HIghly advanced Probabilistic design and Enhanced Reliability methods for high-value, cost-efficient offshore WIND

Informazioni relative al progetto

HIPERWIND

ID dell’accordo di sovvenzione: 101006689

DOI 10.3030/101006689

Progetto chiuso

Data della firma CE 8 Dicembre 2020

Data di avvio 1 Dicembre 2020

Data di completamento 31 Maggio 2024

Finanziato da

• SOCIETAL CHALLENGES - Secure, clean and efficient energy

Costo totale € 4 103 638,75

Contributo UE € 3 999 638,75

Coordinato da

DANMARKS TEKNISKE UNIVERSITET
Denmark

Risultati finali

Documents, reports (9)

Atmospheric-wave multi-scale flow modelling that will resolve the flow fields from mesoscale to farm/turbine scale

Atmosphericwave multiscale flow modelling that will resolve the flow fields from mesoscale to farmturbine scale Based on Tasks 21 22 23

Realistic representation of nonlinear wave conditions applicable for offshore wind turbine design

Realistic representation of nonlinear wave conditions applicable for offshore wind turbine design This will include uncertainty measures of the current methods and suggestions for an improved methodologies Based on Tasks 23 and 24

Aero-servo-hydro-elastic model uncertainty

Aeroservohydroelastic model uncertainty The report documents the uncertainty on aerodynamic loading and on hydrodynamic loading for the fixed and floating case study Based on task 32

Novel surrogate modelling approaches for wind turbine reliability assessment

Novel surrogate modelling approaches for wind turbine reliability assessment The report gathers the developments on dimensionality reduction with Kriging and Bayesian neural networks and compare their efficiency on a common case study Based on task 41

Wind farm parameterization and turbulent wind box generation

Wind farm parameterization and turbulent wind box generation Report on the results including the global sensitivity results on parameters as well as scripts for turbulence box generation Based on tasks 311 and 312

Turbine loading and wake model uncertainty

Turbine loading and wake model uncertainty The report documents the engineering model uncertainty from comparison to LES the probabilistic distribution of environmental parameters and the wind turbine clustering method Based on tasks 313 314 315

Dissemination strategy developed and in place

Dissemination strategy developed and in place. Task 7.5.

Quantification of the impact of electrical events on drivetrain mechanical component degradation

Quantification of the impact of electrical events on drivetrain mechanical component degradation Based on task 52

Offshore wind turbine drivetrain component degradation and lifing models

Offshore wind turbine drivetrain component degradation and lifing models Report on the development of the models and overview of their capabilities Based on task 51

Other (2)

Environmental joint probability distributions and uncertainties

Environmental joint probability distributions and uncertainties These include quantificationidentification of the sitespecific probability distributions of mean wind and wave conditions as well as return periods and magnitudes of transient events Based on tasks 22 23 24 25

Advanced O&M model

Advanced O&M model. The model will allow to compute accurate LCoE and value of wind energy and to define risk-based maintenance plans. Based on task 6.1.

Websites, patent fillings, videos etc. (2)

First project external workshop

First project external workshop Task 76

Project website established

Project website established. Task 7.6.

Pubblicazioni

Peer reviewed articles (11)

Load reduction for wind turbines: an output-constrained, subspace predictive repetitive control approach

Autori: Yichao Liu,Riccardo Ferrari, Jan-Willem van Wingerden
Pubblicato in: Wind Energy Science, Numero 23667451, 2022, ISSN 2366-7451
Editore: Copernicus
DOI: 10.5194/wes-7-523-2022

A truncated, translated Weibull distribution for shallow water sea states

Autori: Erik Vanem and Tiago Fazeres-Ferradosa
Pubblicato in: Coastal Engineering, 2022, ISSN 0378-3839
Editore: Elsevier BV
DOI: 10.1016/j.coastaleng.2021.104077

Mesoscale Simulation of Open Cellular Convection: Roles of Model Resolutions and Physics Parameterizations

Autori: Hai Bui and Mostafa Bakhoday-Paskyabi
Pubblicato in: Journal of Physics: Conference Series, Numero 17426596, 2022, ISSN 1742-6596
Editore: IOP Science
DOI: 10.1088/1742-6596/2362/1/012006

Virtual sensors for wind turbines based on Machine Learning

Autori: Nikolay Dimitrov, Tuhfe Gocmen
Pubblicato in: Wind Energy, 2022, ISSN 1099-1824
Editore: Wiley & Sons LTD
DOI: 10.1002/we.2762

Long-term analysis of wave-induced loads using High Order Spectral Method and direct sampling of extreme wave events

Autori: Odin Gramstadt, Thomas B. Johannessen, Gunnar Lian
Pubblicato in: Marine Structures, Numero Volume 91, 2023, Pagina/e 103473, ISSN 1873-4170
Editore: Elsevier
DOI: 10.1016/j.marstruc.2023.103473

On the ill-conditioning of the combined wind speed estimator and tip-speed ratio tracking control scheme

