IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i8p2092-d1637422.html
   My bibliography  Save this article

TLP-Supported NREL 5MW Floating Offshore Wind Turbine Tower Vibration Reduction Under Aligned and Misaligned Wind-Wave Excitations

Author

Listed:
  • Paweł Martynowicz

    (Department of Process Control, AGH University of Krakow, Mickiewicza 30 Ave., 30-059 Kraków, Poland)

  • Piotr Ślimak

    (Department of Process Control, AGH University of Krakow, Mickiewicza 30 Ave., 30-059 Kraków, Poland)

  • Georgios M. Katsaounis

    (School of Naval Architecture and Marine Engineering, National Technical University of Athens, 9, Iroon Polytechniou Str., 15772 Zografou, Greece)

Abstract

This paper presents a numerical study on the structural vibrations of a TLP-supported NREL 5MW wind turbine equipped with a tuned vibration absorber (TVA) in the nacelle. The analysis was focused on tower bending deflections and was conducted using a reference OpenFAST V3.5.3 dedicated wind turbine modelling software and a finite element simulation framework based on Comsol Multiphysics V6.3 which was newly developed for this study. The obtained four-degree-of-freedom (4-DOF) tower bending model was transferred using modal decomposition to the MATLAB/Simulink R2020b environment, where a 2-DOF TLP surge/sway model and a bidirectional (2-DOF) TVA model were embedded. The wind field was approximated by a Weibull distribution of velocities (8.86 m/s mean, 4.63 m/s standard deviation). It was combined with the wave actions simulated using a Bretschneider spectrum with a significant height of 2.5 m and a peak period of 8.1 s. The TVA model used was either the standard NREL reference 20-ton passive TVA, a 10-ton passive, or a 10-ton controlled TVA (the latter two tuned to the tower’s first bending mode). The controlled TVA utilised a magnetorheological (MR) damper, either operating independently (forming a semi-active MR-TVA) or simultaneously with a force actuator, forming, in this case, a hybrid H-MR-TVA. Both aligned and 45°/90° misaligned wind–wave excitations were examined to investigate the performance of a 10-ton real-time controlled (H-)MR-TVA operating with less working space. In aligned conditions, the semi-active and hybrid MR-TVA solutions demonstrated superior tower vibration mitigation, reducing maximum tower deflections by 11.2% compared to the reference TVA and by 14.9% with regard to the structure without TVA. The reduction in root-mean-square deflection reached up to 4.2%/2.9%, respectively, for the critical along-the-waves direction, while the TVA stroke reduction reached 18.6%. For misaligned excitations, the tower deflection was reduced by 4.3%/4.8% concerning the reference 20-ton TVA, while the stroke was reduced by 22.2%/34.4% (for 45°/90° misalignment, respectively). It is concluded that the implementation of the 10-ton real-time controlled (H-)MR-TVA is a promising alternative to the reference 20-ton passive TVA regarding tower deflection minimisation and TVA stroke reduction for the critical along-the-waves direction. The current research results may be used to design a full-scale semi-active or hybrid TVA system serving a TLP-supported floating offshore wind turbine structure.

