以一半潜式漂浮式海上风电基础为研究对象,基于浮体动力学频域仿真模型,利用支持向量机快速预报模型和基于方差的Sobol参数敏感性分析方法,探究耦合系统中浮式基础构件尺度与技术经济性之间的量化关系。同时,为了检验采样区间和步长对代理模型准确度的影响,分别采用两组不同采样方式获得的样本集对代理模型进行训练,并将两个模型分别用于参数敏感性分析。对比发现,两个样本集训练得到的代理模型预测结果与数值仿真结果吻合度较高,且基于两个代理模型开展参数敏感性分析得到的结果一致性较高,说明模型准确度基本未受到采样方法的影响。敏感性分析结果表明,浮式基础用钢量对立柱直径、跨距、吃水的敏感度较高,其总阶敏感度分别达到0.56、0.21和0.14;平台纵摇运动则对于立柱直径和吃水较为敏感,纵荡运动在不同工况下敏感度指标存在显著差异。在浮式基础尺度设计过程中,可根据不同参数的敏感性确定尺度优化方向,从而更快实现设计目标。
Abstract
The research focuses on the analysis of a semi-submersible floating offshore wind turbine based on the frequency-domain simulation tool. The approaches of support vector machine based surrogate model and the variance-based Sobol sensitivity analysis are utilised to investigate the quantitative correlation between the dimensions of the components and the performance of the floater. Meanwhile, to examine the effects of sampling range and interval on the accuracy of the surrogate model, two groups of samples obtained by the different sampling approach are used to train the models and the results are compared. It is found that the sampling approach has less effects on the accuracy of the model, as both the models show high accuracy in the prediction of the platform performance and yielding similar sensitivity analysis results. Sensitivity analysis results indicate that the steel weight of the floating platform is relatively sensitive to the column diameter, span and draft, with their total sensitivities being 0.56, 0.21 and 0.14 respectively. The platform pitch response shows higher sensitivity to column diameter and draft than other parameters, while the sensitivity index for platform surge response can be various for different environmental conditions. During the scaling design process of floating foundations, the optimization direction can be determined based on the sensitivity of different parameters, thereby achieving the design goals more efficiently.
关键词
海上风电 /
漂浮式风力机 /
敏感性分析 /
代理模型 /
优化设计
Key words
offshore wind power /
floating wind turbine /
sensitivity analysis /
surrogate model /
optimization design
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参考文献
[1] LI J, SHI W, ZHANG L, et al.Wind-wave coupling effect on the dynamic response of a combined wind-wave energy converter[J]. Marine science and engineering, 2021, 9(10): 1101.
[2] WANG S, XING Y, BALAKRISHNA R, et al.Design, local structural stress, and global dynamic response analysis of a steel semi-submersible hull for a 10-MW floating wind turbine[J]. Engineering structures, 2023, 291: 116474.
[3] WANG S S, MOAN T.Methodology of load effect analysis and ultimate limit state design of semi-submersible hulls of floating wind turbines: With a focus on floater column design[J]. Marine structures, 2024, 93: 103526.
[4] WANG S S, XING Y H, BALAKRISHNA R, et al.Design, local structural stress, and global dynamic response analysis of a steel semi-submersible hull for a 10-MW floating wind turbine[J]. Engineering structures, 2023, 291: 116474.
[5] 傅强, 刘笑语, 唐品, 等. 基于AHP-CRITIC法的半潜式钻井平台主尺度多准则决策[J].中国海洋平台,2021,036(5):63-70.
FU Q, LIU X, TANG P, et al.Multi-criteria decision-making of principal dimensions of semi-submersible drilling platforms based on AHP-CRITIC method[J]. China offshore platform, 2021.
[6] FERRI G, MARINO E, BORRI C.Optimal dimensions of a semisubmersible floating platform for a 10 MW wind turbine[J]. Energies, 2020, 13(12): 3092.
[7] LUAN C Y, GAO Z, MOAN T.Development and verification of a time-domain approach for determining forces and moments in structural components of floaters with an application to floating wind turbines[J]. Marine structures, 2017, 51: 87-109.
[8] 邱雨. Spar型浮式垂直轴风力机系统的运动响应研究[D]. 天津: 天津大学, 2016.
QIU Y.Research on motion response of spar floating vertical axis wind turbine system[D]. Tianjin: Tianjin University, 2016.
[9] 陈嘉豪, 尹梓炜, 朱容宽, 等. 漂浮式海上风机平台阻尼结构设计与研究[J]. 南方能源建设, 2021, 8(3): 18-25.
CHEN J H, YIN Z W, ZHU R K, et al.Design and research on the foundation damping structure of semi-submersible floating offshore wind turbines[J]. Southern energy construction, 2021, 8(3): 18-25.
