Plants run by Schleswig-Holstein Netz AG , a subsidiary of energy supplier Hansewerk , already have an AI algorithm in place to detect and predict power grid interruptions and outages. Eon in Essen was the development partner for the predictive maintenance tool. The AI uses hardware information from cables as well as real-time performance measurements (load behavior, etc.) and weather data.

The initial testing and learning phase has been completed to the satisfaction of the project participants. Xiaohu Tao, Head of Plant and Systems Technology at SH Netz, reports that the probability of defects in the power grid being proactively identified has increased by a factor of two to three. This allows maintenance work to be brought forward, he says, effectively saving time and money. Last but not least, the supplier gains significantly more reliability in planning expansion measures.

However, because grid stability is ultimately an overarching issue in which a number of factors have a role to play, scientists and researchers are now increasingly running scenarios as to what impact different developments could have. The latest example is the Fleets at Grid research project by Braunschweig University of Technology and local supplier BS Energy . The project uses a test facility to investigate the potential effect on power grids by (large-scale) charging of electric vehicles.