Intelligent predictions - Weather-based AI-Spitz-light billing for you and your customers

🧮 Calculating the fictitious yield for grid measures

If a renewable energy plant (e.g., PV or wind) is curtailed, the grid operator must reimburse the lost yield.
The Spitz-Light method uses model-based approaches for this - without expensive measuring devices.
In order to realistically estimate the lost electricity, a weather-dependent generation forecast is required.

🌤️ Which weather data is relevant?
Weather parameter Application in the calculation
Global radiation For PV systems: How much solar energy was available at the location?
Wind speed (at hub height) For wind turbines: How much energy could have been generated?
Temperature & air pressure Refinement of PV and wind power (temperature corrects PV efficiency, for example)
Precipitation & snow (optional) For special cases with shading or snow cover on PV systems

✅ Advantages of precise weather data:
No measurement hardware required at each feed-in point
High accuracy thanks to location-specific data (e.g., satellite or model)
Transparent and traceable for grid operators
BNetzA-compliant implementation with minimal effort

⚡ Direct marketers
They often handle billing for renewable energy or CHP plants vis-à-vis the grid operator.
They need weather data to calculate the fictitious reference yield for curtailed plants.
Basis for determining the lost work and financial compensation for it.

🔎 Typical goal:
→ Correctly calculate and bill the economic claim of the operators.

🏭 Plant operators (renewable energy and CHP plants)

Especially operators of larger plants (e.g., wind farms, ground-mounted PV systems) who bill grid operators directly.
For internal billing or to verify the accuracy of the information provided by the direct marketer.

🔎 Objective:
→ Traceable & verifiable basis for lost revenue due to redispatch measures.

🏢 Service providers / billing software providers
Companies that provide software or platforms for redispatch billing use weather data for:
Modeling reference yields
Automating billing logic (peak vs. peak-light)
Integration into customer dashboards

🔎 Goal:
→ Technically correct and automated processing in accordance with BNetzA requirements.

🏛️ Distribution system operators (DSOs)
They check the bills submitted by direct marketers or operators.
They must be able to verify the reference yield calculations – including those based on weather data.
Some DSOs use their own weather models or refer to publicly available weather sources (e.g., DWD).

🔎 Goal:
→ Ensure that only justified outage work is compensated.

🧩 Conclusion:
Role Use of weather data
Direct marketers: Calculate & bill reference yield
Plant operators: Control, self-billing, transparency
Service providers: Technical implementation, automation, API integration
Distribution system operators: Plausibility check, control mechanisms

NAECO Blue offers various data-driven software solutions for the energy industry to reduce weather-related risks. These range from consulting to project planning, development, and construction of solar and wind farms. We also support the operation such plants and the marketing of electricity with the help of AI algorithms for feed-in and consumption forecasts at plant or cluster level. Potential analyses enable reliable investment decisions that are underpinned by long-term forecasts. Consumption forecasts based on smart meters or network nodes enable targeted energy management for balancing group managers, company locations, and private users. System analyses and intelligent maintenance planning ensure smooth operation of the plants. NAECO Blue also distributes large amounts of data for the energy industry.

Some of the services are listed below:
- Feed-in forecasts at plant and cluster level up to 14 days in 15-minute increments
- Backcasting forecasts for wind and solar plants to determine performance and for risk decisions
- Development and consulting for new wind and solar plants
- Consumption forecasts at the smart meter and grid point level
- Long-term forecasts for new plants based on high-quality weather data
- Provision of weather data with around 100 characteristics and different altitudes for almost the entire world
- Analysis of existing plants for unusual effects and events
- Energy price forecasts for particularly forward-looking action
- Digital twin simulations for a potential new plant
- Flexibility as a service: discover and utilize the flexibility potential in your grid or company
- Energy storage and control of flexible plants

Visit us at www.naeco.blue

Spitz-light billing is a simplified yet precise method for determining compensation claims for redispatch measures within the framework of Redispatch 2.0. It offers numerous advantages over the more complex Spitz billing and the flat-rate standard solution.

🧮 Realistic billing – without the need for measurement
The fictitious reference yield is modeled on the basis of weather data and plant parameters.
No expensive measuring equipment is required (e.g., additional sensors at feed-in points).
Saves time and money – while offering greater accuracy than flat rates.

💰 Higher yield reimbursements than with flat-rate billing
The flat-rate calculation according to Section 13a of the German Energy Industry Act (EnWG) often yields conservative values.
In practice, Spitz-light billing often leads to higher compensation payments, as it takes actual weather conditions (e.g., strong winds or high solar radiation) into account.

⚖️ BNetzA-compliant & audit-proof
The method is approved in accordance with Federal Network Agency specification BK6-20-059.
Standardized procedures, transparent weather data sources, and documented modeling make it verifiable and legally compliant.

⚙️ Easy to automate
Spitz-light billing can be easily integrated into digital tools and platforms.
It is ideal for service providers, direct marketers, or operators with many plants.

📉 Reduces administrative effort
No need for individual performance time series or complex contract structures.
More uniform and efficient – particularly relevant for operators of small to medium-sized renewable energy plants.

🤝 Better balance of interests between grid operators and plant operators
The method is a fair compromise between flat rates (too inaccurate) and peak rates (too complex).
All parties involved benefit from transparency, efficiency, and traceability.

💡 Conclusion:

Peak-light billing is simple, fair, and economically attractive - especially for operators and direct marketers who rely on transparent compensation for redispatch measures without having to bear the expense of full peak billing.

The data set includes a wide range of relevant weather parameters, enabling precise, traceable peak billing. Feel free to take a look at our sample data set.

All we need are the coordinates of your wind farm or solar plant and the usual master data. You are also free to choose the format in which you would like to receive the data. Do you have any specific requirements? No problem - we will be happy to accommodate your wishes.