility needs monitoring tool MAUI [2], which has been adapted to the specificities of prospective analyses. Originally designed for short-term operational use, MAUI is modified to process the synthetic chronicle outputs generated by the

ANTARES [3] prospective adequacy simulation framework. The core idea is to model each major source of system uncertainty—namely, load forecast errors, wind and solar forecast errors, and unplanned outages of conventional thermal units— through probabilistic distributions which are statistically estimated using historical data and machine learning techniques. The individual distributions are then convolved to form a global imbalance distribution, from which reserve needs are derived for various balancing products, including aFRR, mFRR, and RR, at each simulation timestep. The methodology has been validated against historical reserve requirement data, demonstrating robust calibration. Subsequently, it was applied to prospective scenarios for the years 2036-2037. The analysis reveals significant increases in reserve requirements compared to current levels. Specifically, the total frequency restoration reserve

(aFRR + mFRR) requirements are projected to increase by approximately 40% in the downward direction and 26% upward. Future extensions of this research will aim to introduce feedback mechanisms between reserve requirement modeling and ANTARES scenario planning. This iterative approach will ensure reserve needs computed by our methodology inform scenario refinement back into prospective adequacy studies, thus ensuring that the simulation of prospective energy systems adequately considers the fulfilment of reserve needs. RTE has already initiated preliminary work toward realizing this integration, reinforcing the strategic importance of flexibility assessment in prospective system planning.