Summary
Battery energy storage systems are now essential for electricity system security, already contributing around 40% of Frequency Containment Reserves (FCR) in France. They are expected to play a growing role in Frequency Restoration Reserves (FRR) and in inertia loss compensation as the share of synchronous machines in the system declines. To accelerate their integration while limiting costs, RTE - the French transmission system operator - has adopted an optimal grid sizing strategy, allowing battery connections on existing infrastructure, but with occasional injection or withdrawal limits. To support this, RTE plans to issue a local congestion signal before the D-1 System Services Tender, warning operators of potential restrictions so they can optimize market strategies and help prevent congestion.
Read more Read lessThis paper proposes a probabilistic approach, in lieu of a traditional deterministic security analysis, to generate the D-1 congestion signal. This approach is based on uncertainty models for loads and renewables based on historical forecast errors. It uses Monte Carlo simulations in combination with the Schaake Shuffle method within a probabilistic DC load flow framework.
This gives an estimation of the probability distributions for network branch flows influenced by battery operations. The position of thermal line limits within these distributions is then used to generate the congestion signal. The method was tested on historical data and a case study in
Picardie, France (46 MW wind, 7.2 MW battery). The results, presented in this article, are promising, especially when compared with more naïve sampling methods.
Additional informations
| Publication type | Session Materials |
|---|---|
| Reference | C2_10850_2026 |
| Publication year | |
| Publisher | CIGRE |
| Country | France |
| Study committees | |
| File size | 1 MB |
| Price for non member | 30 € |
| Price for member | 30 € |
Authors
MARIÉ Alexandre - RTE France; LECHAT Théo - RTE France; LITTLE Emily - RTE France; BRETON Anaëlle - RTE France
Keywords
Security analysis, probabilistic load flow, forecast error model, Schaake Shuffle technique
