Articles | Volume 8, issue 1
https://doi.org/10.5194/wes-8-25-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-8-25-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Jan 2023
Research article |
| 04 Jan 2023
| 04 Jan 2023
Sensitivity analysis of the effect of wind and wake characteristics on wind turbine loads in a small wind farm
National Renewable Energy Laboratory, Golden, Colorado, USA
Amy N. Robertson
National Renewable Energy Laboratory, Golden, Colorado, USA
Jason Jonkman
National Renewable Energy Laboratory, Golden, Colorado, USA
Related authors
Kelsey Shaler, Eliot Quon, Hristo Ivanov, and Jason Jonkman
Wind Energ. Sci., 9, 1451–1463, https://doi.org/10.5194/wes-9-1451-2024, https://doi.org/10.5194/wes-9-1451-2024, 2024
Short summary
Short summary
This paper presents a three-way verification and validation between an engineering-fidelity model, a high-fidelity model, and measured data for the wind farm structural response and wake dynamics during an evolving stable boundary layer of a small wind farm, generally with good agreement.
Roger Bergua, Will Wiley, Amy Robertson, Jason Jonkman, Cédric Brun, Jean-Philippe Pineau, Quan Qian, Wen Maoshi, Alec Beardsell, Joshua Cutler, Fabio Pierella, Christian Anker Hansen, Wei Shi, Jie Fu, Lehan Hu, Prokopios Vlachogiannis, Christophe Peyrard, Christopher Simon Wright, Dallán Friel, Øyvind Waage Hanssen-Bauer, Carlos Renan dos Santos, Eelco Frickel, Hafizul Islam, Arjen Koop, Zhiqiang Hu, Jihuai Yang, Tristan Quideau, Violette Harnois, Kelsey Shaler, Stefan Netzband, Daniel Alarcón, Pau Trubat, Aengus Connolly, Seán B. Leen, and Oisín Conway
Wind Energ. Sci., 9, 1025–1051, https://doi.org/10.5194/wes-9-1025-2024, https://doi.org/10.5194/wes-9-1025-2024, 2024
Short summary
Short summary
This paper provides a comparison for a floating offshore wind turbine between the motion and loading estimated by numerical models and measurements. The floating support structure is a novel design that includes a counterweight to provide floating stability to the system. The comparison between numerical models and the measurements includes system motion, tower loads, mooring line loads, and loading within the floating support structure.
Regis Thedin, Garrett Barter, Jason Jonkman, Rafael Mudafort, Christopher J. Bay, Kelsey Shaler, and Jasper Kreeft
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-6, https://doi.org/10.5194/wes-2024-6, 2024
Revised manuscript accepted for WES
Short summary
Short summary
This work investigates asymmetries in terms of power performance and fatigue loading on a 5-turbine wind farm subject to wake steering strategies. Both the yaw misalignment angle and the wind direction were varied from negative to positive. We highlight conditions in which fatigue loading is lower while still maintenance good power gains and show that partial wake is the source of the asymmetries observed. We provide recommendations in terms of yaw misalignment angles for a given wind direction.
Will Wiley, Jason Jonkman, Amy Robertson, and Kelsey Shaler
Wind Energ. Sci., 8, 1575–1595, https://doi.org/10.5194/wes-8-1575-2023, https://doi.org/10.5194/wes-8-1575-2023, 2023
Short summary
Short summary
A sensitivity analysis determined the modeling parameters for an operating floating offshore wind turbine with the biggest impact on the ultimate and fatigue loads. The loads were the most sensitive to the standard deviation of the wind speed. Ultimate and fatigue mooring loads were highly sensitive to the current speed; only the fatigue mooring loads were sensitive to wave parameters. The largest platform rotation was the most sensitive to the platform horizontal center of gravity.
Paula Doubrawa, Kelsey Shaler, and Jason Jonkman
Wind Energ. Sci., 8, 1475–1493, https://doi.org/10.5194/wes-8-1475-2023, https://doi.org/10.5194/wes-8-1475-2023, 2023
Short summary
Short summary
Wind turbines are designed to withstand any wind conditions they might encounter. This includes high-turbulence flow fields found within wind farms due to the presence of the wind turbines themselves. The international standard allows for two ways to account for wind farm turbulence in the design process. We compared both ways and found large differences between them. To avoid overdesign and enable a site-specific design, we suggest moving towards validated, higher-fidelity simulation tools.