[10] REN Y J, VENUGOPAL V, SHI W.Dynamic analysis of a multi-column TLP floating offshore wind turbine with tendon failure scenarios[J]. Ocean engineering, 2022, 245: 110472.
[11] WILEY W, JONKMAN J, ROBERTSON A, et al.Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads[J]. Wind energy science, 2023, 8(10): 1575-1595.
[12] MARTIN R, LAZAKIS I, BARBOUCHI S, et al.Sensitivity analysis of offshore wind farm operation and maintenance cost and availability[J]. Renewable energy, 2016, 85: 1226-1236.
[13] MAZETTO B M, RITTO T G.Uncertainty and global sensitivity analysis of wind turbines fatigue in non-ideal conditions[J]. Journal of vibration engineering & technologies, 2022, 10(6): 2391-2402.
[14] ECHEVERRÍA F, MALLOR F, SAN MIGUEL U. Global sensitivity analysis of the blade geometry variables on the wind turbine performance[J]. Wind energy, 2017, 20(9): 1601-1616.
[15] HÜBLER C, GEBHARDT C G, ROLFES R. Hierarchical four-step global sensitivity analysis of offshore wind turbines based on aeroelastic time domain simulations[J]. Renewable energy, 2017, 111: 878-891.
[16] WANG Y P, LU Q, YAO T C, et al.Global sensitivity analysis of a semi-submersible floating wind turbine using a neural network fitting method[J]. Ocean engineering, 2023, 285: 115351.
[17] FARAGGIANA E, SIRIGU M, GHIGO A, et al.An efficient optimisation tool for floating offshore wind support structures[J]. Energy reports, 2022, 8: 9104-9118.
[18] PILLAI A C, THIES P R, JOHANNING L.Mooring system design optimization using a surrogate assisted multi-objective genetic algorithm[J]. Engineering optimization, 2019, 51(8): 1370-1392.
[19] LEIMEISTER M, KOLIOS A.Reliability-based design optimization of a spar-type floating offshore wind turbine support structure[J]. Reliability engineering & system safety, 2021, 213: 107666.
[20] 姜宜辰, 段英杰, 王传晟, 等. 一种用于海上风电浮式基础主尺度的智能优化方法: CN202211245305[P].2023-01-06.
JIANG Y, DUAN Y, WANG C, et al.An intelligent optimization method for the main scale of offshore wind turbine floating foundations, CN115577629A[P]. 2022.
[21] 石嫄嫄, 和庆冬, 吴衍剑, 等. 基于多失效模式的海上浮式风电机组结构可靠性研究[J]. 太阳能学报, 2022, 43(9): 236-241.
SHI Y Y, HE Q D, WU Y J, et al.Multi-mode reliability analysis on structural of offshore floating wind turbine[J]. Acta energiae solaris sinica, 2022, 43(9): 236-241.
[22] 陈宇, 祝磊, 吴松熊. 新型漂浮式海上风电基础概念设计和初步动力响应分析[J]. 太阳能学报, 2024: 45(8): 581-586.
CHEN Y, ZHU L, WU S X.Conceptual design and preliminary dynamic response analysis of a new floating offshore wind power foundation[J]. Acta energiae solaris sinica. 2024, 45(8): 581-586.
[23] 张真真, 吴立东, 陈晓敏, 等. 基于支持向量机的风电机组变桨系统故障诊断[J]. 分布式能源, 2021, 6(3): 70-5.
ZHANG Z, WU L, CHEN X, etl. Fault diagnosis of wind turbine pitch system based on support vector machine[J]. Distributed energy, 2021, 6(3): 70-5.
[24] 李涛. 支持向量机在风电功率预测中的应用研究[D]. 北京: 北京交通大学, 2012.
LI T.Research on application of support vector machine in wind power prediction[D]. Beijing: Beijing Jiaotong University, 2012.
[25] Sobol′. Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates[J]. Mathematics and computers in simulation, 2001, 55(1/2/3): 271-280.
[26] CHANG C-C, LIN C-J.LIBSVM: A Library for support vector machines[J]. ACM transactions on intelligent systems and technology, 2011, 2(3): 27.
[27] BORTOLOTTI P, TARRÉS H C, DYKES K, et al. IEA wind TCP task 37: systems engineering in wind energy - WP2.1 reference wind turbines[R]. US: National Renewable Energy Laboratory, 2019.
[28] 李蜀军, 刘青松, 李春, 等. 极端海况下附配重系泊漂浮式风力机响应分析[J]. 太阳能学报, 2022, 43(12): 415-422.
LI S J, LIU Q S, LI C, et al.Response analysis of floating wind turbine with counterweight mooring under extreme sea conditions[J]. Acta energiae solaris sinica, 2022, 43(12): 415-422.
基金
水电水利规划设计总院科技项目（ZS-KJSD-20230005）; 国家自然科学基金面上项目（52071058）
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