Flexible monitoring and control systems for the energy transition and mobility shift in the power distribution grid using Artificial Intelligence
The aim of the project FLEMING is to revolutionize the continuous monitoring of functions and in particular the current use of sensors in distribution networks by using methods of artificial intelligence coupled with an improvement of the associated sensor technology, and thus contribute significantly to the success of the energy and mobility turnaround in Germany.
The focus of German climate and energy policy is on the massive and comprehensive integration of renewable energy plants and the integration of charging stations for electric mobility into the existing power grid. The resulting numerous load fluctuations, e.g. due to decentralised solar systems, as well as the temporally and spatially concentrated energy demand due to charging infrastructure lead to a very high load on the electrical equipment and components up to an overload. At the same time, network operators are exposed to increasing efficiency and cost pressure.
Solution and expected result
The achievement of the described objectives is to be demonstrated by means of two exemplarily selected application scenarios. On the one hand, a thermal sensor system based on several infrared cameras will be used on switchgear. In the second application scenario, the dynamics of switch drives will be investigated using different sensors. A transferability of these shown results to further sensor applications, which are located between these two antipodes, is conceptually worked on.
Benefits for the target group
In order to achieve the objectives of the energy and mobility turnaround while maintaining supply quality, network operators need an improved understanding of the current state of the existing network and its components. This enables potential damage and system failures to be detected or predicted at an early stage or avoided through improved control.
- ABB AG Forschungszentrum Deutschland, Ladenburg
- FIR e. V. an der RWTH Aachen, Aachen
- Gruppe Intelligente Systeme und Maschinelles Lernen der Universität Paderborn (SICP), Paderborn
- Heimann Sensor GmbH, Dresden
- Institut für Elektroenergiesysteme und Hochspannungstechnik (IEH) des Karlsruher Instituts für Technologie (KIT), Karlsruhe
- Lehrstuhl für Wirtschaftsinformatik, insb. Betriebliche Informationssysteme der Universität Paderborn (SICP), Paderborn
- SÜC Energie und H2O GmbH, Coburg