Today, the German electricity market is tied to the weather like hardly any other economic sector. With renewable energies accounting for nearly 60 percent of total generation, it is no longer primarily demand that determines the electricity price, but rather the question: Is the sun shining, is the wind blowing—and how accurately can that be predicted?
While the Weather forecast formerly for the Energy market was once just a side note, today it is one of the most important pieces of information for all stakeholders in electricity trading. An independent and highly specialized market has emerged for precise and regionally resolved weather forecasts. They are considered a critical input factor for grid control, the power exchange, and the economic operation of Battery storage BESS.
Three target groups and different requirements for weather data
Grid operators: schedules, balancing energy, and redispatch
Transmission and distribution system operators need weather forecasts to plan power plant dispatch and grid utilization. If the actual feed-in from wind and PV deviates from the forecast, grid bottlenecks are looming – the result is redispatch measures, meaning short-term interventions in the operating mode of power plants and generation facilities.
The dimension of this problem is shown in current figures: provisional costs for grid bottleneck management rose by four percent in 2025 to around 3.1 billion euros, although the total volume of the measures remained almost unchanged at around 30.3 terawatt-hours.
Particularly noteworthy: In 2025, photovoltaic systems had to be curtailed by 94 percent more than in the previous year – a direct effect of increasingly precise, but also increasingly volatile PV feed-in, which pushes the distribution grid to its limits on sunny days. For grid operators, weather forecasting is therefore not just a nice-to-have for planning, but has a direct impact on costs.
Further information: Redispatch – Technology, Processes & Future
Electricity trader: Price forecast for day-ahead and intraday
For market participants in power trading, the weather forecast is the basis of every price assessment. Since wind and PV feed-in directly influence the merit order, the prediction accuracy about Profit or loss in day-ahead and intraday trading.
The resulting volatility is now extreme: EPEX prices reached in 2025 a span from –130 to +583 €/MWh. In the first half of 2026 were they even prices from – 499 to + 747 €/MWh. The number of hours with negative electricity prices was around 457 in 2024 and 573 in 2025, with a continued upward trend.
At the same time, the average intraday spread grew from 6 ct/kWh (2020) to 11.7 ct/kWh (2025), with a forecast of 15–20 ct/kWh by 2030. Anyone who knows regional cloud cover or a local lull in the wind hours earlier and more accurately than the market can trade these price spikes specifically—those who cannot, pay for them.
BESS operators: schedules, arbitrage, and multi-use control
For battery energy storage system operators, both issues converge into a core business question: when to charge, when to discharge? Schedule optimization of a BESS in front-of-the-meter (FTM) operation depends directly on the accuracy of the price forecast and thus the weather forecast – every missed price peak is lost arbitrage, every poorly timed charge is a real economic loss.
This applies all the more the more granular the revenue strategy is: A storage system that engages in revenue stacking – meaning multiple revenue sources such as Day-Ahead Trading, Intraday Trading and Control energy combined – requires precise, short-term weather data for every single decision-making level.
From prediction to roadmap – briefly explained
Weather services and specialized energy meteorology providers create their forecasts on the basis of numerical weather prediction (NWP) models, which are calculated multiple times using ensemble methods with slightly varied initial conditions in order to depict a range of possible developments. For the energy market, the decisive factor is less the model itself than the regional resolutionA nationwide average forecast says little about whether a lull in the wind will set in above a specific wind farm in Schleswig-Holstein in two hours. The finer the spatial and temporal resolution, the more tradable the information becomes—and the more expensive it is to procure.
Aggregators as intensive users of weather data
How seriously the industry takes the issue is evident in Flexibility aggregators, who coordinate BESS portfolios in FTM operation. For them, investing in the most precise, high-resolution weather data possible is not an IT cost item, but rather a direct revenue driver. Every additional bit of accuracy in short-term forecasting improves schedule optimization across the entire coordinated portfolio and multiplies with the number of controlled assets.
aggregators managing large, cross-border storage portfolios, such as the partners of CUBE CONCEPTS Second Foundation or Inspired, thereby ranking among the market participants with the highest economic interest in forecast quality of all. Therefore, they work closely with meteorological research institutes, commercial weather services, and climate tech companies, actively supporting their work.
Extreme weather as a stress test for the energy market
We have already described in detail in separate articles how strongly individual weather conditions can disrupt the market balance:
- Dark doldrums – when periods of no wind and a lack of solar radiation occur simultaneously and drive up the residual load
- Hellbrunn and Hellbrise on the first weekend of May 2026 – when wind and PV surpluses occur simultaneously and drive prices into negative territory
- Heat wave – when cooling demand, PV efficiency losses, and power plant restrictions coincide
All scenarios have one thing in common: they are weather-related, vary by region, and are only economically manageable if they are predicted in a timely and regionally accurate manner.
Why inaccurate weather forecasts become expensive
The costs of a forecasting error stem essentially from the difference between the price at which a position was hedged and the price at which the actual balancing must take place on the intraday market or via balancing energy. With highly volatile intraday prices – averaging an 11.7 ct/kWh spread in the meantime – even a short-term miscalculation of cloud cover or wind speed can make a significant economic difference. At the system level, this adds up to the billions mentioned at the outset in grid congestion management.
Outlook: Weather and energy market forecasts are merging
With the steadily increasing share of renewable energies, this coupling of weather and market data will intensify further. AI-supported weather models with shorter computation times and finer resolution, combined with a direct connection to price and schedule optimization systems, are increasingly becoming the standard. This applies not only to specialized aggregators, but to every market participant seeking FTM revenues such as Revenue Stacking wants to develop economically viable.
Frequently Asked Questions
Why have weather forecasts become more important for the electricity market?
Because renewable energies now account for a major share of power generation and their feed-in depends directly on the weather. The more accurate the weather forecast, the better grid management, trading, and storage schedules can be planned.
How does a forecasting error affect the electricity price?
If the actual wind or PV feed-in deviates from the forecast, the difference must be balanced out at short notice on the intraday market or via balancing energy – often at significantly worse prices than originally calculated.
What role does the regional resolution of weather data play?
A very important one: National averages reveal little about the actual feed-in at a specific location. For grid operators, traders, and BESS operators, what matters is the most localized, short-term forecast possible.
What does redispatch have to do with the weather forecast?
A significant portion of redispatch measures occurs because wind or PV feed-in differs from forecasts and locally overloads the grid. Better forecasts help to identify such bottlenecks earlier and manage them more precisely.
Why are BESS aggregators investing so much in weather data?
Because the schedule optimization of an energy storage system in FTM operation depends directly on the price forecast—which in turn depends on the weather forecast. In the case of large, cross-border portfolios, every improvement in forecasting accuracy multiplies across all controlled assets.
Conclusion
Precise, regional weather forecasts are no longer just a meteorological detail, but a key economic factor in the energy market. For grid operators, they determine billions of euros in redispatch costs; for traders, profits and losses in volatile intraday trading; and for BESS operators, the profitability of every single schedule. Those who understand this connection and integrate it into their operational strategy gain a clear advantage in a market that is increasingly driven by the weather.