The phase-out of nuclear and coal power is creating an electricity deficit in northern Germany, while there is a surplus of electricity in southern Germany. The transition from centralized to decentralized energy generation from renewable energies is challenging the electricity grid, as it has to integrate many small producers and transport electricity across regions.

The "PrognoNetz" project aims to develop an intelligent, weather-dependent power load forecast. A dense sensor network collects high-resolution weather data along the lines in order to model the weather conditions in 3D as well as over time and along the line sag. Based on historical weather data, the power load capacity for the next two days can be predicted more precisely and the grid can be used more efficiently. This makes it easier for grid operators to plan electricity generation and trading in advance.

In her work, Na Shen is investigating efficient, UAV-supported concepts for installing and maintaining the sensor stations. This includes a gripper arm for attaching, installing and removing the sensor systems. In addition, computer vision algorithms have been developed to detect the relative position and orientation of the UAV to the installation site to support control and installation.