Kelsey Shaler, Benjamin Anderson, Luis A. Martínez-Tossas, Emmanuel Branlard, and Nick Johnson
Wind Energ. Sci., 8, 383–399, https://doi.org/10.5194/wes-8-383-2023, https://doi.org/10.5194/wes-8-383-2023, 2023
Short summary
Short summary
Free-vortex wake (OLAF) and low-fidelity blade-element momentum (BEM) structural results are compared to high-fidelity simulation results for a flexible downwind turbine for varying inflow conditions. Overall, OLAF results were more consistent than BEM results when compared to SOWFA results under challenging inflow conditions. Differences between OLAF and BEM results were dominated by yaw misalignment angle, with varying shear exponent and turbulence intensity causing more subtle differences.
Amy N. Robertson, Kelsey Shaler, Latha Sethuraman, and Jason Jonkman
Wind Energ. Sci., 4, 479–513, https://doi.org/10.5194/wes-4-479-2019, https://doi.org/10.5194/wes-4-479-2019, 2019
Short summary
Short summary
This paper identifies the most sensitive parameters for the load response of a 5 MW wind turbine. Two sets of parameters are examined: one set relating to the wind excitation characteristics and a second related to the physical properties of the wind turbine. The two sensitivity analyses are done separately, and the top most-sensitive parameters are identified for different load outputs throughout the structure. The findings will guide future validation campaigns and measurement needs.
Will Wiley, Jason Jonkman, and Amy Robertson
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-130, https://doi.org/10.5194/wes-2024-130, 2024
Preprint under review for WES
Short summary
Short summary
Numerical models, used to assess loads on floating offshore wind turbines, require many input parameters to describe air and water conditions, system properties, and load calculations. All parameters have some possible range, due to uncertainty and/or variations with time. The selected values can have important effects on the uncertainty in the resulting loads. This work identifies the input parameters that have the most impact on ultimate and fatigue loads for extreme storm load cases.
Lucas Carmo, Jason Jonkman, and Regis Thedin
Wind Energ. Sci., 9, 1827–1847, https://doi.org/10.5194/wes-9-1827-2024, https://doi.org/10.5194/wes-9-1827-2024, 2024
Short summary
Short summary
As floating wind turbines progress to arrays with multiple units, it becomes important to understand how the wake of a floating turbine affects the performance of other units in the array. Due to the compliance of the floating substructure, the wake of a floating wind turbine may behave differently from that of a fixed turbine. In this work, we present an investigation of the mutual interaction between the motions of floating wind turbines and wakes.
Kenneth Brown, Pietro Bortolotti, Emmanuel Branlard, Mayank Chetan, Scott Dana, Nathaniel deVelder, Paula Doubrawa, Nicholas Hamilton, Hristo Ivanov, Jason Jonkman, Christopher Kelley, and Daniel Zalkind
Wind Energ. Sci., 9, 1791–1810, https://doi.org/10.5194/wes-9-1791-2024, https://doi.org/10.5194/wes-9-1791-2024, 2024
Short summary
Short summary
This paper presents a study of the popular wind turbine design tool OpenFAST. We compare simulation results to measurements obtained from a 2.8 MW land-based wind turbine. Measured wind conditions were used to generate turbulent flow fields through several techniques. We show that successful validation of the tool is not strongly dependent on the inflow generation technique used for mean quantities of interest. The type of inflow assimilation method has a larger effect on fatigue quantities.
Kelsey Shaler, Eliot Quon, Hristo Ivanov, and Jason Jonkman
Wind Energ. Sci., 9, 1451–1463, https://doi.org/10.5194/wes-9-1451-2024, https://doi.org/10.5194/wes-9-1451-2024, 2024
Short summary
Short summary
This paper presents a three-way verification and validation between an engineering-fidelity model, a high-fidelity model, and measured data for the wind farm structural response and wake dynamics during an evolving stable boundary layer of a small wind farm, generally with good agreement.
Francesco Papi, Jason Jonkman, Amy Robertson, and Alessandro Bianchini
Wind Energ. Sci., 9, 1069–1088, https://doi.org/10.5194/wes-9-1069-2024, https://doi.org/10.5194/wes-9-1069-2024, 2024
Short summary
Short summary
Blade element momentum (BEM) theory is the backbone of many industry-standard aerodynamic models. However, the analysis of floating offshore wind turbines (FOWTs) introduces new challenges, which could put BEM models to the test. This study systematically compares four aerodynamic models, ranging from BEM to computational fluid dynamics, in an attempt to shed light on the unsteady aerodynamic phenomena that are at stake in FOWTs and whether BEM is able to model them appropriately.
