Bereiche/EI/ees-eeo/Forschung/Graphic_NVP

Project manager: M. Sc. Fabian Bauer

Project partner: 50Hertz Transmission GmbH, Berlin

Project description:

As part of this research project, a novel forecasting model is being developed to predict grid losses in the energy transmission grid. These losses, which are caused by physical processes in lines and equipment, depend on numerous factors such as grid utilization, environmental influences and the feed-in of renewable energies. In particular, the growing integration of wind and solar energy and the associated long transmission distances pose a major challenge.

A model approach based on artificial neural networks (ANN) is being developed for the precise and cost-optimized procurement of balancing energy. The research aims to further expand the use of deep neural networks and to integrate additional exogenous influencing variables in order to increase the accuracy of forecasts and the traceability of results.

Highlights:

  • Use of artificial neural networks for grid loss forecasting
  • Improved model quality through the consideration of exogenous influencing factors
  • Reduction in procurement costs through more precise forecasts
  • Cooperation with 50Hertz Transmission GmbH, Berlin