Im zweiten Teil unserer Serie wenden wir unser Framework zu Netzengpässen auf ein reales BESS-Projekt an. Wir zeigen, wie saisonale Effekte die finanziellen Auswirkungen von Beschränkungen verringern können, und skizzieren Strategien zur Absicherung der Einnahmen.

Batteriespeicher und Netzengpässe: Wie sich Restriktionen auf Projekte auswirken (Teil 2)

In our previous article, we explored the foundational steps to evaluate grid constraints for BESS projects. We covered two critical aspects:

Insights from Step 1: Understanding BESS Behavior

We learned that BESS operations vary significantly by season and market dynamics. Seasonal differences drive charging and discharging patterns—winter operations focus on nighttime charging and evening discharging, while summer operations are dictated by PV production. Furthermore, market segmentation is key: participation in the Day-Ahead market (DAA) is driven by fundamentals, whereas Intraday Continuous (IDC), FCR, and aFRR respond to short-term volatility.

Insights from Step 2: Understanding Grid Constraints

To properly assess the impact of grid constraints, developers and investors must analyze several factors. These include the timing of restrictions—whether they occur seasonally or in response to specific events—their extent, the frequency and operational limits imposed, and the level of advance notice provided by grid operators. Another crucial aspect is whether or not the operator offers financial compensation for restrictions, which can have a significant influence on a project's financial viability.

Today, we move to Step 3, where we take a real-world example to assess the revenue impact of grid constraints and examine practical mitigation strategies.

Project Overview

This BESS project is located near the Alps, where snow cannons create a significant load on the grid during winter months. To mitigate grid stress, the grid operator has the right to influence the operation of the BESS asset during peak demand periods.

Did you know? The snow cannons in the Alps consume so much energy that during peak snowmaking season, their electricity usage can rival that of a small city! In fact, a single large ski resort can use up to 3 GWh of electricity per season—enough to power thousands of households for a year!

Applying our evaluation framework from Part 1, we analyze this project considering four key dimensions:


  • Timing: The grid operator can foresee snow cannon usage well in advance and must communicate any operational restrictions at least two days before they take effect. These constraints are imposed exclusively during winter months when snow production is required.
  • Extent: The grid operator can restrict access on up to 10% of the days annually, meaning that during these periods, the BESS asset must remain offline or operate at reduced capacity.
  • Communication: Since the operator provides sufficient advance notice, the exact method of notification is not as critical given the 2-day lead time.
  • Compensation: No financial compensation is provided for the restricted days.

Assessing the Financial Impact

To evaluate the financial impact of these grid constraints, we consider different scenarios. A simplistic view, assuming no seasonality in revenues, suggests that a 10% restriction on operations would result in a direct 10% revenue loss. However, a more detailed analysis reveals that revenues are not evenly distributed throughout the year, making the actual impact more nuanced.

By analyzing a 90-day moving average revenue trend, we observe that revenues are significantly lower in winter compared to summer. This seasonal revenue pattern indicates that the financial impact of winter restrictions is likely to be lower than initially expected

Graph 1 a): Average daily dispatch profile in winter
Average daily dispatch profile in winter

The grid operator provided data indicating the specific days affected by restrictions. In total, the asset was unavailable for 35 days, with the majority of restrictions occurring in January (14 days) and February (10 days).

Graph 2a) Load factors by RES technology (mix) sorted from high load to low load