load forecasting

To optimise the forecast quality, further influencing factors and a state-of-the-art forecast algorithm are used.

!

Improvement of the forecast quality

 

U

More accurate prediction of individual distributors

Implementation of a transparent and high-performance forecasting system

Challenge

  • 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.

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.

Result

  • 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.

load forecasting

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