Article(id=1281324022659002787, tenantId=1146029695717560320, journalId=1240685776644648972, issueId=1281323885077447100, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1007-7294.2026.02.005, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1750867200000, receivedDateStr=2025-06-26, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1783421052851, onlineDateStr=2026-07-07, pubDate=1771084800000, pubDateStr=2026-02-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783421052851, onlineIssueDateStr=2026-07-07, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783421052851, creator=13701087609, updateTime=1783421052851, updator=13701087609, issue=Issue{id=1281323885077447100, tenantId=1146029695717560320, journalId=1240685776644648972, year='2026', volume='30', issue='2', pageStart='177', pageEnd='340', issueExtLink='null', onlineDate='null', pubDate='1771084800000', pubDateStr='2026-02-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783421020049, creator='13701087609', updateTime=1783422086911, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1281328359892303896, tenantId=1146029695717560320, journalId=1240685776644648972, issueId=1281323885077447100, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1281328359892303897, tenantId=1146029695717560320, journalId=1240685776644648972, issueId=1281323885077447100, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=235, endPage=247, ext={EN=ArticleExt(id=1281324022872912292, articleId=1281324022659002787, tenantId=1146029695717560320, journalId=1240685776644648972, language=EN, title=Integrated analysis of Spar-type floating wind turbine under wind, wave and current conditions in South China Sea islands and reefs, columnId=1241023037940748650, journalTitle=Journal of Ship Mechanics, columnName=Hydrodynamics, runingTitle=null, highlight=null, articleAbstract=

In this study, an integrated simulation method of floating wind turbines based on wind-wave joint probability model and Modelica coupling simulation framework is constructed for the development of renewable energy in the South China Sea islands and reefs. Taking the island and reef sea area of Sansha City as the research object, the joint probability distribution model of wind and wave is reconstructed by historical meteorological data, and the data of island and reef sea area of Sansha City are established by combining with ocean current data. Based on the Modelica platform, a fully coupled numerical model of aerodynamics-hydrodynamics-control-structure-mooring is developed to study the coupled dynamic response characteristics of Spar-type floating wind turbine in the island reef area of Sansha City. The results show that the peak pitch angle of the platform is 4.74° (<5 ° design threshold) under working conditions. The maximum tension safety factor of mooring system meets the requirements of China Classification Society. Under rated conditions, the turbine speed is stable at 11.98 rpm (rated value 12.1 rpm), and the power output reaches 4.60 MW (rated power 5 MW). The research verifies the engineering applicability of the proposed method system, and provides an innovative technical evaluation framework and scientific decision-making basis for the deployment of floating wind power projects in the South China Sea islands.

, authors=Qiu-tong TAN1, 2, Chao HU1, Heng-le QU3, Yong MA1, 4, authorsList=Qiu-tong TAN, Chao HU, Heng-le QU, Yong MA, authorCompany=null, correspAuthors=Chao HU, Yong MA, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2026 Journal of Ship Mechanics. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1281324044179976741, articleId=1281324022659002787, tenantId=1146029695717560320, journalId=1240685776644648972, language=CN, title=南海岛礁风浪流条件下Spar型浮式风机一体化分析, columnId=1241023038087549292, journalTitle=船舶力学, columnName=流体力学, runingTitle=null, highlight=null, articleAbstract=

本研究针对南海岛礁海域浮式风机的开发需求,构建了基于风–浪联合概率模型与Modelica耦合仿真框架的浮式风机一体化仿真方法。以三沙市岛礁海域为研究对象,通过历史气象数据重构了风浪联合概率分布模型,并结合海流数据建立三沙市岛礁海域数据。基于Modelica平台开发了气动–水动–控制–结构–系泊全耦合数值模型,研究了Spar型浮式风机在三沙市岛礁海域的耦合动力响应特性。结果表明:在作业工况下,平台纵摇角峰值为4.74°,小于5°的设计阈值;系泊系统最大张力安全系数均满足中国船级社规范要求;额定工况下风机转速稳定在11.98 rpm接近额定值12.1 rpm,功率输出达4.60 MW接近额定功率5 MW。研究验证了所提方法的工程适用性,为南海岛礁浮式风机工程部署提供了仿真分析方法与科学决策依据。