Roger Bergua, Will Wiley, Amy Robertson, Jason Jonkman, Cédric Brun, Jean-Philippe Pineau, Quan Qian, Wen Maoshi, Alec Beardsell, Joshua Cutler, Fabio Pierella, Christian Anker Hansen, Wei Shi, Jie Fu, Lehan Hu, Prokopios Vlachogiannis, Christophe Peyrard, Christopher Simon Wright, Dallán Friel, Øyvind Waage Hanssen-Bauer, Carlos Renan dos Santos, Eelco Frickel, Hafizul Islam, Arjen Koop, Zhiqiang Hu, Jihuai Yang, Tristan Quideau, Violette Harnois, Kelsey Shaler, Stefan Netzband, Daniel Alarcón, Pau Trubat, Aengus Connolly, Seán B. Leen, and Oisín Conway
Wind Energ. Sci., 9, 1025–1051, https://doi.org/10.5194/wes-9-1025-2024, https://doi.org/10.5194/wes-9-1025-2024, 2024
Short summary
Short summary
This paper provides a comparison for a floating offshore wind turbine between the motion and loading estimated by numerical models and measurements. The floating support structure is a novel design that includes a counterweight to provide floating stability to the system. The comparison between numerical models and the measurements includes system motion, tower loads, mooring line loads, and loading within the floating support structure.
Regis Thedin, Garrett Barter, Jason Jonkman, Rafael Mudafort, Christopher J. Bay, Kelsey Shaler, and Jasper Kreeft
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-6, https://doi.org/10.5194/wes-2024-6, 2024
Revised manuscript accepted for WES
Short summary
Short summary
This work investigates asymmetries in terms of power performance and fatigue loading on a 5-turbine wind farm subject to wake steering strategies. Both the yaw misalignment angle and the wind direction were varied from negative to positive. We highlight conditions in which fatigue loading is lower while still maintenance good power gains and show that partial wake is the source of the asymmetries observed. We provide recommendations in terms of yaw misalignment angles for a given wind direction.
Emmanuel Branlard, Jason Jonkman, Cameron Brown, and Jiatian Zhang
Wind Energ. Sci., 9, 1–24, https://doi.org/10.5194/wes-9-1-2024, https://doi.org/10.5194/wes-9-1-2024, 2024
Short summary
Short summary
In this work, we implement, verify, and validate a physics-based digital twin solution applied to a floating offshore wind turbine. The article present methods to obtain reduced-order models of floating wind turbines. The models are used to form a digital twin which combines measurements from the TetraSpar prototype (a full-scale floating offshore wind turbine) to estimate signals that are not typically measured.
Stefano Cioni, Francesco Papi, Leonardo Pagamonci, Alessandro Bianchini, Néstor Ramos-García, Georg Pirrung, Rémi Corniglion, Anaïs Lovera, Josean Galván, Ronan Boisard, Alessandro Fontanella, Paolo Schito, Alberto Zasso, Marco Belloli, Andrea Sanvito, Giacomo Persico, Lijun Zhang, Ye Li, Yarong Zhou, Simone Mancini, Koen Boorsma, Ricardo Amaral, Axelle Viré, Christian W. Schulz, Stefan Netzband, Rodrigo Soto-Valle, David Marten, Raquel Martín-San-Román, Pau Trubat, Climent Molins, Roger Bergua, Emmanuel Branlard, Jason Jonkman, and Amy Robertson
Wind Energ. Sci., 8, 1659–1691, https://doi.org/10.5194/wes-8-1659-2023, https://doi.org/10.5194/wes-8-1659-2023, 2023
Short summary
Short summary
Simulations of different fidelities made by the participants of the OC6 project Phase III are compared to wind tunnel wake measurements on a floating wind turbine. Results in the near wake confirm that simulations and experiments tend to diverge from the expected linearized quasi-steady behavior when the reduced frequency exceeds 0.5. In the far wake, the impact of platform motion is overestimated by simulations and even seems to be oriented to the generation of a wake less prone to dissipation.
