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

Livrables

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

Development and implementation of probabilistic and uncertainty quantification methods for reliability sensitivity analysis

Development and implementation of probabilistic and uncertainty quantification methods for reliability sensitivity analysis. Based on task 5.4.

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

Validation of the newly developed FLS and ULS distribution predictions and quantification of the resulting uncertainty reduction

Validation of the newly developed FLS and ULS distribution predictions and the quantification of the resulting uncertainty reduction. Based on task 4.5.

Quantification of the impacts of HIPERWIND on LCoE

Quantification of the impacts of HIPERWIND on LCoE. A summary report as well as an improved cost modelling tool are delivered. Based on task 6.2.

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

Final project report

Final project report. Task 7.4.

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

Validation of component lifing and reliability models including grid events

Validation of component lifing and reliability models including grid events. Based on task 5.3.

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

Quantification of the impacts of HIPERWIND on Market Value

Quantification of the impacts of HIPERWIND on Market Value. Based on task 6.3.

Floating wind turbine structural design procedure including SLS

Floating wind turbine structural design procedure including SLS. Includes development and quantification of the utilization of SLS for floating wind turbine structural design including the rotor-nacelle assembly.Based on task 4.4.

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

Methods for adaptive calculation of FLS loads and reliability, and their impact on probabilistic fatigue design

Methods for adaptive calculation of FLS loads and reliability, and their impact on probabilistic fatigue design. Based on task 4.3.

Methods for efficient ULS reliability calculations and their impact on probabilistic design

Methods for efficient ULS reliability calculations and their impact on probabilistic design. Based on task 4.2.

Final project workshop

Final project workshop. Task 7.6.

Second project external workshop

Second project external workshop. Task 7.6.

First project external workshop

First project external workshop Task 76

Project website established

Project website established. Task 7.6.

Exploitation roadmap

Exploitation roadmap. Task 7.5.

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.

Publications

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

Auteurs: Yichao Liu,Riccardo Ferrari, Jan-Willem van Wingerden
Publié dans: Wind Energy Science, Numéro 23667451, 2022, ISSN 2366-7451
Éditeur: Copernicus
DOI: 10.5194/wes-7-523-2022

A truncated, translated Weibull distribution for shallow water sea states

Auteurs: Erik Vanem and Tiago Fazeres-Ferradosa
Publié dans: Coastal Engineering, 2022, ISSN 0378-3839
Éditeur: Elsevier BV
DOI: 10.1016/j.coastaleng.2021.104077

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

Auteurs: Hai Bui and Mostafa Bakhoday-Paskyabi
Publié dans: Journal of Physics: Conference Series, Numéro 17426596, 2022, ISSN 1742-6596
Éditeur: IOP Science
DOI: 10.1088/1742-6596/2362/1/012006

Gaussian wake model fitting in a transient event over Alpha Ventus wind farm

Auteurs: Maria Krutova, Mostafa Bakhoday-Paskyabi
Publié dans: Wind Energy Science Journal, 2023, ISSN 2366-7451
Éditeur: Copernicus Gmbh
DOI: 10.5194/wes-2023-79

Virtual sensors for wind turbines based on Machine Learning

Auteurs: Nikolay Dimitrov, Tuhfe Gocmen
Publié dans: Wind Energy, 2022, ISSN 1099-1824
Éditeur: Wiley & Sons LTD
DOI: 10.1002/we.2762

Modelling of turbine power and local wind conditions in wind farm using an autoencoder neural network

Auteurs: Suguang Dou, Nikolay Dimitrov
Publié dans: Journal of Physics: Conference Series, Numéro 2265, 2022, Page(s) 032069, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/2265/3/032069

Evaluation of sea surface roughness parameterization in meso-to-micro scale simulation of the offshore wind field

Auteurs: Xu Ning, Mostafa Bakhoday Paskyabi, Hoang Hai Bui, Mohammadreza Mohammadpour Penchah
Publié dans: Journal of Wind Engineering and Industrial Aerodynamics, Numéro 242, 2024, Page(s) 105592, ISSN 0167-6105
Éditeur: Elsevier BV
DOI: 10.1016/j.jweia.2023.105592

Impact of swell waves on atmospheric surface turbulence: wave–turbulence decomposition methods

Auteurs: Mostafa Bakhoday Paskyabi
Publié dans: Wind Energy Science, Numéro 9, 2024, Page(s) 1631-1645, ISSN 2366-7451
Éditeur: Copernicus Gmbh
DOI: 10.5194/wes-9-1631-2024

Comparison of probabilistic structural reliability methods for ultimate limit state assessment of wind turbines

Auteurs: Hong Wang, Odin Gramstad, Styfen Schär, Stefano Marelli, Erik Vanem
Publié dans: Structural Safety, Numéro 111, 2024, Page(s) 102502, ISSN 0167-4730
Éditeur: Elsevier BV
DOI: 10.1016/j.strusafe.2024.102502