, authors=谈秋桐1, 2, 胡超1, 曲恒乐3, 马勇1, 4, authorsList=谈秋桐, 胡超, 曲恒乐, 马勇, authorCompany=null, correspAuthors=胡超, 马勇, authorNote=

谈秋桐(1996–),男,博士研究生

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胡 超(1991–),男,博士,通讯作者,E-mail:
马 勇(1980–),男,博士,教授,通讯作者,E-mail:
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Challenges in simulation of aerodynamics, hydrodynamics, and mooring-line dynamics of floating offshore wind turbines[C]//The 21st International Offshore and Polar Engineering Conference, Maui, Hawaii: OnePetro, 2011., articleTitle=null, refAbstract=null), Reference(id=1281324053805904505, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=3, rfOrder=2, authorNames=null, journalName=null, refType=null, unstructuredReference=Ormberg H, Bachynski E E. 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ArticleFig(id=1281324049875841631, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=CN, label=图8, caption=UNSPAR的锚链布置图, figureFileSmall=yBr7ZEohJbdxK1e27Qmc3Q==, figureFileBig=UK4/RQRnE7oZt3w4IBrVrw==, tableContent=null), ArticleFig(id=1281324049955533408, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=EN, label=Fig.9, caption=Time domain rotation response of the FOWT, figureFileSmall=tsHnyppHaP5LnkqhCGY1vw==, figureFileBig=xETMYMNl1Fv2vaEqGopx7g==, tableContent=null), ArticleFig(id=1281324050018447969, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=CN, label=图9, caption=风机转速时域曲线, figureFileSmall=tsHnyppHaP5LnkqhCGY1vw==, figureFileBig=xETMYMNl1Fv2vaEqGopx7g==, tableContent=null), ArticleFig(id=1281324050081362530, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=EN, label=Fig.10, caption=Time domain power response of the FOWT, figureFileSmall=pSGkWpaOGKp1keS8jbmUFA==, figureFileBig=2JzBcU4CFmAimEBKqfW9qg==, tableContent=null), ArticleFig(id=1281324050165248611, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=CN, label=图10, caption=风机功率时域曲线, figureFileSmall=pSGkWpaOGKp1keS8jbmUFA==, figureFileBig=2JzBcU4CFmAimEBKqfW9qg==, tableContent=null), ArticleFig(id=1281324050295272036, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=EN, label=Tab.1, caption=

Properties of floating platform structure

, figureFileSmall=null, figureFileBig=null, tableContent=
参数数值
水线下深度(总吃水)120 m
水线上平台高度10 m
平台质量(含压载)7 466 330 kg
沿着平台中心线的水面
下的重心位置
89.9155 m
关于重心的平台横摇转动惯量4 229 230 000 kg·m2
关于重心的平台纵摇转动惯量4 229 230 000 kg·m2
关于重心的平台艏摇转动惯量164 230 00 kg·m2
), ArticleFig(id=1281324050408518245, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=CN, label=表1, caption=

浮式平台结构主要参数

, figureFileSmall=null, figureFileBig=null, tableContent=
参数数值
水线下深度(总吃水)120 m
水线上平台高度10 m
平台质量(含压载)7 466 330 kg
沿着平台中心线的水面
下的重心位置
89.9155 m
关于重心的平台横摇转动惯量4 229 230 000 kg·m2
关于重心的平台纵摇转动惯量4 229 230 000 kg·m2
关于重心的平台艏摇转动惯量164 230 00 kg·m2
), ArticleFig(id=1281324050467238502, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=EN, label=Tab.2, caption=

