Sustainable resilient data-enabled offshore wind farm and control co-design

Informations projet

SUDOCO

N° de convention de subvention: 101122256

DOI

10.3030/101122256

Date de signature de la CE 21 Août 2023

Date de début 1 Octobre 2023

Date de fin 30 Septembre 2027

Financé au titre de

• Climate, Energy and Mobility

Coût total

€ 6 261 873,75

Contribution de l’UE

€ 6 261 873,75

Coordonné par

TECHNISCHE UNIVERSITEIT DELFT
Netherlands

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Documents, reports (4)

Reference scenarios

This deliverable relates to T3.1 where the scenarios used for both economic and environmental model development will be defined. The report will describe scenarios for value function modelling including environmental and economic parameter space.

Economic value function model

This report will contain a control-friendly economic model for calculating wind farm revenue, COVE and other economic metrics. The work related to this deliverable is performed in T3.2 dealing with the control-friendly economic model development, verification and uncertainty quantification.

Baseline wind farms

This deliverable is related to T1.1 In this task we will define two baseline wind farms: 1) a small 9 turbine windfarm with 15MW reference turbines that is also used in CL-Windcon, 2) a rotor diameter scaled version of the HKN wind farm lay-out with 69 IEA 20MW turbines. We will perform baseline Large Eddy Simulations (LES) simulations using EllipSys3D for all the reference cases and for dedicated time-varying atmospheric flow cases. Moreover, wewill develop a generic wind farm controller interface that is platform- and language-agnostic, thereby allowing the validation of complicated and closed-loop wind farm control solutions in various high-fidelity simulation software solutions.This deliverable will describe two baseline wind farms and a database with the results of the benchmarks simulations.

Environmental value function model

This deliverable reports the work performed in T3.3 on the control-friendly environmental model development, verification, and uncertainty quantification. The report will present a control-friendly environmental model for calculating offset and own CO2 emissions.

Publications

Peer reviewed articles (7)

Profit-optimal data-driven operation of a hybrid power plant participating in energy markets

Auteurs: A Anand, J Petzschmann, K Strecker, R Braunbehrens, A Kaifel, C L Bottasso
Publié dans: Journal of Physics: Conference Series, Numéro 2767, 2024, ISSN 1742-6596
Éditeur: IOP Publishing
DOI: 10.1088/1742-6596/2767/9/092069

Machine learning to rapidly predict turbine yaw angles for wake steering

Auteurs: Andrew P. J. Stanley, Tim Mulder, Bart Doekemeijer, Jasper Kreeft
Publié dans: Journal of Physics: Conference Series, Numéro 2767, 2024, ISSN 1742-6596
Éditeur: IOP Publishing
DOI: 10.1088/1742-6596/2767/8/082011

First experimental results on lifetime-aware wind farm control

Auteurs: R Braunbehrens, A Anand, F Campagnolo, C L Bottasso
Publié dans: Journal of Physics: Conference Series, Numéro 2767, 2024, ISSN 1742-6596
Éditeur: IOP Publishing
DOI: 10.1088/1742-6596/2767/3/032042DOWNLOADARTICLEPDF

How do technological choices affect the economic and environmental performance of offshore wind farms?

Auteurs: S Kainz, A Guilloré, C L Bottasso
Publié dans: Journal of Physics: Conference Series, Numéro 2767, 2024, ISSN 1742-6588
Éditeur: IOP Publishing
DOI: 10.1088/1742-6596/2767/8/082005

How do technological choices affect the economic and environmental performance of offshore wind farms?

Auteurs: S Kainz, A Guilloré, C L Bottasso
Publié dans: Journal of Physics: Conference Series, Numéro 2767, 2024, ISSN 1742-6588
Éditeur: IOP Publishing
DOI: 10.1088/ISSN.1742-6596

Closed-loop coupling of a dynamic wake model with a wind inflow estimator

Auteurs: J Di Cave, R Braunbehrens, J Krause, A Guilloré, C L Bottasso
Publié dans: Journal of Physics: Conference Series, Numéro 2767, 2024, ISSN 1742-6596
Éditeur: IOP Publishing Ltd.
DOI: 10.1088/1742-6596/2767/3/032034

Evaluating the potential of wake steering co-design for wind farm layout optimization through a tailored genetic algorithm

Auteurs: M. Baricchio, P. M. O. Gebraad, and J.-W. van Wingerden
Publié dans: Wind Energ. Sci., Numéro 11, 2024, ISSN 2366-7451
Éditeur: Copernicus
DOI: 10.5194/WES-9-2113-2024