Multi-objective optimization of a negative stiffness vibration control system for offshore wind turbines

被引:4
|
作者
Kapasakalis, K. A. [1 ,3 ]
Gkikakis, A. E. [2 ]
Sapountzakis, E. J. [1 ]
Chatzi, E. N. [3 ]
Kampitsis, A. E. [4 ]
机构
[1] Natl Tech Univ Athens, Inst Struct Anal & Antiseism Res, Sch Civil Engn, Zografou Campus, Athens 15780, Greece
[2] Ist Italiano Tecnol, Dept Adv Robot, Via S Quirico 19D, I-16163 Genoa, Italy
[3] Swiss Fed Inst Technol, Dept Civil Environm & Geomat Engn, Stefano Franscini Pl 5, CH-8093 Zurich, Switzerland
[4] Aristotle Univ Thessaloniki, Inst Struct Anal & Dynam Struct, Sch Civil Engn, Thessaloniki 54124, Greece
关键词
Offshore wind turbines; Vibration control; Negative stiffness; Sensitivity and robust analysis; Multi-objective optimization; Nonlinear FEM; TUNED MASS DAMPERS; FOUNDATIONS; DESIGN;
D O I
10.1016/j.oceaneng.2024.117631
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
A systematic multi -objective optimization approach is presented for designing vibration control systems for monopile Offshore Wind Turbines (OWT) under the combined actions of wind and wave. An extended configuration of the KDamper (EKD) is employed, with second -order tower phenomena and soil-structure interaction effects taken into account. A holistic approach is employed to design an optimal EKD by considering competing objectives and limitations, such as engineering requirements, manufacturing specifications, available budget, and uncertainties in the design parameters. A global sensitivity analysis is conducted to identify the influence of each parameter of the OWT-EKD system on performance. Subsequently, a global multi -objective optimization is employed to explore the trade-off between conflicting objectives (Pareto front) and demonstrate that the EKD effectively operates even without specific components (e.g., dampers). In accounting for the uncertainties involved, such as manufacturing tolerances and environmental conditions, a robust analysis on a bi-objective Pareto front is performed, leading to the selection of EKD designs that exhibit superior average performance. The numerical results demonstrate the improvement in the peak tower dynamic response and the effective damping compared to a conventional Tuned Mass Damper comprising 20 times higher mass.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Multi-Objective Optimization and Comparison of DC/DC Converters for Offshore Wind Turbines
    Timmers, Victor
    Egea-Alvarez, Agusti
    Gkountaras, Aris
    Xu, Lie
    [J]. IEEE ACCESS, 2024, 12 : 81236 - 81251
  • [2] Data-driven predictive control for floating offshore wind turbines based on deep learning and multi-objective optimization
    Zhang, Yanfeng
    Yang, Xiyun
    Liu, Siqu
    [J]. OCEAN ENGINEERING, 2022, 266
  • [3] Multi-objective optimization for an autonomous unmoored offshore wind energy system substructure
    Annan, Aaron M.
    Lackner, Matthew A.
    Manwell, James F.
    [J]. APPLIED ENERGY, 2023, 344
  • [4] A Dynamic Multi-objective Model for Improving Maintenance Management of Offshore Wind Turbines
    Pliego Marugan, Alberto
    Garcia Marquez, Fausto Pedro
    Maria Pinar-Perez, Jesus
    [J]. PROCEEDINGS OF THE SIXTEENTH INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT - VOL 1, 2022, 144 : 112 - 123
  • [5] Multi-objective optimization for simultaneously designing active control of tower vibrations and power control in wind turbines
    Lara, Manuel
    Garrido, Juan
    Ruz, Mario L.
    Vazquez, Francisco
    [J]. ENERGY REPORTS, 2023, 9 : 1637 - 1650
  • [6] Multi-objective genetic algorithm-based wind turbines control
    Yin, Jintian
    Liu, Li
    Peng, Zhihua
    Chen, Riheng
    [J]. JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING, 2023, 23 (02) : 1053 - 1068
  • [7] A multi-objective design optimization framework for wind turbines under altitude consideration
    Mellal, Mohamed Arezki
    Pecht, Michael
    [J]. ENERGY CONVERSION AND MANAGEMENT, 2020, 222
  • [8] Data-driven multi-objective predictive control of offshore wind farm based on evolutionary optimization
    Yin, Xiuxing
    Zhang, Wencan
    Jiang, Zhansi
    Pan, Li
    [J]. RENEWABLE ENERGY, 2020, 160 : 974 - 986
  • [9] Multi-Objective Numerical Optimization of Radial Turbines
    Fuhrer, Christopher
    Kovachev, Nikola
    Vogt, Damian M.
    Mahalingam, Ganesh Raja
    Mann, Stuart
    [J]. Journal of Turbomachinery, 2024, 146 (03):
  • [10] MULTI-OBJECTIVE NUMERICAL OPTIMIZATION OF RADIAL TURBINES
    Fuhrer, Christopher
    Kovachev, Nikola
    Vogt, Damian M.
    Mahalingam, Ganesh Raja
    Mann, Stuart
    [J]. PROCEEDINGS OF ASME TURBO EXPO 2023: TURBOMACHINERY TECHNICAL CONFERENCE AND EXPOSITION, GT2023, VOL 13D, 2023,