Parameters of 5MW NREL wind turbine

, figureFileSmall=null, figureFileBig=null, tableContent=
参数数值
额定功率5 MW
伺服控制统一变桨距控制
切入/额定/切出风速3/11.4/25 m/s
切入/额定转子转速6.9/12.1 rpm
转子/轮毂半径63/1.5 m
轮毂高度(相对塔基)80 m
塔架高度(相对塔基)77.6 m
塔架重心高度33.4 m
机舱相对z轴的转动惯量2.61×106 kg·m2
轮毂质量5.68×104 kg
轮毂转动惯量(相对转轴)1.16×105 kg·m2
), ArticleFig(id=1281324050538541671, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=CN, label=表2, caption=

5MW NREL风机主要参数

, figureFileSmall=null, figureFileBig=null, tableContent=
参数数值
额定功率5 MW
伺服控制统一变桨距控制
切入/额定/切出风速3/11.4/25 m/s
切入/额定转子转速6.9/12.1 rpm
转子/轮毂半径63/1.5 m
轮毂高度(相对塔基)80 m
塔架高度(相对塔基)77.6 m
塔架重心高度33.4 m
机舱相对z轴的转动惯量2.61×106 kg·m2
轮毂质量5.68×104 kg
轮毂转动惯量(相对转轴)1.16×105 kg·m2
), ArticleFig(id=1281324050605650536, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=EN, label=Tab.3, caption=

Properties of mooring

, figureFileSmall=null, figureFileBig=null, tableContent=
参数数值参数数值
锚链数3锚链直径0.09 m
相邻锚链夹角120°锚链等效质量密度77.7066 kg·m−1
下锚深度320 m水中锚链等效重力698.094 N·m−1
导缆孔深度70 m锚链等效拉伸刚度384243000 kg·m−1
下锚距平台中心线距离853.87 m附加艏摇弹性刚度98340000 Nm·rad−1
未拉伸状态锚链长度902.2 m
), ArticleFig(id=1281324050786005609, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=CN, label=表3, caption=

系泊主要参数

, figureFileSmall=null, figureFileBig=null, tableContent=
参数数值参数数值
锚链数3锚链直径0.09 m
相邻锚链夹角120°锚链等效质量密度77.7066 kg·m−1
下锚深度320 m水中锚链等效重力698.094 N·m−1
导缆孔深度70 m锚链等效拉伸刚度384243000 kg·m−1
下锚距平台中心线距离853.87 m附加艏摇弹性刚度98340000 Nm·rad−1
未拉伸状态锚链长度902.2 m
), ArticleFig(id=1281324050857308778, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=EN, label=Tab.4, caption=

Fitting parameters of wind and wave joint distribution

, figureFileSmall=null, figureFileBig=null, tableContent=
拟合参数数值拟合参数数值拟合参数数值
$ {\alpha }_{\text{U}} $2.309b31.563f12.5
$ {\beta }_{\text{U}} $9.546θ–0.36f24.25
a11.371γ1f30.90
a20.281e18k1–0.01
a31.138e20.48k20.19
b10.657e31.18k3–0.32
b20.035
), ArticleFig(id=1281324050957972075, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=CN, label=表4, caption=

风浪联合分布拟合参数

, figureFileSmall=null, figureFileBig=null, tableContent=
拟合参数数值拟合参数数值拟合参数数值
$ {\alpha }_{\text{U}} $2.309b31.563f12.5
$ {\beta }_{\text{U}} $9.546θ–0.36f24.25
a11.371γ1f30.90
a20.281e18k1–0.01
a31.138e20.48k20.19
b10.657e31.18k3–0.32
b20.035
), ArticleFig(id=1281324051129938540, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=EN, label=Tab.5, caption=