Will Wiley, Jason Jonkman, Amy Robertson, and Kelsey Shaler
Wind Energ. Sci., 8, 1575–1595, https://doi.org/10.5194/wes-8-1575-2023, https://doi.org/10.5194/wes-8-1575-2023, 2023
Short summary
Short summary
A sensitivity analysis determined the modeling parameters for an operating floating offshore wind turbine with the biggest impact on the ultimate and fatigue loads. The loads were the most sensitive to the standard deviation of the wind speed. Ultimate and fatigue mooring loads were highly sensitive to the current speed; only the fatigue mooring loads were sensitive to wave parameters. The largest platform rotation was the most sensitive to the platform horizontal center of gravity.
Paula Doubrawa, Kelsey Shaler, and Jason Jonkman
Wind Energ. Sci., 8, 1475–1493, https://doi.org/10.5194/wes-8-1475-2023, https://doi.org/10.5194/wes-8-1475-2023, 2023
Short summary
Short summary
Wind turbines are designed to withstand any wind conditions they might encounter. This includes high-turbulence flow fields found within wind farms due to the presence of the wind turbines themselves. The international standard allows for two ways to account for wind farm turbulence in the design process. We compared both ways and found large differences between them. To avoid overdesign and enable a site-specific design, we suggest moving towards validated, higher-fidelity simulation tools.
Paul Veers, Carlo L. Bottasso, Lance Manuel, Jonathan Naughton, Lucy Pao, Joshua Paquette, Amy Robertson, Michael Robinson, Shreyas Ananthan, Thanasis Barlas, Alessandro Bianchini, Henrik Bredmose, Sergio González Horcas, Jonathan Keller, Helge Aagaard Madsen, James Manwell, Patrick Moriarty, Stephen Nolet, and Jennifer Rinker
Wind Energ. Sci., 8, 1071–1131, https://doi.org/10.5194/wes-8-1071-2023, https://doi.org/10.5194/wes-8-1071-2023, 2023
Short summary
Short summary
Critical unknowns in the design, manufacturing, and operation of future wind turbine and wind plant systems are articulated, and key research activities are recommended.
Roger Bergua, Amy Robertson, Jason Jonkman, Emmanuel Branlard, Alessandro Fontanella, Marco Belloli, Paolo Schito, Alberto Zasso, Giacomo Persico, Andrea Sanvito, Ervin Amet, Cédric Brun, Guillén Campaña-Alonso, Raquel Martín-San-Román, Ruolin Cai, Jifeng Cai, Quan Qian, Wen Maoshi, Alec Beardsell, Georg Pirrung, Néstor Ramos-García, Wei Shi, Jie Fu, Rémi Corniglion, Anaïs Lovera, Josean Galván, Tor Anders Nygaard, Carlos Renan dos Santos, Philippe Gilbert, Pierre-Antoine Joulin, Frédéric Blondel, Eelco Frickel, Peng Chen, Zhiqiang Hu, Ronan Boisard, Kutay Yilmazlar, Alessandro Croce, Violette Harnois, Lijun Zhang, Ye Li, Ander Aristondo, Iñigo Mendikoa Alonso, Simone Mancini, Koen Boorsma, Feike Savenije, David Marten, Rodrigo Soto-Valle, Christian W. Schulz, Stefan Netzband, Alessandro Bianchini, Francesco Papi, Stefano Cioni, Pau Trubat, Daniel Alarcon, Climent Molins, Marion Cormier, Konstantin Brüker, Thorsten Lutz, Qing Xiao, Zhongsheng Deng, Florence Haudin, and Akhilesh Goveas
Wind Energ. Sci., 8, 465–485, https://doi.org/10.5194/wes-8-465-2023, https://doi.org/10.5194/wes-8-465-2023, 2023
Short summary
Short summary
This work examines if the motion experienced by an offshore floating wind turbine can significantly affect the rotor performance. It was observed that the system motion results in variations in the load, but these variations are not critical, and the current simulation tools capture the physics properly. Interestingly, variations in the rotor speed or the blade pitch angle can have a larger impact than the system motion itself.
