The successful integration of fluctuating renewable energy sources into electricity systems depends, among other things, on thorough planning to avoid capacity bottlenecks and to ensure a high level of supply reliability. However, the further expansion of renewable energies will place a burden on the existing grid infrastructure. In order to increase the transmission capacity of overhead lines and at the same time reduce the cost of new lines, comprehensive high-resolution overhead line monitoring is required in real time. This is precisely where the research project PrognoNetz - Self-learning sensor networks for weather-dependent overhead line operation comes in. The current consumption capacity of the new weather sensors being developed not only depends on the current flow in the lines but, above all, on the air temperature, wind and solar radiation. At low outside temperatures or in a strong or cooling wind, more current can flow through the lines.
The network of Artificial Intelligence (AI)-based weather sensors offers a reliable alternative to today’s technology. In contrast to conventional weather stations, the new sensors being developed are used at strategic points sufficiently close to the transmission lines and in close proximity to each other so that the weather model can be adapted to realistic conditions in real time. They also have a self-learning function that allows them to automatically generate precise load capacity forecasts for hours or even days based on the weather data measured. In addition, the weather service provider UBIMET Deutschland, together with the Institute for Information Processing Technology (ITIV) of the Karlsruhe Institute of Technology (KIT), is developing novel forecasting models based on artificial intelligence that are suitable for transmission networks. With the help of historical weather data and topological characteristics, they are able to automatically generate more accurate forecasts for a transmission line. ITIV is also doing research on drones and on a laser-based wind sensor that promises more accurate measurements than conventional sensors. The use of drones is expected to help reduce personnel costs and safety risks during the installation and maintenance of the weather sensors. As part of the BMWi-funded project, the next step will be to simulate the smart grid for the high-voltage lines in the state of Baden-Württemberg.