- A customer from the energy sector needs to accurately forecast the load profiles of its distribution partners on a daily basis.
- The forecasting software currently in use is not flexible enough and provides forecasts that are too imprecise in detail.
- The customer wants a transparent, flexible and high-performance solution.
Through the use of modern Forecasting algorithms (Deep Learning) and other influencing factors, the Forecast quality improved. Above all, the use of new Weather parameters and the intensive tuning of the model (load forecasting) lead to a significant improvement in the forecast quality.
- Stable forecasting model in an automated environment.
- Significant improvement in process transparency compared to the existing solution.
- Demonstration that a better forecast quality can be achieved with a fully automated process.
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