Description
Chair: André Baier, Dominik Beinert (Fraunhofer IEE)
Content / Abstract:
This session focuses on the application of artefitial intelligence in the energy sector. We are looking for talks from various related topics which explore the challenges and some of the employed solutions for the critcal energy infrastructure.
Topics of interest include:
- Forecasting generation and consumption
- State estimation for electrical grids
- Vegetation detection for overhead condutors
- Bird detection on wind sites
- Autonomous agents for grid operation und energy markets
Agenda
- Welcome: 5 min
- 4 contributed talks (each 15 min + 5 min discusison)
- Conclusion: 5 min
The expansion of renewable energies is of crucial importance for the future of energy supply. There are numerous reasons for this change and highlight the need for a transition from fossil fuels to sustainable energy sources. Access to clean energy plays a central role in improving the quality of life and protecting our environment. A diverse data basis is essential for efficient...
As the expansion of renewable energies grows, the need for accurate energy forecasts becomes crucial due to the dependency on volatile energy sources. Traditional forecasting systems, which utilize weather data and historical generation data, are challenged by the unique behaviors of individual power plants, lack of data and changing conditions (Yan et al. 2022). To address these challenges,...
Early fault detection is crucial in predictive maintenance for wind turbines, yet comparing different algorithms remains challenging due to the scarcity of domain-specific public datasets. Many papers introduce sophisticated algorithms based on inaccessible data, making their results difficult to verify and hard to compare with results of similar algorithms. This presentation addresses these...
Maintenance work orders are commonly used to document information about wind turbine operation and maintenance. This includes details about proactive and reactive wind turbine downtimes, such as preventative and corrective maintenance. However, the information contained in
maintenance work orders is often unstructured and difficult to analyze, presenting challenges for decision-makers wishing...
