Developing the Next Generation of Environmentally-Friendly Floating Wind Farms with Innovative Technologies and Sustainable Solutions

Información del proyecto

FLOATFARM

Identificador del acuerdo de subvención: 101136091

DOI

10.3030/101136091

Fecha de la firma de la CE 17 Noviembre 2023

Fecha de inicio 1 Enero 2024

Fecha de finalización 31 Diciembre 2027

Financiado con arreglo a

• Climate, Energy and Mobility

Coste total

€ 5 997 630,00

Aportación de la UE

€ 5 997 630,00

Coordinado por

TECHNISCHE UNIVERSITAT BERLIN
Germany

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Documents, reports (2)

Novel generator design and performance

The preliminary design of an innovative lightweight generator design that leverages Hagnesia’s patented technology will be carried out. The design will be optimized based on the requirements of the project. The characteristics of the direct-drive generator will be described.

Validated wake model for QBlade capable of modeling turbine interactions

In this task, a new wake model will be developed to increase the fidelity of the wake model within QBlade without sacrificing computational efficiency. TUB, with the help of DTU, will develop this new wake model, which will be released as an open-source flow solver (M12). This solver will be coupled to QBlade in order to allow fast simulation of active wake excitation methods. The wake model will be validated against unsteady wake measurements using data gathered in wind tunnel experiments at the TU Delft.

Other (2)

An Interface of HAWC2 to the Framework for Floating Offshore Turbine Design Optimization WEIS

The source code of the interface between HAWC2 and WEIS will be released on GitHub (or similar) together with a hands-on examples on its application and inital demonstration cases.

An Interface of QBlade to the Framework for Floating Offshore Turbine Design Optimization WEIS

The source code of the interface between QBlade and WEIS will be released on GitHub (or similar) together with a hands-on examples on its application and inital demonstration cases.

Publicaciones

Peer reviewed articles (1)

A Deep Learning Strategy for the Retrieval of Sea Wave Spectra from Marine Radar Data

Autores: Giovanni Ludeno, Giuseppe Esposito, Claudio Lugni, Francesco Soldovieri, Gianluca Gennarelli
Publicado en: Journal of Marine Science and Engineering, Edición 12, 2024, ISSN 2077-1312
Editor: MDPI AG
DOI: 10.3390/JMSE12091609