"Your day ahead spot forecast brings a high quality comparative view alongside other day ahead forecasts. The accuracy of your forecasts has convinced us, especially for high and low prices."
How are the forecasts formed?
The forecasting models react flexibly to different situations in the electricity market. The models use weather forecasts, the status of power plants and transmission links, fuel prices, the hydropower, and several other variables as input data.
The forecasting models use a wide range of data from European bidding zones. The implementation is based on non-machine learning heuristics in addition to machine learning.
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"You have clearly been able to bring something new to the forecasting market and in our experience this approach seems to be very competitive in forecasting electricity prices."
