Arkona is the most efficient wind farm to date in the Baltic Sea: off the coast of the island of Rügen, 60 wind turbines are located on an area of 39 square kilometers and have a total output of 385 megawatts. An individual structural health monitoring concept developed by Wölfel is designed to ensure that the wind turbines feed into the grid as continuously and efficiently as possible, incur the lowest possible costs for operation and maintenance and meet the requirements of the authorities.

Substructures of offshore wind turbines have to reliably withstand environmental conditions, operational and extreme loads during their design lifetime that may exceed the time period of 25 years. Within their lifetime, they may experience damage and structural changes. This study proposes a novel, data-driven approach for the quantification of probability of detection (POD) for the structural change due to scour on a monopile substructure. To achieve this aim, numerical analyses with finite elements are combined with real measured vibration data from an offshore wind farm.

If ice forms on the rotor blades of a wind energy plant, it must be shut down in accordance with official regulations in order to protect the surroundings from ice being shed. Critical ice build-up must therefore be reliably detected using technical measures. A meteorological sensor for ice detection was installed in the Hamwiede wind farm from the very beginning. However, it became apparent already in the first winter that the shutdown due to ice was very imprecise. False alarms and unnecessary shutdowns became more frequent. The potential of the wind farm could therefore not be fully exploited in the particularly high-yield winter months. Discover in our case study how downtimes at the Hamwiede wind farm were significantly and reliably reduced with the help of IDD.Blade from Wölfel.