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

Auteurs: Odin Gramstadt, Thomas B. Johannessen, Gunnar Lian
Publié dans: Marine Structures, Numéro Volume 91, 2023, Page(s) 103473, ISSN 1873-4170
Éditeur: 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

Auteurs: L Brandetti, Y Liu, SP Mulders, C Ferreira, S Watson and JW van Wingerden
Publié dans: Journal of Physics: Conference Series, Numéro 17426596, 2022, ISSN 1742-6596
Éditeur: IOP Science
DOI: 10.1088/1742-6596/2265/3/032085

Flow acceleration statistics: a new paradigm for wind-driven loads, towards probabilistic turbine design

Auteurs: Mark Kelly
Publié dans: Wind Energy Science Journal, 2025, ISSN 2366-7451
Éditeur: Copernicus GmbH
DOI: 10.5194/wes-2024-69

Given-data probabilistic fatigue assessment for offshore wind turbines using Bayesian quadrature

Auteurs: Elias Fekhari, Vincent Chabridon, Joseph Muré, Bertrand Iooss
Publié dans: Data-Centric Engineering, Numéro 5, 2024, ISSN 2632-6736
Éditeur: Cambridge University Press
DOI: 10.1017/dce.2023.27

Emulating the dynamics of complex systems using autoregressive models on manifolds (mNARX)

Auteurs: Styfen Schär, Stefano Marelli, Bruno Sudret
Publié dans: Mechanical Systems and Signal Processing, Numéro 208, 2024, Page(s) 110956, ISSN 0888-3270
Éditeur: Academic Press
DOI: 10.1016/j.ymssp.2023.110956

Parameterization of Wave‐Induced Stress in Large‐Eddy Simulations of the Marine Atmospheric Boundary Layer

Auteurs: Xu Ning, Mostafa Bakhoday Paskyabi
Publié dans: Journal of Geophysical Research: Oceans, Numéro 129, 2024, ISSN 2169-9275
Éditeur: AGU
DOI: 10.1029/2023jc020722

End-to-end wind turbine design under uncertainties: a practical example

Auteurs: NK Dimitrov, M Kelly, M. McWilliam, M Guiton, A Cousin, PA Joulin, ML Mayol, M Munoz-Zuniga, L Franceschini, A Lovera, E Fekhari, E Ardillon, C Peyrard, M Bakhoday-Paskyabi, S Marelli, S Schar, E Vanem, C Agrell, O Gramstad, H Wang
Publié dans: Journal of Physics: Conference Series, Numéro 2767, 2024, Page(s) 082017, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/2767/8/082017

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

Auteurs: Erik Vanem
Publié dans: Journal of Offshore Mechanics and Arctic Engineering, 2023, ISSN 0892-7219
Éditeur: ASME
DOI: 10.1115/1.4056786

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

Auteurs: Erik Vanem
Publié dans: Renewable Energy, 2023, ISSN 0960-1481
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.renene.2022.11.033

Implementation of a Simple Actuator Disk for Large-Eddy Simulation in the Weather Research and Forecasting Model (WRF-SADLES v1.2) for wind turbine wake simulation

Auteurs: Hai Bui, Mostafa Bakhoday-Paskyabi, Mohammadreza Mohammadpour-Penchah
Publié dans: Geoscientific Model Development, Numéro 17, 2024, Page(s) 4447-4465, ISSN 1991-9603
Éditeur: Copernicus Gmbh
DOI: 10.5194/gmd-17-4447-2024

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

Auteurs: A. Lovera, E. Fekhari, B. Jézéquel, M. Dupoiron, M. Guiton and E. Ardillon
Publié dans: Journal of Physics: Conference Series, 2023, Page(s) Volume 2505, pages 012011, ISSN 1742-6596
Éditeur: IOP Science
DOI: 10.1088/1742-6596/2505/1/012011

A Joint Probability Distribution for Multivariate Wind-Wave Conditions and Discussions on Uncertainties

Auteurs: Erik Vanem, Elias Fekhari, Nikolay Dimitrov, Mark Kelly, Alexis Cousin, Martin Guiton
Publié dans: Journal of Offshore Mechanics and Arctic Engineering, Numéro 146, 2024, ISSN 0892-7219
Éditeur: ASME
DOI: 10.1115/1.4064498

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

Auteurs: Kim, T., Natarajan, A., Lovera, A., Julan, E., Peyrard, C., Capaldo, M., Huwart, G., Bozonnet, P., & Guiton, M
Publié dans: Journal of Physics: Conference Series, Numéro 17426596, 2022, ISSN 1742-6596
Éditeur: IOPScience
DOI: 10.1088/1742-6596/2265/4/042006