Kelsey Shaler, Benjamin Anderson, Luis A. Martínez-Tossas, Emmanuel Branlard, and Nick Johnson
Wind Energ. Sci., 8, 383–399, https://doi.org/10.5194/wes-8-383-2023, https://doi.org/10.5194/wes-8-383-2023, 2023
Short summary
Short summary
Free-vortex wake (OLAF) and low-fidelity blade-element momentum (BEM) structural results are compared to high-fidelity simulation results for a flexible downwind turbine for varying inflow conditions. Overall, OLAF results were more consistent than BEM results when compared to SOWFA results under challenging inflow conditions. Differences between OLAF and BEM results were dominated by yaw misalignment angle, with varying shear exponent and turbulence intensity causing more subtle differences.
Koen Boorsma, Gerard Schepers, Helge Aagard Madsen, Georg Pirrung, Niels Sørensen, Galih Bangga, Manfred Imiela, Christian Grinderslev, Alexander Meyer Forsting, Wen Zhong Shen, Alessandro Croce, Stefano Cacciola, Alois Peter Schaffarczyk, Brandon Lobo, Frederic Blondel, Philippe Gilbert, Ronan Boisard, Leo Höning, Luca Greco, Claudio Testa, Emmanuel Branlard, Jason Jonkman, and Ganesh Vijayakumar
Wind Energ. Sci., 8, 211–230, https://doi.org/10.5194/wes-8-211-2023, https://doi.org/10.5194/wes-8-211-2023, 2023
Short summary
Short summary
Within the framework of the fourth phase of the International Energy Agency's (IEA) Wind Task 29, a large comparison exercise between measurements and aeroelastic simulations has been carried out. Results were obtained from more than 19 simulation tools of various fidelity, originating from 12 institutes and compared to state-of-the-art field measurements. The result is a unique insight into the current status and accuracy of rotor aerodynamic modeling.
Jason M. Jonkman, Emmanuel S. P. Branlard, and John P. Jasa
Wind Energ. Sci., 7, 559–571, https://doi.org/10.5194/wes-7-559-2022, https://doi.org/10.5194/wes-7-559-2022, 2022
Short summary
Short summary
This paper summarizes efforts done to understand the impact of design parameter variations in the physical system (e.g., mass, stiffness, geometry, aerodynamic, and hydrodynamic coefficients) on the linearized system using OpenFAST in support of the development of the WEIS toolset to enable controls co-design of floating offshore wind turbines.
Emmanuel Branlard, Ian Brownstein, Benjamin Strom, Jason Jonkman, Scott Dana, and Edward Ian Baring-Gould
Wind Energ. Sci., 7, 455–467, https://doi.org/10.5194/wes-7-455-2022, https://doi.org/10.5194/wes-7-455-2022, 2022
Short summary
Short summary
In this work, we present an aerodynamic tool that can model an arbitrary collections of wings, blades, rotors, and towers. With these functionalities, the tool can be used to study and design advanced wind energy concepts, such as horizontal-axis wind turbines, vertical-axis wind turbines, kites, or multi-rotors. This article describes the key features of the tool and presents multiple applications. Field measurements of horizontal- and vertical-axis wind turbines are used for comparison.
Matthias Kretschmer, Jason Jonkman, Vasilis Pettas, and Po Wen Cheng
Wind Energ. Sci., 6, 1247–1262, https://doi.org/10.5194/wes-6-1247-2021, https://doi.org/10.5194/wes-6-1247-2021, 2021
Short summary
Short summary
We perform a validation of the new simulation tool FAST.Farm for the prediction of power output and structural loads in single wake conditions with respect to measurement data from the offshore wind farm alpha ventus. With a new wake-added turbulence functionality added to FAST.Farm, good agreement between simulations and measurements is achieved for the considered quantities. We hereby give insights into load characteristics of an offshore wind turbine subjected to single wake conditions.
Amy N. Robertson, Kelsey Shaler, Latha Sethuraman, and Jason Jonkman
Wind Energ. Sci., 4, 479–513, https://doi.org/10.5194/wes-4-479-2019, https://doi.org/10.5194/wes-4-479-2019, 2019
Short summary
Short summary
This paper identifies the most sensitive parameters for the load response of a 5 MW wind turbine. Two sets of parameters are examined: one set relating to the wind excitation characteristics and a second related to the physical properties of the wind turbine. The two sensitivity analyses are done separately, and the top most-sensitive parameters are identified for different load outputs throughout the structure. The findings will guide future validation campaigns and measurement needs.