Suggested Citation

  • Paweł Martynowicz & Piotr Ślimak & Georgios M. Katsaounis, 2025. "TLP-Supported NREL 5MW Floating Offshore Wind Turbine Tower Vibration Reduction Under Aligned and Misaligned Wind-Wave Excitations," Energies, MDPI, vol. 18(8), pages 1-32, April.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:8:p:2092-:d:1637422
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/8/2092/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/8/2092/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sajid Ali & Hongbae Park & Adnan Aslam Noon & Aamer Sharif & Daeyong Lee, 2024. "Accuracy Testing of Different Methods for Estimating Weibull Parameters of Wind Energy at Various Heights above Sea Level," Energies, MDPI, vol. 17(9), pages 1-19, May.
    2. Antonio Galán-Lavado & Matilde Santos, 2021. "Analysis of the Effects of the Location of Passive Control Devices on the Platform of a Floating Wind Turbine," Energies, MDPI, vol. 14(10), pages 1-19, May.
    3. Fitzgerald, Breiffni & McAuliffe, James & Baisthakur, Shubham & Sarkar, Saptarshi, 2023. "Enhancing the reliability of floating offshore wind turbine towers subjected to misaligned wind-wave loading using tuned mass damper inerters (TMDIs)," Renewable Energy, Elsevier, vol. 211(C), pages 522-538.
    4. Paweł Martynowicz & Georgios M. Katsaounis & Spyridon A. Mavrakos, 2024. "Comparison of Floating Offshore Wind Turbine Tower Deflection Mitigation Methods Using Nonlinear Optimal-Based Reduced-Stroke Tuned Vibration Absorber," Energies, MDPI, vol. 17(6), pages 1-30, March.
    5. Paweł Martynowicz, 2021. "Nonlinear Optimal-Based Vibration Control of a Wind Turbine Tower Using Hybrid vs. Magnetorheological Tuned Vibration Absorber," Energies, MDPI, vol. 14(16), pages 1-22, August.
    6. Madsen, F.J. & Nielsen, T.R.L. & Kim, T. & Bredmose, H. & Pegalajar-Jurado, A. & Mikkelsen, R.F. & Lomholt, A.K. & Borg, M. & Mirzaei, M. & Shin, P., 2020. "Experimental analysis of the scaled DTU10MW TLP floating wind turbine with different control strategies," Renewable Energy, Elsevier, vol. 155(C), pages 330-346.
    7. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2018. "Forecasting the Long-Term Wind Data via Measure-Correlate-Predict (MCP) Methods," Energies, MDPI, vol. 11(6), pages 1-17, June.
    8. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2017. "Techno-Economic Assessment of Wind Energy Potential at Three Locations in South Korea Using Long-Term Measured Wind Data," Energies, MDPI, vol. 10(9), pages 1-24, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zbysław Dobrowolski & Peter Adamišin & Arkadiusz Babczuk & Sławomir Kotylak, 2025. "Towards a Green Transformation: Legal Barriers to Onshore Wind Farm Construction," Energies, MDPI, vol. 18(5), pages 1-17, March.
    2. Matilde Santos, 2022. "Special Issue on Dynamics and Control of Offshore and Onshore Wind Turbine Structures," Energies, MDPI, vol. 15(8), pages 1-3, April.
    3. Truong, Hoai Vu Anh & Dang, Tri Dung & Vo, Cong Phat & Ahn, Kyoung Kwan, 2022. "Active control strategies for system enhancement and load mitigation of floating offshore wind turbines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    4. Dongbum Kang & Kyungnam Ko & Jongchul Huh, 2018. "Comparative Study of Different Methods for Estimating Weibull Parameters: A Case Study on Jeju Island, South Korea," Energies, MDPI, vol. 11(2), pages 1-19, February.
    5. Mohammed H. Alsharif & Jeong Kim & Jin Hong Kim, 2018. "Opportunities and Challenges of Solar and Wind Energy in South Korea: A Review," Sustainability, MDPI, vol. 10(6), pages 1-23, June.
    6. Yang, Lin & Liao, Kangping & Ma, Qingwei & Ma, Gang & Sun, Hanbing, 2023. "Investigation of wake characteristics of floating offshore wind turbine with control strategy using actuator curve embedding method," Renewable Energy, Elsevier, vol. 218(C).
    7. Wakui, Tetsuya & Nagamura, Atsushi & Yokoyama, Ryohei, 2021. "Stabilization of power output and platform motion of a floating offshore wind turbine-generator system using model predictive control based on previewed disturbances," Renewable Energy, Elsevier, vol. 173(C), pages 105-127.
    8. Ahmed WA Hammad & Ali Akbarnezhad & Assed Haddad & Elaine Garrido Vazquez, 2019. "Sustainable Zoning, Land-Use Allocation and Facility Location Optimisation in Smart Cities," Energies, MDPI, vol. 12(7), pages 1-23, April.
    9. Kim, T. & Madsen, F.J. & Bredmose, H. & Pegalajar-Jurado, A., 2023. "Numerical analysis and comparison study of the 1:60 scaled DTU 10 MW TLP floating wind turbine," Renewable Energy, Elsevier, vol. 202(C), pages 210-221.
    10. Sajid Ali & Choon-Man Jang, 2020. "Optimum Design of Hybrid Renewable Energy System for Sustainable Energy Supply to a Remote Island," Sustainability, MDPI, vol. 12(3), pages 1-16, February.
    11. Woochul Nam & Ki-Yong Oh, 2020. "Mutually Complementary Measure-Correlate-Predict Method for Enhanced Long-Term Wind-Resource Assessment," Mathematics, MDPI, vol. 8(10), pages 1-20, October.
    12. Yang, Lei & Li, Binbin & Dong, Yehong & Hu, Zhenzhong & Zhang, Kai & Li, Sunwei, 2025. "Large-amplitude rotation of floating offshore wind turbines: A comprehensive review of causes, consequences, and solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 211(C).
    13. Li, Xia & Xu, Li & Cai, Jingjing & Peng, Cheng & Bian, Xiaoyan, 2024. "Offshore wind turbine selection with multi-criteria decision-making techniques involving D numbers and squeeze adversarial interpretive structural modeling method," Applied Energy, Elsevier, vol. 368(C).
    14. Dali, Ali & Abdelmalek, Samir & Bakdi, Azzeddine & Bettayeb, Maamar, 2021. "A new robust control scheme: Application for MPP tracking of a PMSG-based variable-speed wind turbine," Renewable Energy, Elsevier, vol. 172(C), pages 1021-1034.
    15. Baisthakur, Shubham & Fitzgerald, Breiffni, 2024. "Physics-Informed Neural Network surrogate model for bypassing Blade Element Momentum theory in wind turbine aerodynamic load estimation," Renewable Energy, Elsevier, vol. 224(C).
    16. Kim, Young Jun & Charlou, Moran & Bouscasse, Benjamin & Leroy, Vincent & Aliyar, Sithik & Bonnefoy, Félicien & Kim, Kyong-Hwan & Choi, Young-Myung, 2025. "High fidelity simulations of a floating offshore wind turbine in irregular waves by coupling OpenFOAM and OpenFAST," Renewable Energy, Elsevier, vol. 243(C).
    17. Mekalathur B Hemanth Kumar & Saravanan Balasubramaniyan & Sanjeevikumar Padmanaban & Jens Bo Holm-Nielsen, 2019. "Wind Energy Potential Assessment by Weibull Parameter Estimation Using Multiverse Optimization Method: A Case Study of Tirumala Region in India," Energies, MDPI, vol. 12(11), pages 1-21, June.
    18. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2018. "Forecasting the Long-Term Wind Data via Measure-Correlate-Predict (MCP) Methods," Energies, MDPI, vol. 11(6), pages 1-17, June.
    19. Paweł Martynowicz, 2022. "Experimental Study on the Optimal-Based Vibration Control of a Wind Turbine Tower Using a Small-Scale Electric Drive with MR Damper Support," Energies, MDPI, vol. 15(24), pages 1-25, December.
    20. Alessandro Fontanella & Giulia Da Pra & Marco Belloli, 2023. "Integrated Design and Experimental Validation of a Fixed-Pitch Rotor for Wind Tunnel Testing," Energies, MDPI, vol. 16(5), pages 1-15, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:18:y:2025:i:8:p:2092-:d:1637422. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.