
About
Oliver Ackermann Lylloff is a Researcher at DTU Wind and Energy Systems, Technical University of Denmark, specializing in experimental wind turbine aeroacoustics and wind tunnel testing. His work directly contributes to UN Sustainable Development Goals for affordable clean energy and climate action through advanced rotor design research.
Education:
- PhD in Wind Energy Systems, Technical University of Denmark (2017-2021)
Dr. Lylloff's research centers on experimental aeroacoustic characterization of wind turbine components using the Poul la Cour Wind Tunnel (PLCT). His expertise spans leading edge erosion analysis, vortex generator noise detection via beamforming, and Kevlar membrane acoustic properties under aerodynamic loading. He develops innovative methodologies for noise source localization and blade surface durability testing, directly addressing industry challenges in turbine noise reduction and efficiency optimization.
His recent publications (2024-2025) demonstrate a cohesive research trajectory focused on experimental wind tunnel validation of aerodynamic and aeroacoustic phenomena. Key trends include the development of open-source tools like AeroAcoustics.jl, systematic studies of leading edge protection systems, and advanced beamforming techniques for noise source identification—bridging theoretical fluid dynamics with practical wind turbine design constraints.
As Principal Investigator for the Sustainable and Cost Efficient Small Wind Turbine project (2025-2027), Dr. Lylloff leads a €2.1M research initiative funded by the Danish Energy Agency. His grant portfolio includes multiple collaborative projects with industry partners like Siemens Gamesa and Vestas, focusing on distributed energy solutions and blade erosion mitigation.
Dr. Lylloff operates within DTU's Rotors Wind Turbine Design Division and the Poul la Cour Wind Tunnel Laboratory (PLCT), where he manages experimental campaigns using state-of-the-art microphone arrays and beamforming systems. He actively disseminates research through public datasets like the PLCT-data collections and engages in knowledge transfer via media appearances and conference organization.
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