Parameters of design cases

, figureFileSmall=null, figureFileBig=null, tableContent=
工况名称编号风速Uw/(m·s−1有义波高Hs/m谱峰周期Tp/s流速/(m·s−1
作业工况LC182.5910.20.62
额定工况LC211.43.2410.50.62
自存工况LC328.997.2812.750.89
), ArticleFig(id=1281324052824437360, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=CN, label=表5, caption=

设计工况参数

, figureFileSmall=null, figureFileBig=null, tableContent=
工况名称编号风速Uw/(m·s−1有义波高Hs/m谱峰周期Tp/s流速/(m·s−1
作业工况LC182.5910.20.62
额定工况LC211.43.2410.50.62
自存工况LC328.997.2812.750.89
), ArticleFig(id=1281324052899934833, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=EN, label=Tab.6, caption=

Time domain motion response statistics of the FOWT

, figureFileSmall=null, figureFileBig=null, tableContent=
工况纵荡/m垂荡/m纵摇/°
最大值均值最大值均值最大值均值
LC126.0824.890.06–0.224.743.16
LC233.7526.080.43–0.256.824.76
LC312.858.011.09–0.0133.360.73
), ArticleFig(id=1281324052983820914, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=CN, label=表6, caption=

风机时域运动响应统计值

, figureFileSmall=null, figureFileBig=null, tableContent=
工况纵荡/m垂荡/m纵摇/°
最大值均值最大值均值最大值均值
LC126.0824.890.06–0.224.743.16
LC233.7526.080.43–0.256.824.76
LC312.858.011.09–0.0133.360.73
), ArticleFig(id=1281324053113844339, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=EN, label=Tab.7, caption=

Safety factors of mooring system

, figureFileSmall=null, figureFileBig=null, tableContent=
设计工况准静力分析动力分析
平台远离其他结构物平台邻近有其他结构物平台远离其他结构物平台邻近其他结构
完整作业工况2.73.02.252.47
完整自存工况2.02.21.671.84
破损作业工况1.82.01.571.73
破损自存工况1.432.00/1.571.251.37
瞬态作业工况1.221.34
瞬态自存工况1.051.16
), ArticleFig(id=1281324053290005108, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=CN, label=表7, caption=

系泊系统安全系数表

, figureFileSmall=null, figureFileBig=null, tableContent=
设计工况准静力分析动力分析
平台远离其他结构物平台邻近有其他结构物平台远离其他结构物平台邻近其他结构
完整作业工况2.73.02.252.47
完整自存工况2.02.21.671.84
破损作业工况1.82.01.571.73
破损自存工况1.432.00/1.571.251.37
瞬态作业工况1.221.34
瞬态自存工况1.051.16
), ArticleFig(id=1281324053378085493, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=EN, label=Tab.8, caption=

Force of mooring cable

, figureFileSmall=null, figureFileBig=null, tableContent=
工况名称失效锚链编号系泊索编号最大张力/kN安全系数
完整作业工况1729.42811.20
21329.1676.14
31325.7976.16
完整自存工况1795.65310.26
21057.6117.72
31057.6017.72
破损作业工况12524.98815.56
3543.04215.04
31272.87629.93
2520.35615.70
破损自存工况12550.49614.84
3550.48814.84
31274.97929.70
3530.53315.39
瞬态作业工况121008.4748.10
31008.4558.10
31781.00810.46
21008.4748.10
瞬态自存工况121076.3467.59
31076.3497.59
31805.28810.14
21076.3477.59
), ArticleFig(id=1281324053449388662, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1281324022659002787, language=CN, label=表8, caption=

