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Offshore wind power is becoming a cornerstone of the global transition to renewable energy. Yet, while the potential is enormous, the majority of wind resources are located in deep-water areas where traditional fixed-bottom turbines are not feasible. To unlock this potential, floating offshore wind technologies must be developed that are not only technically robust but also cost-effective and scaleable.

This MSCA Postdoctoral Fellowship addresses this challenge by developing an innovative Tilted Counter-Rotating Vertical Axis Wind Turbine (TCR-VAWT). Unlike conventional designs, this turbine is specifically optimized to operate under the tilted conditions typical of spar-buoy floating platforms. By adapting to these unique dynamics, the TCR-VAWT offers both aerodynamic and structural advantages, making it a promising solution for the next generation of floating offshore wind systems.

01 Sep 2025 - 31 Aug 2027

EU HORIZON-MSCA-2024-PF-01

About the project

  • Background

    The project brings together cutting-edge methodologies and industrial-academic collaboration. On the aerodynamic side, high-fidelity Computational Fluid Dynamics (CFD) simulations will be used to investigate airflow interactions, and energy capture efficiency. Subsequently, Finite Element Method (FEM) simulations will be carried out to assess structural integrity, material performance, and reliability under tilt conditions.

    Collaboration with the start-up World-Wide-Wind (WWW) will play a key role in translating theoretical insights into practical engineering solutions. This partnership will focus on turbine sizing, material selection, and design optimization, ensuring that the concept can move closer to industrial feasibility.

    A further step of the project involves building and testing a small-scale prototype. Through wind tunnel experiments and physical testing, the numerical models will be validated, providing essential insights into real performance. These validated results will then serve as the foundation for developing a Machine Learning algorithm – the Tilted VAWT Analysis and Optimization Code (TVDAOC).

  • Project goals

    By integrating advanced simulation techniques, experimental validation, and artificial intelligence, this project aims to push the boundaries of floating offshore wind technology. The expected outcomes include higher efficiency, reduced costs, and scalable solutions — key factors in making offshore wind in deep waters a viable and competitive energy source worldwide.

    Ultimately, the research will contribute to global efforts in decarbonization and energy security, offering an innovative pathway to harness one of the most abundant and underutilized renewable energy resources on the planet.

Participants

  • NMBU participants
  • External participants

    Hans Bernhoff - CTO at World-Wide-Wind (WWW)

    Giovanna Barigozzi - University of Bergamo