FlexPowerHub

API extension: import customer-specific price time series

In order to be equipped for fully automated bidding, a large amount of data must be exchanged between the customer system and the bid generator. By exchanging forecasts, schedules, marginal price time series, etc., the foundation has been laid for obtaining optimal bids when participating in the balancing energy market and leveraging the competitive edge

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Market analysis and innovations in Q1 2025

Market development & forecast performance in Q1 2025 The balancing energy market in Germany and Austria was extremely dynamic in the first quarter of 2025. While the negative markets (aFRR-, mFRR-) in particular suffered from falling prices in January and February, the picture changed significantly in March: massive price increases led to significant revenue growth

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Comparison of delivery times in the capacity market – 1 day ahead vs 2 day ahead

The advantages of the 1DA forecast over the 2DA forecast can be demonstrated on both the Austrian and German aFRR markets. We have implemented a special dashboard on our website where monthly updates are published. Dashboard Comparison of revenues on the Austrian aFRR Comparison of revenues on the German aFRR A comparison of the yields

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Backtesting – Compare revenues of different strategies and forecasts

I should have…who wouldn’t like to know in retrospect how it would have gone if…? With our backtesting tool you can answer exactly these questions. Create multiple strategies in the bid generator for the same asset, but with different parameters such as a different risk percentile, a different call probability, e.g. 20MW vs. 1MW bids,

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