Autori: L Brandetti, Y Liu, SP Mulders, C Ferreira, S Watson and JW van Wingerden
Pubblicato in: Journal of Physics: Conference Series, Numero 17426596, 2022, ISSN 1742-6596
Editore: IOP Science
DOI: 10.1088/1742-6596/2265/3/032085

Analyzing Extreme Sea State Conditions by Time-Series Simulation Accounting for Seasonality

Autori: Erik Vanem
Pubblicato in: Journal of Offshore Mechanics and Arctic Engineering, 2023, ISSN 0892-7219
Editore: ASME
DOI: 10.1115/1.4056786

Analysing multivariate extreme conditions using environmental contours and accounting for serial dependence

Autori: Erik Vanem
Pubblicato in: Renewable Energy, 2023, ISSN 0960-1481
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.renene.2022.11.033

Quantifying and clustering the wake-induced perturbations within a wind farm for load analysis

Autori: A. Lovera, E. Fekhari, B. Jézéquel, M. Dupoiron, M. Guiton and E. Ardillon
Pubblicato in: Journal of Physics: Conference Series, 2023, Pagina/e Volume 2505, pages 012011, ISSN 1742-6596
Editore: IOP Science
DOI: 10.1088/1742-6596/2505/1/012011

A comprehensive code-to-code comparison study with the modified IEA15MW-UMaine Floating Wind Turbine for H2020 HIPERWIND project

Autori: Kim, T., Natarajan, A., Lovera, A., Julan, E., Peyrard, C., Capaldo, M., Huwart, G., Bozonnet, P., & Guiton, M
Pubblicato in: Journal of Physics: Conference Series, Numero 17426596, 2022, ISSN 1742-6596
Editore: IOPScience
DOI: 10.1088/1742-6596/2265/4/042006

Multiscale Simulation of Offshore Wind Variability During Frontal Passage: Brief Implication on Turbines' Wakes and Load

Autori: Mostafa Bakhoday-Paskyabi, Maria Krutova, Hai Bui and Xu Ning
Pubblicato in: Journal of Physics: Conference Series, 2022, ISSN 1742-6596
Editore: IOP Science
DOI: 10.1088/1742-6596/2362/1/012003

Conference proceedings (9)

Efficient techniques for fast uncertainty propagation in an offshore wind turbine multi-physics simulation tool

Autori: E. Fekhari, B. Iooss, V. Chabridon, J. Muré
Pubblicato in: Trends in Renewable Energies Offshore, 2022
Editore: HAL open science

Bernstein adaptive nonparametric conditional sampling: a new method for rare event probability estimation

Autori: Elias Fekhari, Vincent Chabridon, Bertrand Iooss, Joseph Muré
Pubblicato in: Proceedings of the International Conference on Application of Statistics and Probability in Civil Engineering, 2023
Editore: International Conference on Application of Statistics and Probability in Civil Engineering

Wake parametrization and surrogate modeling for loads and power prediction

Autori: N. Bonfils, G. Huwart, M. Guiton, T. Perdrizet
Pubblicato in: Proceedings of the WindEurope Technology workshop (2022), 2022
Editore: WindEurope

Drag coefficient Uncertainty for floating wind turbines

Autori: Fabien Robaux, Adria Borras Nadal, Christophe Peyrard, Michel Benoit, William Benguigui, Martin Guiton
Pubblicato in: Proceedings of the conference 18ème journées de l’hydrodynamique, Nov 2022, Poitiers, France., 2022
Editore: 18ème journées de l’hydrodynamique, Nov 2022, Poitiers, France.

Drag coefficient Uncertainty for floating wind turbines

Autori: F. Robaux, A. Borras Nadal, C. Peyrard, Michel Benoit, William Benguigui, M. Guiton
Pubblicato in: Journée Hydrodynamique Poitiers, France, 2022
Editore: Journée Hydrodynamique Poitiers

Analyzing extreme sea state conditions by time-series simulation

Autori: Erik Vanem
Pubblicato in: Proceedings of the ASME 2022 41st International Conference on Ocean, Offshore and Arctic Engineering OMAE 2022, 2022, ISBN 978-0-7918-8586-4
Editore: ASME
DOI: 10.1115/omae2022-78795

Deep learning-based modelling of wake-induced effects in wind farms

Autori: Suguang Dou, Nikolay Dimitrov
Pubblicato in: Proceedings of the WindEurope technology workshop (2022), 2022
Editore: WindEurope

A Joint Probability Distribution Model for Multivariate Wind and Wave Conditions

Autori: Erik Vanem, Elias Fekhari, Nikolay Dimitrov, Mark Kelly, Alexis Cousin, Martin Guiton
Pubblicato in: Proceedings series of the International Conference on Offshore Mechanics and Arctic Engineering (OMAE), 2023
Editore: ASME
DOI: 10.1115/omae2023-101961

Uncertainty evaluation of BEM approaches for offshore wind turbine design

Autori: M. L. Mayol, P. A. Joulin, N. K. Dimitrov, A. Lovera, S. Eldevik, A. Cousin, and M. Guiton
Pubblicato in: EMSRIM conference, 2022
Editore: EMSRIM conference