系泊受力情况

, figureFileSmall=null, figureFileBig=null, tableContent=
工况名称失效锚链编号系泊索编号最大张力/kN安全系数
完整作业工况1729.42811.20
21329.1676.14
31325.7976.16
完整自存工况1795.65310.26
21057.6117.72
31057.6017.72
破损作业工况12524.98815.56
3543.04215.04
31272.87629.93
2520.35615.70
破损自存工况12550.49614.84
3550.48814.84
31274.97929.70
3530.53315.39
瞬态作业工况121008.4748.10
31008.4558.10
31781.00810.46
21008.4748.10
瞬态自存工况121076.3467.59
31076.3497.59
31805.28810.14
21076.3477.59
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南海岛礁风浪流条件下Spar型浮式风机一体化分析
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谈秋桐 1, 2 , 胡超 1 , 曲恒乐 3 , 马勇 1, 4
船舶力学 | 流体力学 2026,30(2): 235-247
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船舶力学 |流体力学 2026 , 30 (2) : 235 -247
南海岛礁风浪流条件下Spar型浮式风机一体化分析
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谈秋桐1, 2, 胡超1 , 曲恒乐3, 马勇1, 4
作者信息
  • 1.中山大学 海洋工程与技术学院,广东 珠海 519082
  • 2.招商局海洋装备研究院有限公司,广东 深圳 518067
  • 3.蓬莱巨涛海洋工程重工有限公司,山东 烟台 264000
  • 4.南方海洋科学与工程广东省实验室(珠海),广东 珠海 519082
通讯作者:
胡 超(1991–),男,博士,通讯作者,E-mail:
马 勇(1980–),男,博士,教授,通讯作者,E-mail:
作者简介:

谈秋桐(1996–),男,博士研究生

Integrated analysis of Spar-type floating wind turbine under wind, wave and current conditions in South China Sea islands and reefs
Qiu-tong TAN1, 2, Chao HU1 , Heng-le QU3, Yong MA1, 4
Affiliations
  • 1.School of Marine Engineering and Technology, Sun Yat-sen University, Zhuhai 519082, China
  • 2.China Merchants Marine and Offshore Research Institute Co., Ltd., Shenzhen 518067, China
  • 3.Penglai Jutal Offshore Engineering Heavy Industries Co., Ltd., Yantai 264000, China
  • 4.Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
出版时间: 2026-02-15 doi: 10.3969/j.issn.1007-7294.2026.02.005
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本研究针对南海岛礁海域浮式风机的开发需求,构建了基于风–浪联合概率模型与Modelica耦合仿真框架的浮式风机一体化仿真方法。以三沙市岛礁海域为研究对象,通过历史气象数据重构了风浪联合概率分布模型,并结合海流数据建立三沙市岛礁海域数据。基于Modelica平台开发了气动–水动–控制–结构–系泊全耦合数值模型,研究了Spar型浮式风机在三沙市岛礁海域的耦合动力响应特性。结果表明:在作业工况下,平台纵摇角峰值为4.74°,小于5°的设计阈值;系泊系统最大张力安全系数均满足中国船级社规范要求;额定工况下风机转速稳定在11.98 rpm接近额定值12.1 rpm,功率输出达4.60 MW接近额定功率5 MW。研究验证了所提方法的工程适用性,为南海岛礁浮式风机工程部署提供了仿真分析方法与科学决策依据。

一体化分析  /  Modelica  /  风浪联合分布  /  Spar型浮式风机

In this study, an integrated simulation method of floating wind turbines based on wind-wave joint probability model and Modelica coupling simulation framework is constructed for the development of renewable energy in the South China Sea islands and reefs. Taking the island and reef sea area of Sansha City as the research object, the joint probability distribution model of wind and wave is reconstructed by historical meteorological data, and the data of island and reef sea area of Sansha City are established by combining with ocean current data. Based on the Modelica platform, a fully coupled numerical model of aerodynamics-hydrodynamics-control-structure-mooring is developed to study the coupled dynamic response characteristics of Spar-type floating wind turbine in the island reef area of Sansha City. The results show that the peak pitch angle of the platform is 4.74° (<5 ° design threshold) under working conditions. The maximum tension safety factor of mooring system meets the requirements of China Classification Society. Under rated conditions, the turbine speed is stable at 11.98 rpm (rated value 12.1 rpm), and the power output reaches 4.60 MW (rated power 5 MW). The research verifies the engineering applicability of the proposed method system, and provides an innovative technical evaluation framework and scientific decision-making basis for the deployment of floating wind power projects in the South China Sea islands.

