Enter your email address
Submit
Write your message
1- MSc Student, Faculty of Civil Engineering, Babol Noshirvani University of Technology, Babol, Iran.
2- Associate Professor, Faculty of Civil Engineering, Babol Noshirvani University of Technology, Babol, Iran.
2- Associate Professor, Faculty of Civil Engineering, Babol Noshirvani University of Technology, Babol, Iran.
Abstract: (193 Views)
| This research aims to develop a comprehensive analytical framework for evaluating the dynamic resistance and performance optimization of offshore wind turbines using smart control systems under varying environmental conditions. It presents a comparative analysis of passive, semi-active, and smart control methods for structural life extension and dynamic response improvement. An advanced numerical model of a 5 MW offshore wind turbine installed on a jacket structure in the North Sea was developed and analyzed under 29 different marine conditions. The methodology integrates multi-scale modeling techniques, advanced dynamic simulation, and multi-objective optimization algorithms. The proposed smart control system achieved a 58% reduction in dynamic tower acceleration, a 45% improvement in displacement control, and a 3.2-fold increase in the fatigue life of critical connections compared to conventional methods. Furthermore, economic analyses indicate the system's economic viability with a payback period of 4.2 years. The results demonstrate that smart control systems can significantly enhance the reliability and economic efficiency of offshore wind energy projects. The practical applications of this research can guide the design of next-generation offshore wind turbines with improved dynamic performance and longer operational life. |
Type of Study: Research Paper |
Subject:
Offshore Structure
Received: 2025/11/7 | Accepted: 2026/02/2
Received: 2025/11/7 | Accepted: 2026/02/2
فایل صوتی چکیده مقاله [MP3 2611 KB] (6 Download)
References
1. Council, G. W. E. (2023). Boston Consulting Group. 2023. Mission Critical: Building the global wind energy supply chain for a, 1.
2. Liu, Y., Han, S., & Yan, J. (2025). Offshore Wind Farm Technology. Springer Nature. [DOI:10.1007/978-981-96-1889-7] [PMID]
3. Yamaguchi, A., & Ishihara, T. (2015). Floating offshore wind measurement system by using LIDAR and its verification. Proceedings of the Europe's Premier Wind Energy Event.
4. Schwarz, M., Glienke, R., Wegener, F., & Seidel, M. (2023, June). Fatigue Assessment of Eccentrically Loaded Flange Connections in Wind Energy Turbines. In ISOPE International Ocean and Polar Engineering Conference (pp. ISOPE-I). ISOPE.
5. Schafhirt, S., Page, A., Eiksund, G. R., & Muskulus, M. (2016). Influence of soil parameters on the fatigue lifetime of offshore wind turbines with monopile support structure. Energy Procedia, 94, 347-356. [DOI:10.1016/j.egypro.2016.09.194]
6. van der Tempel, J., & Molenaar, D. P. (2002). Wind turbine structural dynamics-a review of the principles for modern power generation, onshore and offshore. Wind engineering, 26(4), 211-222. [DOI:10.1260/030952402321039412]
7. Colwell, S., & Basu, B. (2009). Tuned liquid column dampers in offshore wind turbines for structural control. Engineering structures, 31(2), 358-368. [DOI:10.1016/j.engstruct.2008.09.001]
8. Dezvareh, R., Bargi, K., & Mousavi, S. A. (2016). Control of wind/wave-induced vibrations of jacket-type offshore wind turbines through tuned liquid column gas dampers. Structure and Infrastructure Engineering, 12(3), 312-326. [DOI:10.1080/15732479.2015.1011169]
9. Bargi, K., Dezvareh, R., & Mousavi, S. A. (2016). Contribution of tuned liquid column gas dampers to the performance of offshore wind turbines under wind, wave, and seismic excitations. Earthquake Engineering and Engineering Vibration, 15(3), 551-561. [DOI:10.1007/s11803-016-0343-z]
10. Hokmabady, H., Mohammadyzadeh, S., & Mojtahedi, A. (2019). Suppressing structural vibration of a jacket-type platform employing a novel Magneto-Rheological Tuned Liquid Column Gas Damper (MR-TLCGD). Ocean Engineering, 180, 60-70. [DOI:10.1016/j.oceaneng.2019.03.055]
11. Lu, F., Long, K., Diaeldin, Y., Saeed, A., Zhang, J., & Tao, T. (2023). A time-domain fatigue damage assessment approach for the tripod structure of offshore wind turbines. Sustainable Energy Technologies and Assessments, 60, 103450. [DOI:10.1016/j.seta.2023.103450]
12. Wu, T., Zhang, C., & Guo, X. (2024). Dynamic responses of monopile offshore wind turbines in cold sea regions: Ice and aerodynamic loads with soil-structure interaction. Ocean Engineering, 292, 116536. [DOI:10.1016/j.oceaneng.2023.116536]
13. Chen, J., Hu, Z., Liu, G., & Wan, D. (2019). Coupled aero-hydro-servo-elastic methods for floating wind turbines. Renewable energy, 130, 139-153. [DOI:10.1016/j.renene.2018.06.060]