Peter Graf, Katherine Dykes, Rick Damiani, Jason Jonkman, and Paul Veers
Wind Energ. Sci., 3, 475–487, https://doi.org/10.5194/wes-3-475-2018, https://doi.org/10.5194/wes-3-475-2018, 2018
Short summary
Short summary
Current approaches to wind turbine extreme load estimation are insufficient to routinely and reliably make required estimates over 50-year return periods. Our work hybridizes the two main approaches and casts the problem as stochastic optimization. However, the extreme variability in turbine response implies even an optimal sampling strategy needs unrealistic computing resources. We therefore conclude that further improvement requires better understanding of the underlying causes of loads.
Srinivas Guntur, Jason Jonkman, Ryan Sievers, Michael A. Sprague, Scott Schreck, and Qi Wang
Wind Energ. Sci., 2, 443–468, https://doi.org/10.5194/wes-2-443-2017, https://doi.org/10.5194/wes-2-443-2017, 2017
Short summary
Short summary
This paper presents a validation and code-to-code verification of the U.S. Dept of Energy/NREL wind turbine aeroelastic code, FAST v8, on a 2.3 MW wind turbine. Model validation is critical to any model-based research and development activity, and validation efforts on large turbines, as the current one, are extremely rare, mainly due to the scale. This paper, which was a collaboration between NREL and Siemens Wind Power, successfully demonstrates and validates the capabilities of FAST.
Related subject area
Thematic area: Materials and operation | Topic: Fatigue
Probabilistic surrogate modeling of damage equivalent loads on onshore and offshore wind turbines using mixture density networks
Effect of scour on the fatigue life of offshore wind turbines and its prevention through passive structural control
Review of rolling contact fatigue life calculation for oscillating bearings and application-dependent recommendations for use
Data-driven surrogate model for wind turbine damage equivalent load
Quantifying the effect of low-frequency fatigue dynamics on offshore wind turbine foundations: a comparative study
Probabilistic temporal extrapolation of fatigue damage of offshore wind turbine substructures based on strain measurements
Damage equivalent load synthesis and stochastic extrapolation for fatigue life validation
Deepali Singh, Richard Dwight, and Axelle Viré
Wind Energ. Sci., 9, 1885–1904, https://doi.org/10.5194/wes-9-1885-2024, https://doi.org/10.5194/wes-9-1885-2024, 2024
Short summary
Short summary
The selection of a suitable site for the installation of a wind turbine plays an important role in ensuring a safe operating lifetime of the structure. In this study, we show that mixture density networks can accelerate this process by inferring functions from data that can accurately map the environmental conditions to the loads but also propagate the uncertainty from the inflow to the response.
Yu Cao, Ningyu Wu, Jigang Yang, Chao Chen, Ronghua Zhu, and Xugang Hua
Wind Energ. Sci., 9, 1089–1104, https://doi.org/10.5194/wes-9-1089-2024, https://doi.org/10.5194/wes-9-1089-2024, 2024
Short summary
Short summary
This study investigates the offshore wind turbine support structure’s fatigue life by a rapid numerical model which considers the effects of scour and a tuned mass damper. An optimization technique is proposed to find the damper's optimal parameters, considering time-varying scour. It is found that the damper optimized by the proposed optimization technique performs better than an initially designed damper in terms of fatigue life enhancement.
Oliver Menck and Matthias Stammler
Wind Energ. Sci., 9, 777–798, https://doi.org/10.5194/wes-9-777-2024, https://doi.org/10.5194/wes-9-777-2024, 2024
Short summary
Short summary
Oscillating bearings, like rotating bearings, can fail due to rolling contact fatigue. But the publications in the literature on this topic are difficult to understand. In order to help people decide which method to use, we have summarized the available literature. We also point out some errors and things to look out for to help engineers that want to calculate the rolling contact fatigue life of an oscillating bearing.
Rad Haghi and Curran Crawford
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2023-157, https://doi.org/10.5194/wes-2023-157, 2023
Revised manuscript accepted for WES
Short summary
Short summary
The journal paper focuses on developing surrogate models for predicting the Damage Equivalent Load (DEL) on wind turbines without needing extensive aeroelastic simulations. The study emphasizes the development of a sequential machine-learning architecture for this purpose. The study also explores implementing simplified wake models and transfer learning to enhance the models' prediction capabilities in various wind conditions.