integration analysis  /  Modelica  /  joint distribution of wind and wave  /  Spar-type floating wind turbine
谈秋桐, 胡超, 曲恒乐, 马勇. 南海岛礁风浪流条件下Spar型浮式风机一体化分析. 船舶力学, 2026 , 30 (2) : 235 -247 . DOI: 10.3969/j.issn.1007-7294.2026.02.005
Qiu-tong TAN, Chao HU, Heng-le QU, Yong MA. Integrated analysis of Spar-type floating wind turbine under wind, wave and current conditions in South China Sea islands and reefs[J]. Journal of Ship Mechanics, 2026 , 30 (2) : 235 -247 . DOI: 10.3969/j.issn.1007-7294.2026.02.005
海洋覆盖了地球表面70%的区域,蕴藏着储量丰富的风能资源。海上风能相比于陆地风能具有风速高、风向稳、不占用土地等优势。然而,由于技术和经济上的限制,目前海上风力发电仅占全球可再生能源发电量的很小一部分,所以发展海上风电技术将在未来发挥重要作用。在海上风电技术中,浮式风机一体化仿真技术在风机的初步和详细设计中起着重要作用。
在海上浮式风机一体化仿真研究方面,由于频域计算在捕捉由气动载荷和控制系统引起的非线性动态特性方面存在缺陷,因此需要对浮式风机进行时域范围内的全耦合仿真分析[1]。目前浮式风机一体化仿真软件主要可分为三个类别,分别是商业软件、开源软件和结合开源代码的拓展类软件:
(1)在商业软件方面,目前较为知名的浮式风机一体化仿真软件有Bladed、HAWC2和Orcaflex等。(2)在开源软件中,由美国可再生能源实验室NREL开发的FAST系统是目前普遍认可的一体化仿真软件。(3)开源拓展类是指在原有开源代码的基础上,编写对应的接口程序,与目前已知的商业软件进行对接,使其具备对浮式风机进行一体化耦合计算的功能。这类软件普遍采用FAST中的开源代码,例如Matha等[2]将FAST中的气动模块Aerodyn和水动力模块Hydrodyn与多体仿真计算软件SIMPACK相结合对浮式风机进行时域运动仿真。Ormberg等[35]将Simo–Reflix求解器与Aerodyn进行耦合,使其成为可以进行包括风机塔筒和叶片弹性变形模拟的一体化仿真系统。Roddier等[6]整合了TimeFloat–FAST系统,并将其运用于WindFloat概念的一体化仿真中[7]。Yang等[8]和Zhang等[9]将FAST的部分模块进行改变并与水动力计算软件AQWA进行结合,拓展了对于不同平台概念的仿真应用,例如在平台上柔性连接浮体或波浪能装置。
除了以上所述三类传统的数值仿真方法外,基于AI的仿真方法和软件也相继面世,例如Hu等[10]开发了一种基于SADA机器学习方法的浮式风机全耦合仿真系统,并对由Chen等[11]开发的DARwind浮式风机一体化仿真系统进行深度学习,与实验结果进行对比,吻合较好。
然而,上述仿真软件普遍存在一些问题。(1)商业软件虽提供完整解决方案,但其封闭式架构导致三个显著缺陷:其一,核心算法不可见且无法修改,难以适配新型浮式结构创新需求;其二,系统间数据耦合依赖固定接口,制约多物理场深度交互分析;其三,软件扩展需依赖厂商定制开发,研究自主性受限。(2)对于FAST等开源工具及拓展类,其基于Fortran的面向过程开发模式导致代码复用率低、可维护性差,需要耗费大量的时间进行代码的研读并理清代码之间的调用和逻辑关系。(3)基于AI的仿真系统是一个黑盒系统,在进行新型风机的计算时,没有相应的学习目标,带来计算结果不稳定的风险。
