As the switchover to renewable energy gathers pace in Germany, existing power lines are reaching their limits as power peaks from wind and solar overload the grid – resulting in the loss of surplus energy as it fizzles out. Energy storage solutions are the best way to manage this effect and to reduce grid infrastructure costs. Currently, however, there is no way of intelligently networking storage facilities in order to control power flows.
Step in the Landshut University of Applied Sciences in Bavaria, which has teamed up with DHYBRID Power Systems GmbH and CONPOWER GmbH to develop a cross-grid storage control system based on Big Data and machine learning. The joint project is called iGridControl.
Professor Alfons Haber, who is co-leading the project with Dr Mona Riemenschneider, explains the pressing demand for such a system: “In order to compensate for peak loads in local grids, generation plants and storage facilities would have to be massively expanded. This would result in high investment costs. However, it is already becoming apparent that the expansion of the distribution grids will not be able to keep pace with the steadily increasing share of renewable energy,” he says in a .
With an intelligent control solution at their disposal, plant operators would be able to regulate their output flexibly and become more energy and cost efficient. A wider benefit is that the security of Germany’s electricity supply will be bolstered, as well as the autonomy of regional grids.
In the first step, the researchers will record the load conditions of the grids. They will then build the architecture for a smart grid control system using Big Data analysis and intelligent algorithms. The data will then be provided to plants and storage facilities.
iGridControl has been funded by the Federal Ministry for Economic Affairs and Energy with EUR 190,000 until 2022.