Negin Sadeghi, Pietro D'Antuono, Nymfa Noppe, Koen Robbelein, Wout Weijtjens, and Christof Devriendt
Wind Energ. Sci., 8, 1839–1852, https://doi.org/10.5194/wes-8-1839-2023, https://doi.org/10.5194/wes-8-1839-2023, 2023
Short summary
Short summary
Analysis of long-term fatigue damage of four offshore wind turbines using 3 years of measurement data was performed for the first time to gain insight into the low-frequency fatigue damage (LFFD) impact on overall consumed life. The LFFD factor depends on the (linear) stress–life (SN) curve slope, heading, site, signal, and turbine type. Up to ∼ 65 % of the total damage can be related to LFFDs. Therefore, in this case study, the LFFD effect has a significant impact on the final damage.
Clemens Hübler and Raimund Rolfes
Wind Energ. Sci., 7, 1919–1940, https://doi.org/10.5194/wes-7-1919-2022, https://doi.org/10.5194/wes-7-1919-2022, 2022
Short summary
Short summary
Offshore wind turbines are beginning to reach their design lifetimes. Hence, lifetime extensions are becoming relevant. To make well-founded decisions on possible lifetime extensions, fatigue damage predictions are required. Measurement-based assessments instead of simulation-based analyses have rarely been conducted so far, since data are limited. Therefore, this work focuses on the temporal extrapolation of measurement data. It is shown that fatigue damage can be extrapolated accurately.
Anand Natarajan
Wind Energ. Sci., 7, 1171–1181, https://doi.org/10.5194/wes-7-1171-2022, https://doi.org/10.5194/wes-7-1171-2022, 2022
Short summary
Short summary
The article delineates a novel procedure to use 10 min measurement statistics with few known parameters of the wind turbine to determine the long-term fatigue damage probability and compare this with the expected damage levels from the design to provide an indicator of structural reliability and remaining life. The results are validated with load measurements from a wind turbine within an offshore wind farm.
Cited articles
Clifton, A.: 135 m Meteorological Towers at the NWTC, Instrumentation, Data Acquisition and
Processing (Draft), https://wind.nrel.gov/MetData/Publications/ (last access: 5 August 2019), 2014. a
Diaz, S., Carta, J. A., and Castaneda, A.: Influence of the Variation of
Meteorological and Operational Parameters on Estimation of the Power Output
of a Wind Farm with Active Power Control, Renew. Energ., 159, 812–826,
https://doi.org/10.1016/j.renene.2020.05.187, 2020. a
Dimitrov, N., Natarajan, A., and Kelly, M.: Model of Wind Shear Conditional on Turbulence and Its Impact on Wind Turbine Loads, Wind Energy, 18, 1917–1931, 2015. a
Doubrawa, P., Annoni, J., Jonkman, J., and Ghate, A.: Optimization-Based
Calibration of FAST.Farm Parameters Against SOWFA, in: AIAA SciTech Forum,
36th Wind Energy Symposium, 8–12 January 2018, AIAA, Kissimmee, FL, USA,
https://doi.org/10.2514/6.2018-0512, 2018. a, b
Dykes, K., Ning, A., King, R., Graf, P., Scott, G., and Veers, P.: Sensitivity Analysis of Wind Plant
Performance to Key Turbine Design Parameters: A Systems Engineering Approach,
in: AIAA SciTech Forum, 13–17 January 2014, AIAA, National Harbor, Maryland, USA, 1–26 pp., https://doi.org/10.2514/6.2014-1087, 2014. a
Gan, Y., Duan, Q., Gong, W., Tong, C., Sun, Y., and Chu, W.: A Comprehensive
Evaluation of Various Sensitivity Analysis Methods: A Case Study with a
Hydrological Model, Environ. Modell. Softw., 51, 269–285, 2014. a
Jonkman, B.: TurbSim User's Guide v2.00.00, Tech. Rep. NREL/TP, October 2014, National Renewable Energy Laboratory, Golden, CO, USA, https://www.nrel.gov/wind/nwtc/assets/downloads/TurbSim/TurbSim_v2.00.pdf (last access: 2 January 2023), 2014. a
Jonkman, J., Butterfield, S., Musial, W., and Scott, G.: Definition of a 5 MW
Reference Wind Turbine for Offshore System Development, Tech. Rep.
NREL/TP-500-38060, February 2009, National Renewable Energy Laboratory, Golden, CO, USA, https://www.nrel.gov/docs/fy09osti/38060.pdf (last access: 2 January 2023), 2009. a, b
Kelley, N.: Turbulence-Turbine Interaction: The Bases for the Development of
the TurbSim Stochastic Simulator, Tech. Rep. NREL/TP-5000-52353, November 2011, National
Renewable Energy Laboratory, Golden, CO, USA, https://www.nrel.gov/docs/fy12osti/52353.pdf (last access: 2 January 2023), 2011. a
Moroz, E.: Time to Upgrade the Wind Turbine Suitability Process, 22–25 May 2017, AWEA WindPower, Anaheim, CA, USA, 2017. a
Nelson, L. D., Manuel, L., Sutherland, H. J., and Veers, P. S.: Statistical Analysis of Wind Turbine Inflow and Structural Response Data from the LIST Program, Journal of Solar Energy Engineering, 125, 541–550, https://doi.org/10.1115/1.1627831, 2003. a
OpenFAST: openfast documentation, GitHub, https://github.com/OpenFAST/openfast (last access: 1 May 2021), 2021. a
Quick, J., Annoni, J., King, R., Dykes, K., Fleming, P., and Ning, A.: Optimization Under Uncertainty for Wake Steering Strategies, J. Phys. Conf. Ser., 854, 1–10, https://doi.org/10.1088/1742-6596/854/1/012036, 2017. a, b
Rezaei, M., Mostafaeipour, A., Saidi-Mehrabad, M., Qolipour, M., Sedaghat, A., Arabnia, H. R., and Momeni, M.: Sensitivity
Analysis of Criteria to Optimize Wind Farm Localizing: A Case Study, Wind
Engineer., 44, 294–312, https://doi.org/10.1177/0309524X19849848, 2020.
a
Saranyasontoorn, K., Manuel, L., and Veers, P. S.: A Comparison of Standard
Coherence Models for Inflow Turbulenc with Estimates from Field Measurements,
J. Sol. Energ., 126, 1069–1082, 2004. a
Shaler, K., Jonkman, J., and Hamilton, N.: Effects of Inflow Spatiotemporal
Discretization on Wake Meandering and Turbine Structural Response Using
FAST.Farm, J. Phys.-Conf. Ser., 1256, 012023,
https://doi.org/10.1088/1742-6596/1256/1/012023, 2019. a
Solari, G.: Turbulence Modelling for Gust Loading, J. Struct. Eng., 113, 1550–1569, 1987. a
Solari, G. and Piccardo, G.: Probabilistic 3-D Turbulence Modeling for Gust
Buffeting of Structures, Probabilist. Eng. Mech., 16, 73–86,
2001. a
Tautz-Weinert, J., Yurusen, N. Y., Melero, J. J., and Watson, S. J.:
Sensitivity Study of a Wind Farm Maintenance Decision – A Performance and
Revenue Analysis, Renew. Energ., 132, 93–105,
https://doi.org/10.1016/j.renene.2018.07.110, 2019. a
Teunissen, H.: Characteristics of the Mean Wind and Turbulence in the Planetary Boundary Layer, Phd thesis, University of Toronto, Toronto, Canada, http://resolver.tudelft.nl/uuid:40e61f5a-17f5-4641-bb35-9d8dcff95eec (last access: 2 January 2023), 1970. a
Ulazia, A., Sa'enz, J., Ibarra-Berastegi, G., González-Rojí, S. J., and Carreno-Madinabeitia, S.: Global Estimations
of Wind Energy Potential Considering Seasonal Air Density changes, Energy,
187, 1–11, https://doi.org/10.1016/j.energy.2019.115938, 2019. a, b
Walter, K., Weiss, C., Swift, A., Chapman, J., and Kelley, N. D.: Speed and Direction Shear in the
Stable Nocturnal Boundary Layer, J. Sol. Energ. Engineering, 131,
1–7, https://doi.org/10.1115/1.3035818, 2019. a
Short summary
This work evaluates which wind-inflow- and wake-related parameters have the greatest influence on fatigue and ultimate loads for turbines in a small wind farm. Twenty-eight parameters were screened using an elementary effects approach to identify the parameters that lead to the largest variation in these loads of each turbine. The findings show the increased importance of non-streamwise wind components and wake parameters in fatigue and ultimate load sensitivity of downstream turbines.
This work evaluates which wind-inflow- and wake-related parameters have the greatest influence...
Altmetrics
Final-revised paper
Preprint