The project partners are investigating the linking of lightweight construction principles and the digitalized production of offshore wind turbines with the aim of saving resources and reducing CO2 emissions. BMWE, 05/2021 - 12/2026
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Digitalization is a dynamic and clearly noticeable process in industry – including the wind energy and hydrogen sectors. Through its complex research topics, Fraunhofer IWES offers digital solutions in all areas. In addition to standards such as data monitoring, topics such as big data and the digital twin have also found their way into research. They are being utilized and further developed in a wide range of different scientific fields.
Virtual test rigs are a major focus at Fraunhofer IWES among other things. The physical test rigs are used to develop numerical models and validate them fully with experimental tests. This enables the development of new test methods which are not physical.
At the Dynamic Nacelle Testing Laboratory (DyNaLab), for example, it is possible to describe a mechanical test. The model represents a nacelle, the surrounding test infrastructure, and the auxiliary systems. The virtual nacelle test rig can also map the effects of electrical tests on the mechanical structure.
With the IWES Digital Hub, we bundle our digital expertise on a central platform as digital services. The hub facilitates access to selected software tools that are developed, validated, and tested at Fraunhofer IWES, and thus making the planning, design, and operation of wind farms more efficient.
In addition to a range of software used in-house, IWES also makes open source fluid dynamics software available to external users. FOXES, a modular wind farm simulation and wake modeling toolbox, and iwopy, a framework for coupling different optimization modules, together form the basis for calculating different optimization scenarios of wind energy utilization.
Use cases range from wind farm optimization (e.g., layout optimization or wake steering) to post-construction analyses, studies, comparisons, and wake model validations. Further open source releases are also planned for the future.
The project partners are investigating the linking of lightweight construction principles and the digitalized production of offshore wind turbines with the aim of saving resources and reducing CO2 emissions. BMWE, 05/2021 - 12/2026
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The project partners are developing an AI-supported diagnostics system for verifying power curves and detecting faults for a higher energy yield from wind. BMFTR, funding program KI4KMU, 04/2024 - 12/2026
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Fraunhofer IWES is developing software to allow offshore project stakeholders to make quick and informed decisions based on comparisons of planned and actual project statuses. BMWE, 02/2026 – 10/2026
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The project partners are developing a method for the creation of digital twins of large rolling bearings in order to improve their condition monitoring and reliability. BMWE, 07/2022 - 06/2027
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The project partners improve the model-based assessment of the remaining lifetime of wind turbines using a machine learning based correction in the simulation algorithm. BMFTR, 11/2022 – 10/2025
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The international project partners are training a new generation of multidisciplinary engineers, who will be investigating key issues regarding the use of AI in wind farm operation while earning their doctorates. EU Horizon Europe MSCA Doctoral Networks, MARIE SKŁODOWSKA-CURIE ACTIONS, 09/2024 – 08/2028
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