14. Li, T. (2024). Machine learning-based wind turbine control systems for demand-oriented scenarios.
15. Shittu, A. A. (2020). Structural reliability assessment of complex offshore structures based on non-intrusive stochastic methods (Doctoral dissertation, Cranfield University).
16. Du, J., Li, H., Zhang, M., & Wang, S. (2015). A novel hybrid frequency-time domain method for the fatigue damage assessment of offshore structures. Ocean Engineering, 98, 57-65. [DOI:10.1016/j.oceaneng.2015.02.004]
17. Sharifi, M., Lotfollahi-Yaghin, M. A., Ahmadi, H., & Mojtahedi, A. (2025). Geometrical effects on the degree of bending (DoB) in two-planar tubular DY-joints of jacket substructure in offshore wind turbines. Ocean Engineering, 341, 122687. [DOI:10.1016/j.oceaneng.2025.122687]
18. Wang, Y., Liang, F., Zhang, H., & Zheng, H. (2025). Numerical evaluation of the dynamic performance of recommissioned offshore wind turbines under service life extension and repowering strategies. Computers and Geotechnics, 186, 107370. [DOI:10.1016/j.compgeo.2025.107370]
19. Jonkman, J. M., & Buhl, M. L. (2005). FAST user's guide (Vol. 365, p. 366). Golden, CO, USA: National Renewable Energy Laboratory.
20. Dezvareh, R., & Nazokkar, A. (2025). Enhancing Dynamic Performance of OC4-DeepCwind Semi-submersible Floating Wind Turbine Utilizing Multi-level Semi-active Dampers. Arabian Journal for Science and Engineering, 1-23. [DOI:10.1007/s13369-025-10507-0]
21. Nazokkar, A., & Dezvareh, R. (2022). Vibration control of floating offshore wind turbine using semi-active liquid column gas damper. Ocean Engineering, 265, 112574. [DOI:10.1016/j.oceaneng.2022.112574]
22. Emami, M., Dezvareh, R., & Mousavi, S. A. (2022). Contribution of fluid viscous dampers on fatigue life of lattice-type offshore wind turbines. Ocean Engineering, 245, 110506. [DOI:10.1016/j.oceaneng.2021.110506]
23. Muff, A., Wormsen, A., Hørte, T., Fjeldstad, A., Osen, P., Kirkemo, F., ... & Reinås, L. (2021, June). Use of DNVGL-RP-C203 for Determining the Fatigue Capacity of Connectors. In International Conference on Offshore Mechanics and Arctic Engineering (Vol. 85123, p. V002T02A010). American Society of Mechanical Engineers. [DOI:10.1115/OMAE2021-62880]
24. Kauzlarich, J. J. (1989). The palmgren-miner rule derived. In Tribology Series (Vol. 14, pp. 175-179). Elsevier. [DOI:10.1016/S0167-8922(08)70192-5]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
International Journal of Maritime Technology is licensed under a
Creative Commons Attribution-NonCommercial 4.0 International License.