AI sensors improve power grid utilization
The PrognoNetz project brings together science and industry to work on sensor networks that improve the utilization of overhead power lines. Meteorological data is collected and evaluated directly on the power lines.20 May 2019 Roland Freist
Together with partners from industry, the Karlsruhe Institute of Technology (KIT) is developing a meteorological network that uses intelligent AI sensor nodes to record weather conditions along overhead power lines. This data can be used to estimate the power cable temperature and the resulting permissible current carrying capacity: the lower the outside temperatures and the stronger the wind around a cable, the better it is cooled and the higher its capacity.
German Weather Service data is usually not suitable for such analysis, because its weather stations are too far away from the power lines. The data now being collected directly from the lines should help improve the utilization of existing power grids. The PrognoNetz project focuses on developing self-learning algorithms that predict the possible current carrying capacity. The idea is to leverage historical measurement data to create intelligent models for each cable in the power grid.
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