Wind Energy

Wind energy has become an important cornerstone for a successful energy transition. Without a massive conversion and expansion of onshore and offshore wind energy, Germany will not be able to achieve its climate protection goals and ensure a secure supply of sustainable electricity. The performance of complex wind turbines has increased enormously in recent decades, not least thanks to intensive research.

Wind energy research at LUH is part of ForWind, the joint center for wind energy research at the universities of Oldenburg, Hanover and Bremen. Together with the German Aerospace Center (DLR) and the Fraunhofer Institute for Wind Energy Systems IWES, ForWind forms the Wind Energy Research Alliance.

The Collaborative Research Center Offshore Megastructures (SFB 1463) was launched in 2021. Using the concept of a digital twin, an integrated design and operating methodology for offshore megastructures is being researched and demonstration examples of an offshore wind turbine with an output of more than 20 MW, with a focus on support structures and rotor blades. Further information on the SFB can be found on the corresponding project page zu finden.

 

Selected infrastructures and laboratories related to wind energy research

Selected projects from the field of wind energy research

Showing results 21 - 25 out of 33

TransWind: Transdisciplinary end-of-life analysis of wind turbines for the development of technically and economically optimal end-of-funding strategies

Rolfes, R., Breitner, M., Hübler, C. & Schmidt, F.

1 Nov 202031 Oct 2023

Project: Research

FANFOLD: Collaborative project: Fast nonlinear machine learned ANalysis For rOtor bLaDes

Rolfes, R., Rolffs, C. & Dorn, O. N.

1 Sept 202031 Aug 2024

Project: Research

VIPile: Collaborative project: Influence of vibration parameters on the installation and load-bearing behaviour of monopiles

Rolfes, R., Schaumann, P., Hübler, C. & Wolniak, M. T.

1 Aug 202031 Jul 2024

Project: Research

SONYA: Verbundvorhaben: Steigerung der Zuverlässigkeit von segmentieren Rotorblättern durch hybride Zustandsüberwachung; Teilvorhaben: Maschinelles Lernen für das hybride SHM-System

Rolfes, R. & Abbassi, A.

1 Jul 202030 Jun 2023

Project: Research

PreciWind: Collaborative project: Precise measuring system for contactless recording and analysis of the dynamic flow behaviour of wind turbine rotor blades

Rolfes, R., Gebhardt, C. G., Schuster, D. & Hente, C.

1 Jan 202031 Oct 2023

Project: Research


MORE INFORMATION IN THE "RESEARCH" SECTION: