Articles | Volume 7, issue 3
https://doi.org/10.5194/wes-7-1209-2022
© Author(s) 2022. 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-7-1209-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Jun 2022
Research article |
| 08 Jun 2022
| 08 Jun 2022
Impacts of wind field characteristics and non-steady deterministic wind events on time-varying main-bearing loads
Wind Energy and Control Centre, Department of Electronic and Electrical Engineering, The University of Strathclyde, Glasgow, UK
Adam Stock
Wind Energy and Control Centre, Department of Electronic and Electrical Engineering, The University of Strathclyde, Glasgow, UK
George Elderfield
Wind Energy and Control Centre, Department of Electronic and Electrical Engineering, The University of Strathclyde, Glasgow, UK
Robin Elliott
Onyx Insight, Nottingham, United Kingdom
James Brasseur
Aerospace Mechanics Research Center, University of Colorado, Boulder, United States
Jonathan Keller
National Renewable Energy Laboratory, Golden, United States
National Renewable Energy Laboratory, Golden, United States
Wooyong Song
ORE Catapult, Inovo, Glasgow, United Kingdom
Related authors
Piotr Fojcik, Edward Hart, and Emil Hedevang
Wind Energ. Sci., 10, 1943–1962, https://doi.org/10.5194/wes-10-1943-2025, https://doi.org/10.5194/wes-10-1943-2025, 2025
Short summary
Short summary
Increasing the efficiency of wind farms can be achieved via reducing the impact of wakes – flow regions with lower wind speed occurring downwind from turbines. This work describes training and validation of a novel method for the estimation of the wake effects impacting a turbine. The results show that for most tested wind conditions, the developed model is capable of robust detection of wake presence and accurate characterisation of its properties. Further validation and improvements are planned.
Edward Hart
Wind Energ. Sci., 10, 1821–1827, https://doi.org/10.5194/wes-10-1821-2025, https://doi.org/10.5194/wes-10-1821-2025, 2025
Short summary
Short summary
A parametric model for the wind direction rose is presented, with testing on real offshore wind farm data indicating that the model performs well. The presented model provides opportunities for standardisation and enables more systematic analyses of wind direction distribution impacts and sensitivities.
Julian Quick, Edward Hart, Marcus Binder Nilsen, Rasmus Sode Lund, Jaime Liew, Piinshin Huang, Pierre-Elouan Rethore, Jonathan Keller, Wooyong Song, and Yi Guo
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-63, https://doi.org/10.5194/wes-2025-63, 2025
Revised manuscript under review for WES
Short summary
Short summary
Wind turbine main bearings often fail prematurely, creating costly maintenance challenges. This study examined how wake effects – where upstream turbines create disturbed airflow that impacts downstream turbines – affect bearing lifespans. Using computer simulations, we found that wake effects reduce bearing life by 16% on average. The direction of wake impact matters significantly due to interactions between wind forces and gravity, informing better wind turbine and farm farm design strategies.
Scott Dallas, Adam Stock, and Edward Hart
Wind Energ. Sci., 9, 841–867, https://doi.org/10.5194/wes-9-841-2024, https://doi.org/10.5194/wes-9-841-2024, 2024
Short summary
Short summary
This review presents the current understanding of wind direction variability in the context of control-oriented modelling of wind turbines and wind farms in a manner suitable to a wide audience. Motivation comes from the significant and commonly seen yaw error of horizontal axis wind turbines, which carries substantial negative impacts on annual energy production and the levellised cost of wind energy. Gaps in the literature are identified, and the critical challenges in this area are discussed.
Edward Hart, Elisha de Mello, and Rob Dwyer-Joyce
Wind Energ. Sci., 7, 1533–1550, https://doi.org/10.5194/wes-7-1533-2022, https://doi.org/10.5194/wes-7-1533-2022, 2022
Short summary
Short summary
This paper is the second in a two-part study on lubrication in wind turbine main bearings. Investigations are conducted concerning lubrication in the double-row spherical roller main bearing of a 1.5 MW wind turbine. This includes effects relating to temperature, starvation, grease-thickener interactions and possible non-steady EHL effects. Results predict that the modelled main bearing would be expected to operate under mixed lubrication conditions for a non-negligible proportion of its life.
Edward Hart, Elisha de Mello, and Rob Dwyer-Joyce
Wind Energ. Sci., 7, 1021–1042, https://doi.org/10.5194/wes-7-1021-2022, https://doi.org/10.5194/wes-7-1021-2022, 2022
Short summary
Short summary
This work provides an accessible introduction to elastohydrodynamic lubrication theory as a precursor to analysis of lubrication in a wind turbine main bearing. Fundamental concepts, derivations and formulas are presented, followed by the more advanced topics of starvation, non-steady effects, surface roughness interactions and grease lubrication.
Amir R. Nejad, Jonathan Keller, Yi Guo, Shawn Sheng, Henk Polinder, Simon Watson, Jianning Dong, Zian Qin, Amir Ebrahimi, Ralf Schelenz, Francisco Gutiérrez Guzmán, Daniel Cornel, Reza Golafshan, Georg Jacobs, Bart Blockmans, Jelle Bosmans, Bert Pluymers, James Carroll, Sofia Koukoura, Edward Hart, Alasdair McDonald, Anand Natarajan, Jone Torsvik, Farid K. Moghadam, Pieter-Jan Daems, Timothy Verstraeten, Cédric Peeters, and Jan Helsen
Wind Energ. Sci., 7, 387–411, https://doi.org/10.5194/wes-7-387-2022, https://doi.org/10.5194/wes-7-387-2022, 2022
Short summary
Short summary
This paper presents the state-of-the-art technologies and development trends of wind turbine drivetrains – the energy conversion systems transferring the kinetic energy of the wind to electrical energy – in different stages of their life cycle: design, manufacturing, installation, operation, lifetime extension, decommissioning and recycling. The main aim of this article is to review the drivetrain technology development as well as to identify future challenges and research gaps.
James Stirling, Edward Hart, and Abbas Kazemi Amiri
Wind Energ. Sci., 6, 15–31, https://doi.org/10.5194/wes-6-15-2021, https://doi.org/10.5194/wes-6-15-2021, 2021
Short summary
Short summary
This paper considers the modelling of wind turbine main bearings using analytical models. The validity of simplified analytical representations is explored by comparing main-bearing force reactions with those obtained from higher-fidelity 3D finite-element models. Results indicate that good agreement can be achieved between the analytical and 3D models in the case of both non-moment-reacting (such as for a spherical roller bearing) and moment-reacting (such as a tapered roller bearing) set-ups.
Pietro Bortolotti, Lee Jay Fingersh, Nicholas Hamilton, Arlinda Huskey, Chris Ivanov, Mark Iverson, Jonathan Keller, Scott Lambert, Jason Roadman, Derek Slaughter, Syhoune Thao, and Consuelo Wells
Wind Energ. Sci., 10, 2025–2050, https://doi.org/10.5194/wes-10-2025-2025, https://doi.org/10.5194/wes-10-2025-2025, 2025
Short summary
Short summary
This study compares a wind turbine with blades behind the tower (downwind) to the traditional upwind design. Testing a 1.5 MW turbine at the National Renewable Energy Laboratory's Flatirons Campus, we measured performance, loads, and noise. Numerical models matched well with observations. The downwind setup showed higher fatigue loads and sound variations but also an unexpected power improvement. Downwind rotors might be a valid alternative for future floating offshore wind applications.
Piotr Fojcik, Edward Hart, and Emil Hedevang
Wind Energ. Sci., 10, 1943–1962, https://doi.org/10.5194/wes-10-1943-2025, https://doi.org/10.5194/wes-10-1943-2025, 2025
Short summary
Short summary
Increasing the efficiency of wind farms can be achieved via reducing the impact of wakes – flow regions with lower wind speed occurring downwind from turbines. This work describes training and validation of a novel method for the estimation of the wake effects impacting a turbine. The results show that for most tested wind conditions, the developed model is capable of robust detection of wake presence and accurate characterisation of its properties. Further validation and improvements are planned.
Mario De Florio, Gabriel Appleby, Jonathan Keller, Ali Eftekhari Milani, Donatella Zappalá, and Shawn Sheng
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-157, https://doi.org/10.5194/wes-2025-157, 2025
Preprint under review for WES
Short summary
Short summary
We developed a new method to predict when wind turbine parts are likely to fail, allowing maintenance to be planned before costly breakdowns occur. By combining real measurements from turbines with knowledge of how cracks grow in metal, our approach gives more reliable forecasts even when only limited data are available. We also measure how confident the predictions are, helping operators make better decisions. This can reduce downtime and lower the cost of wind energy.
Edward Hart
Wind Energ. Sci., 10, 1821–1827, https://doi.org/10.5194/wes-10-1821-2025, https://doi.org/10.5194/wes-10-1821-2025, 2025
Short summary
Short summary
A parametric model for the wind direction rose is presented, with testing on real offshore wind farm data indicating that the model performs well. The presented model provides opportunities for standardisation and enables more systematic analyses of wind direction distribution impacts and sensitivities.
Julian Quick, Edward Hart, Marcus Binder Nilsen, Rasmus Sode Lund, Jaime Liew, Piinshin Huang, Pierre-Elouan Rethore, Jonathan Keller, Wooyong Song, and Yi Guo
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-63, https://doi.org/10.5194/wes-2025-63, 2025
Revised manuscript under review for WES
Short summary
Short summary
Wind turbine main bearings often fail prematurely, creating costly maintenance challenges. This study examined how wake effects – where upstream turbines create disturbed airflow that impacts downstream turbines – affect bearing lifespans. Using computer simulations, we found that wake effects reduce bearing life by 16% on average. The direction of wake impact matters significantly due to interactions between wind forces and gravity, informing better wind turbine and farm farm design strategies.
Scott Dallas, Adam Stock, and Edward Hart
Wind Energ. Sci., 9, 841–867, https://doi.org/10.5194/wes-9-841-2024, https://doi.org/10.5194/wes-9-841-2024, 2024
Short summary
Short summary
This review presents the current understanding of wind direction variability in the context of control-oriented modelling of wind turbines and wind farms in a manner suitable to a wide audience. Motivation comes from the significant and commonly seen yaw error of horizontal axis wind turbines, which carries substantial negative impacts on annual energy production and the levellised cost of wind energy. Gaps in the literature are identified, and the critical challenges in this area are discussed.
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.
Tuhfe Göçmen, Filippo Campagnolo, Thomas Duc, Irene Eguinoa, Søren Juhl Andersen, Vlaho Petrović, Lejla Imširović, Robert Braunbehrens, Jaime Liew, Mads Baungaard, Maarten Paul van der Laan, Guowei Qian, Maria Aparicio-Sanchez, Rubén González-Lope, Vinit V. Dighe, Marcus Becker, Maarten J. van den Broek, Jan-Willem van Wingerden, Adam Stock, Matthew Cole, Renzo Ruisi, Ervin Bossanyi, Niklas Requate, Simon Strnad, Jonas Schmidt, Lukas Vollmer, Ishaan Sood, and Johan Meyers
Wind Energ. Sci., 7, 1791–1825, https://doi.org/10.5194/wes-7-1791-2022, https://doi.org/10.5194/wes-7-1791-2022, 2022
Short summary
Short summary
The FarmConners benchmark is the first of its kind to bring a wide variety of data sets, control settings, and model complexities for the (initial) assessment of wind farm flow control benefits. Here we present the first part of the benchmark results for three blind tests with large-scale rotors and 11 participating models in total, via direct power comparisons at the turbines as well as the observed or estimated power gain at the wind farm level under wake steering control strategy.
Edward Hart, Elisha de Mello, and Rob Dwyer-Joyce
Wind Energ. Sci., 7, 1533–1550, https://doi.org/10.5194/wes-7-1533-2022, https://doi.org/10.5194/wes-7-1533-2022, 2022
Short summary
Short summary
This paper is the second in a two-part study on lubrication in wind turbine main bearings. Investigations are conducted concerning lubrication in the double-row spherical roller main bearing of a 1.5 MW wind turbine. This includes effects relating to temperature, starvation, grease-thickener interactions and possible non-steady EHL effects. Results predict that the modelled main bearing would be expected to operate under mixed lubrication conditions for a non-negligible proportion of its life.
Edward Hart, Elisha de Mello, and Rob Dwyer-Joyce
Wind Energ. Sci., 7, 1021–1042, https://doi.org/10.5194/wes-7-1021-2022, https://doi.org/10.5194/wes-7-1021-2022, 2022
Short summary
Short summary
This work provides an accessible introduction to elastohydrodynamic lubrication theory as a precursor to analysis of lubrication in a wind turbine main bearing. Fundamental concepts, derivations and formulas are presented, followed by the more advanced topics of starvation, non-steady effects, surface roughness interactions and grease lubrication.
Amir R. Nejad, Jonathan Keller, Yi Guo, Shawn Sheng, Henk Polinder, Simon Watson, Jianning Dong, Zian Qin, Amir Ebrahimi, Ralf Schelenz, Francisco Gutiérrez Guzmán, Daniel Cornel, Reza Golafshan, Georg Jacobs, Bart Blockmans, Jelle Bosmans, Bert Pluymers, James Carroll, Sofia Koukoura, Edward Hart, Alasdair McDonald, Anand Natarajan, Jone Torsvik, Farid K. Moghadam, Pieter-Jan Daems, Timothy Verstraeten, Cédric Peeters, and Jan Helsen
Wind Energ. Sci., 7, 387–411, https://doi.org/10.5194/wes-7-387-2022, https://doi.org/10.5194/wes-7-387-2022, 2022
Short summary
Short summary
This paper presents the state-of-the-art technologies and development trends of wind turbine drivetrains – the energy conversion systems transferring the kinetic energy of the wind to electrical energy – in different stages of their life cycle: design, manufacturing, installation, operation, lifetime extension, decommissioning and recycling. The main aim of this article is to review the drivetrain technology development as well as to identify future challenges and research gaps.
James Stirling, Edward Hart, and Abbas Kazemi Amiri
Wind Energ. Sci., 6, 15–31, https://doi.org/10.5194/wes-6-15-2021, https://doi.org/10.5194/wes-6-15-2021, 2021
Short summary
Short summary
This paper considers the modelling of wind turbine main bearings using analytical models. The validity of simplified analytical representations is explored by comparing main-bearing force reactions with those obtained from higher-fidelity 3D finite-element models. Results indicate that good agreement can be achieved between the analytical and 3D models in the case of both non-moment-reacting (such as for a spherical roller bearing) and moment-reacting (such as a tapered roller bearing) set-ups.
Cited articles
Barter, G. E., Robertson, A., and Musial, W.: A systems engineering vision for
floating offshore wind cost optimization, Renewable Energy Focus, 34, 1–16,
https://doi.org/10.1016/j.ref.2020.03.002, 2020. a
Bergua, R., Keller, J., Bankestrom, O., Dunn, M., Guo, Y., Key, A., and Young,
E.: Up-tower investigation of main bearing cage slip and loads,
https://www.nrel.gov/docs/fy22osti/81240.pdf (last access: 11 March 2022), 2021. a
Bossanyi, E. A.: Individual blade pitch control for load reduction, Wind
Energy, 6, 119–128, 2003. a
Burton, T., Jenkins, N., Sharpe, D., and Bossanyi, E.: Wind Energy Handbook, 2nd Edition, John Wiley & Sons ltd, Chichester, ISBN 978-0-470-69975-1, 2001. a
Cardaun, M., Roscher, B., Schelenz, R., and Jacobs, G.: Analysis of
Wind-Turbine Main Bearing Loads Due to Constant Yaw Misalignments over a 20
Years Timespan, Energies, 12, 1768, https://doi.org/10.3390/en12091768, 2019. a, b
Chatzopoulos, A.-P.: Full envelope wind turbine controller design for power
regulation and tower load reduction, PhD thesis, University of Strathclyde,
https://doi.org/10.48730/xcmh-3713, 2011. a
Fleming, P., Annoni, J., Shah, J. J., Wang, L., Ananthan, S., Zhang, Z., Hutchings, K., Wang, P., Chen, W., and Chen, L.: Field test of wake steering at an offshore wind farm, Wind Energ. Sci., 2, 229–239, https://doi.org/10.5194/wes-2-229-2017, 2017. a
Gaertner, E., Rinker, J., Sethuraman, L., Zahle, F., Anderson, B., Barter, G.,
Abbas, N., Meng, F., Bortolotti, P., Skrzypinski, W., Scott, G., Feil, R.,
Bredmose, H., Dykes, K., Shields, M., Allen, C., and Viselli, A.: Definition
of the IEA 15-megawatt offshore reference wind turbine,
https://www.nrel.gov/docs/fy20osti/75698.pdf (last access: 1 June 2022), 2020. a
GE: Haliade 150-6MW offshore wind turbine,
https://www.ge.com/renewableenergy/wind-energy/offshore-wind/offshore-turbine-haliade-150-6mw (last access: 13 May 2022),
2021. a
Gould, B. and Burris, D.: Effects of wind shear on wind turbine rotor loads and
planetary bearing reliability, Wind Energy, 19, 1011–1021, 2016. a
Guo, Y., van Dam, J., Bergua, R., Jové, J., and Campbell, J.: Improving Wind
Turbine Drivetrain Reliability Using a Combined Experimental, Computational,
and Analytical Approach, in: ASME 2014 International Design Engineering
Technical Conferences & Computers and Information in Engineering Conference
(IDETC/CIE 2014), NREL/CP-5000-61683,
https://www.nrel.gov/docs/fy15osti/61683.pdf (last access: 1 June 2022), 2014. a, b
Guo, Y., Parsons, T., Dykes, K., and King, R. N.: A systems engineering
analysis of three-point and four-point wind turbine drivetrain
configurations, Wind Energy, 20, 537–550, 2017. a
Guo, Y., Bankestrom, O., Bergua, R., Keller, J., and Dunn, M.: Investigation of
main bearing operating conditions in a three-point mount wind turbine
drivetrain, Forschung im Ingenieurwesen, 1–11, https://doi.org/10.1007/s10010-021-00477-8, 2021. a, b
Hart, E., Turnbull, A., Feuchtwang, J., McMillan, D., Golysheva, E., and
Elliott, R.: Wind turbine main-bearing loading and wind field
characteristics, Wiley Wind Energy, 22, 1534–1547, https://doi.org/10.1002/we.2386,
2019. a, b, c
Hart, E., Clarke, B., Nicholas, G., Kazemi Amiri, A., Stirling, J., Carroll, J., Dwyer-Joyce, R., McDonald, A., and Long, H.: A review of wind turbine main bearings: design, operation, modelling, damage mechanisms and fault detection, Wind Energ. Sci., 5, 105–124, https://doi.org/10.5194/wes-5-105-2020, 2020. a, b, c, d, e
Jamieson, P. and Hassan, G.: Innovation in wind turbine design, vol. 2, Wiley
Online Library, 2011. a
Jenkins, N., Burton, T. L., Bossanyi, E., Sharpe, D., and Graham, M. (Eds.): Wind
Energy Handbook, John Wiley & Sons, ISBN 9781119451099, 2021. a
Jonkman, J., Butterfield, S., Musial, W., and Scott, G.: Definition of a 5-MW
reference wind turbine for offshore system development, Tech. rep., National
Renewable Energy Laboratory (NREL), Golden, CO (United States),
https://www.nrel.gov/docs/fy09osti/38060.pdf (last access: 21 April 2022), 2009. a, b
Keller, J., Sheng, S., Cotrell, J., and Greco, A.: Wind turbine drivetrain
reliability collaborative workshop: a recap, Tech. rep., U.S. Department of
Energy, https://www.nrel.gov/docs/fy16osti/66593.pdf (last access: 10 April 2022), 2016. a
Kelley, N. D. and Jonkman, B. J.: Overview of the TurbSim stochastic inflow
turbulence simulator, Tech. rep., National Renewable Energy Laboratory
(NREL), Golden, CO (United States), https://www.nrel.gov/docs/fy05osti/36971.pdf
(last access: 1 June 2022), 2005. a
Kock, S., Jacobs, G., and Bosse, D.: Determination of Wind Turbine Main Bearing
Load Distribution, IOP Conf. Ser.-J. Phys., 1222, 012030,
https://doi.org/10.1088/1742-6596/1222/1/012030, 2019. a
Lavely, A. W.: Effects of daytime atmospheric boundary layer turbulence on the
generation of nonsteady wind turbine loadings and predictive accuracy of
lower order models, The Pennsylvania State University, https://etda.libraries.psu.edu/catalog/13830awl5173
(last access: 1 June 2022), 2017. a, b, c
Leithead, W. and Stock, A.: UK wind energy technologies – Wind Turbine
Control, in: UK Wind Energy Technologies, edited by: Hogg, S. and Crabtree,
C., chap. 6, Routledge, 1 edn., 219–258, https://doi.org/10.4324/9781315681382,
2016. a, b
Leithead, W. E. and Dominguez, S.: Coordinated control design for wind turbine
control systems, in: Proceedings of European Wind Energy Conference and
Exhibition, Athens, Greece, 27 February 2006–2 March 2006, vol. 27, https://www.researchgate.net/publication/267683408_Coordinated_Control_Design_for_Wind_Turbine_Control_Systems
(last access: 1 June 2022), 2006. a
Mann, J.: Wind field simulation, Probabilist. Eng. Mech., 13,
269–282, https://doi.org/10.1016/S0266-8920(97)00036-2, 1998. a
Murphy, P., Lundquist, J. K., and Fleming, P.: How wind speed shear and directional veer affect the power production of a megawatt-scale operational wind turbine, Wind Energ. Sci., 5, 1169–1190, https://doi.org/10.5194/wes-5-1169-2020, 2020. a
Nandi, T., Herrig, A., and Brasseur, J.: Non-steady wind turbine response to
daytime atmospheric turbulence, Philos. T. Roy.
Soc. A, 375, 20160103, https://doi.org/10.1098/rsta.2016.0103,
2017. a, b
Nejad, A. R. and Torsvik, J.: Drivetrains on floating offshore wind turbines: lessons learned over the last 10 years, Forsch. Ingenieurw., 85, 335–343, https://doi.org/10.1007/s10010-021-00469-8, 2021. a
Nejad, A. R., Keller, J., Guo, Y., Sheng, S., Polinder, H., Watson, S., Dong, J., Qin, Z., Ebrahimi, A., Schelenz, R., Gutiérrez Guzmán, F., Cornel, D., Golafshan, R., Jacobs, G., Blockmans, B., Bosmans, J., Pluymers, B., Carroll, J., Koukoura, S., Hart, E., McDonald, A., Natarajan, A., Torsvik, J., Moghadam, F. K., Daems, P.-J., Verstraeten, T., Peeters, C., and Helsen, J.: Wind turbine drivetrains: state-of-the-art technologies and future development trends, Wind Energ. Sci., 7, 387–411, https://doi.org/10.5194/wes-7-387-2022, 2022. a, b, c
Pedersen, J., Juncker, K., and Randewijk, P. J.: Lifetime Estimation of
Semiconducting Components in 8MW Wind Turbine Generators with “Power
Boost” Functionality, in: 2020 55th International Universities Power
Engineering Conference (UPEC), 1–6, IEEE, https://doi.org/10.1109/UPEC49904.2020.9209801, 2020. a
Sethuraman, L., Guo, Y., and Sheng, S.: Main bearing dynamics in three point
suspension drivetrains for wind turbines, American Wind Energy Association
WindPower Conference and Exhibition, https://www.nrel.gov/docs/fy15osti/64311.pdf
(last access: 1 June 2022), 2015.