An open-source Python-based tool for Mann turbulence generation with constraints and non-Gaussian capabilities

Auteurs: Nikolay Dimitrov, Mads Pedersen, Ásta Hannesdóttir
Publié dans: Journal of Physics: Conference Series, Numéro 2767, 2024, Page(s) 052058, ISSN 1742-6588
Éditeur: Institute of Physics
DOI: 10.1088/1742-6596/2767/5/052058

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

Auteurs: Mostafa Bakhoday-Paskyabi, Maria Krutova, Hai Bui and Xu Ning
Publié dans: Journal of Physics: Conference Series, 2022, ISSN 1742-6596
Éditeur: IOP Science
DOI: 10.1088/1742-6596/2362/1/012003

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

Auteurs: E. Fekhari, B. Iooss, V. Chabridon, J. Muré
Publié dans: Trends in Renewable Energies Offshore, 2022
Éditeur: HAL open science

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

Auteurs: Elias Fekhari, Vincent Chabridon, Bertrand Iooss, Joseph Muré
Publié dans: Proceedings of the International Conference on Application of Statistics and Probability in Civil Engineering, 2023
Éditeur: International Conference on Application of Statistics and Probability in Civil Engineering

Wake parametrization and surrogate modeling for loads and power prediction

Auteurs: N. Bonfils, G. Huwart, M. Guiton, T. Perdrizet
Publié dans: Proceedings of the WindEurope Technology workshop (2022), 2022
Éditeur: WindEurope

A novel strategy to surrogate the transient response of wind turbine simulations

Auteurs: Schär, Styfen; Marelli, Stefano; Sudret, Bruno
Publié dans: MASCOT-NUM Annual Meeting 2022, Clermont Ferrand, France, June 7–9, 2022, Numéro 4, 2022
Éditeur: ETH Zurich, Institute of Structural Engineering
DOI: 10.3929/ethz-b-000588038

Drag coefficient Uncertainty for floating wind turbines

Auteurs: Fabien Robaux, Adria Borras Nadal, Christophe Peyrard, Michel Benoit, William Benguigui, Martin Guiton
Publié dans: Proceedings of the conference 18ème journées de l’hydrodynamique, Nov 2022, Poitiers, France., 2022
Éditeur: 18ème journées de l’hydrodynamique, Nov 2022, Poitiers, France.

Reliability analysis of wind turbines using manifold-NARX surrogate models

Auteurs: Schär, Styfen; id_orcid0000-0001-6715-220X; Marelli, Stefano; id_orcid0000-0002-9268-9014; Sudret, Bruno; id_orcid0000-0002-9501-7395
Publié dans: Engineering Mechanics Institute 2023 International Conference (EMI 2023), Palermo, Italy, August 27-30, 2023, Numéro 1, 2023
Éditeur: ETH Zurich
DOI: 10.3929/ethz-b-000638791

Drag coefficient Uncertainty for floating wind turbines

Auteurs: F. Robaux, A. Borras Nadal, C. Peyrard, Michel Benoit, William Benguigui, M. Guiton
Publié dans: Journée Hydrodynamique Poitiers, France, 2022
Éditeur: Journée Hydrodynamique Poitiers

Analyzing extreme sea state conditions by time-series simulation

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

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

Auteurs: Suguang Dou, Nikolay Dimitrov
Publié dans: Proceedings of the WindEurope technology workshop (2022), 2022
Éditeur: WindEurope

A Joint Probability Distribution Model for Multivariate Wind and Wave Conditions

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

Autoregressive surrogate models of high-dimensional time-dependent wind turbine simulations for uncertainty quantification

Auteurs: Schär, Styfen; Marelli, Stefano; id_orcid0000-0002-9268-9014; Sudret, Bruno; id_orcid0000-0002-9501-7395
Publié dans: Engineering Mechanics Institute Conference (EMI 2022), Baltimore, MD, USA, May 31 – June 3, 2022, Numéro 1, 2022
Éditeur: ETH Zurich, Institute of Structural Engineering
DOI: 10.3929/ethz-b-000588042

Uncertainty evaluation of BEM approaches for offshore wind turbine design

Auteurs: M. L. Mayol, P. A. Joulin, N. K. Dimitrov, A. Lovera, S. Eldevik, A. Cousin, and M. Guiton
Publié dans: EMSRIM conference, 2022
Éditeur: EMSRIM conference

A Simulation Study on the Usefulness of the Bernstein Copula for Statistical Modeling of Metocean Variables

Auteurs: Erik Vanem, Øystein Lande, Elias Fekhari
Publié dans: Volume 2: Structures, Safety, and Reliability, 2024
Éditeur: American Society of Mechanical Engineers
DOI: 10.1115/omae2024-121159

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