Case Study

BESS Dispatch in France: Navigating Volatility

Capturing the shift from capacity-driven stability to energy-opportunistic gains through physics-aware, 15-minute granularity modelling.

The Challenge

In markets like France, determining attainable P&L requires a constant, multi-market balancing act. This study analyzes a utility-scale asset during a winter week that perfectly illustrates the complexity of modern dispatch.

The week of January 19 to 25, 2026, began with narrow Day-Ahead spreads, forcing a cautious capacity strategy. However, as mid-week volatility hit ancillary markets, the optimal path shifted radically, requiring the asset to pivot toward aggressive energy-opportunistic behavior.

Dispatch Strategy

By rebuilding the battery's life in 15-minute steps, our modelling captures the trading sequence exactly as it happens—from Day-Ahead commitments to Intraday adjustments:

  • Identified 15-minute intervals where energy value exceeded capacity standby payments.
  • Executed high-throughput cycles to capture price spikes while respecting site-specific cycling limits.
  • Maintained strict physical SoC guardrails to ensure availability for the most lucrative windows.
Detailed dispatch visualization showing SoC and power layers
Preview of the dispatch per product and SoC evolution
The Results

The asset captured aFRR energy price spikes that compensated for narrow Day-Ahead spreads. By maintaining high availability through disciplined SoC management, the dispatch executed high-throughput cycles exactly when market volatility peaked.

This performance validates the model's ability to navigate trade-offs between capacity commitments and energy opportunism. The resulting attainable P&L serves as a transparent baseline, separating operational execution from broader market trends.

Download the Full Case Study

Access the complete analysis, including high-resolution dispatch charts, State of Charge profiles, and a deep-dive into the French market economics for this period.

Download Case Study (PDF)
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