a
Stirling, J., Hart, E., and Kazemi Amiri, A.: Constructing fast and representative analytical models of wind turbine main bearings, Wind Energ. Sci., 6, 15–31, https://doi.org/10.5194/wes-6-15-2021, 2021. a, b, c, d
Thompson, D. W.: Mitigating size related limitations in wind turbine control,
PhD thesis, University of Strathclyde, https://doi.org/10.48730/ej6k-8507, 2018. a, b
Torsvik, J., Nejad, A. R., and Pedersen, E.: Main bearings in large offshore
wind turbines: development trends, design and analysis requirements, J. Phys.-Conf. Ser., 1037, 042020, https://doi.org/10.1088/1742-6596/1037/4/042020,
2018. a
van Dam, J.: Advanced Wind Turbine Drivetrain Topology for Improving System
Reliability, NREL/TP-5000-77552, Tech. rep., National Renewable Energy
Laboratory (NREL),
https://www.nrel.gov/docs/fy20osti/77552.pdf (last access: 1 June 2022), 2020. a
Vijayakumar, G. and Brasseur, J.: Blade-resolved modeling with
fluid–structure interaction, chap. 2, edited by: Veers, P. S., Wind Energy
Modeling and Simulation, Volume 1: Atmosphere and Plant, Tech. rep., National
Renewable Energy Laboratory (NREL), Golden, CO (United States), https://doi.org/10.1049/PBPO125F_ch2, 2019. a
Wang, S., Nejad, A. R., Bachynski, E. E., and Moan, T.: Effects of bedplate
flexibility on drivetrain dynamics: Case study of a 10 MW spar type floating
wind turbine, Renew. Energ., 161, 808–824,
https://doi.org/10.1016/j.renene.2020.07.148, 2020. a
Zhang, H., Shi, W., Liu, G., and Chen, Z.: A Method to Solve the Stiffness of
Double-Row Tapered Roller Bearing, Math. Probl. Eng., 2019, 1857931, https://doi.org/10.1155/2019/1857931,
2019. a, b
Zheng, J., Ji, J., Yin, S., and Tong, V. C.: The load distribution of the main
shaft bearing considering combined load and misalignment in a floating
direct-drive wind turbine, in: E3S web of conferences, vol. 64, 07009, EDP
Sciences, https://doi.org/10.1051/e3sconf/20186407009, 2018. a
Zheng, J., Ji, J., Yin, S., and Tong, V.-C.: Fatigue life analysis of
double-row tapered roller bearing in a modern wind turbine under oscillating
external load and speed, P. I. Mech.
Eng. C-J. Mech., 234,
3116–3130, 2020a. a
Zheng, J., Ji, J., Yin, S., and Tong, V.-C.: Internal loads and contact
pressure distributions on the main shaft bearing in a modern gearless wind
turbine, Tribol. Int., 141, 105960, https://doi.org/10.1016/j.triboint.2019.105960, 2020b. a
Short summary
We consider characteristics and drivers of loads experienced by wind turbine main bearings using simplified models of hub and main-bearing configurations. Influences of deterministic wind characteristics are investigated for 5, 7.5, and 10 MW turbine models. Load response to gusts and wind direction changes are also considered. Cubic load scaling is observed, veer is identified as an important driver of load fluctuations, and strong links between control and main-bearing load response are shown.
We consider characteristics and drivers of loads experienced by wind turbine main bearings using...
Altmetrics
Final-revised paper
Preprint