为了解决以上问题,一些研究者[1216]正在尝试采用更为先进和开放的语言对浮式风机进行建模,其中Modelica语言以其独特的非因果建模方式和面向对象的编码方式,为研究者们提供一条高效的浮式风机一体化仿真路径。其优点如下:(1)利用Modelica语言构建模型时,等号两边变量调换位置和未调换是等效的,即所谓的“非因果关系”;而在其他的语言中,等号多作为单向赋值操作,即所谓“因果关系”。在求解常微分方程时,Modelica仅需要将方程列出,并设定自变量初值,求解器利用多种积分求解方法(如龙格库塔法、dassl变步长法)会自动对时间进行离散并求解方程组。对研究者而言,不需要建立数值迭代过程,可以降低建模难度,专注力学关系。(2)Modelica融合可视化建模和层级化分类的特点,可将力学关系用图形化方式表达。具体而言,可直接通过拓扑图进行建模,直观地理解各个模型之间的关系,相对于代码流式建模,拖拽建模可以自动生成对应的代码,也简化了代码输入的过程。(3)Modelica内置丰富的物理库,其力学多体库可大幅简化浮式风机建模过程,省去多体动力学中复杂的坐标转换代码,显著提升开发效率。
本研究采用Modelica语言,基于势流理论、叶素动量理论、悬链线方程和气动控制建立Spar型浮式风机一体化仿真预报模型。以中国南海西沙群岛三沙市周围海域为目标海域,对5 MW–Spar浮式风机进行一体化分析,为南海岛礁部署浮式风机提供参考。
根据美国国家海洋和大气管理局(NOAA)数据,我国西沙群岛周边海域水深最深处达到2966 m,但是由于岛屿周边有珊瑚礁形成礁盘,导致其水深大都在200 m范围之内,本文将平台安装在礁盘平台的边缘处,水深范围为250 m至400 m。
由于本项目中针对的目标海域水深与Hywind–Spar浮式风机平台设计水深(320 m)较为接近,本研究中将以NREL OC3–Hywind Spar型5 MW水平轴浮式风机为例进行研究。
该型浮式风机的基本形式如图1所示,相关参数可见表1表23
假设浮体的六自由度运动为$ \xi \left(t\right) $,根据牛顿第二定理,可以得到浮体运动方程为
$ {M}_{kj}{\ddot{\xi }}_{j}={F}_{j} $
式中:下标kj表示自由度(1=纵荡,2=横荡,3=垂荡,4=横摇,5=纵摇,6=艏摇),Mkj为浮体的惯性矩阵,Fj为载荷,其中包含了水动、气动、系泊等载荷,具体形式如下
$ {F}_{j}=F_{j}^{\text{Hydro}}+F_{}^{\text{Wind}}+F_{}^{\text{Mooring}}\text+{F}^{\text{Cu}\mathrm{rrent}} $
式中:$ F_{j}^{\text{Hydro}} $为水动力载荷,$ F_{}^{\text{Wind}} $为气动载荷,$ F_{}^{\text{Mooring}} $为系泊载荷,$ {F}^{\text{Current}} $为流载荷。
$ F_{j}^{{\mathrm{Hydro}}} $进行进一步的分解,如下
$ F_{j}^{\text{Hydro}}=F_{j}^{\text{Static}}+F_{j}^{\text{Wave}}+F_{j}^{\text{Drag}} $
式中:$ F_{j}^{\text{Static}} $为静水回复力,由浮态变化引起;$ F_{j}^{\text{Wave}} $为波浪力,由速度势变化引起的载荷;$ F_{j}^{\text{Drag}} $为黏性阻尼力,由于势流理论假设中忽略了黏性,为了弥补这部分载荷加入由莫里森公式计算得到的黏性阻尼力。
本研究引入空气动力学模块AeroDyn来解决叶片和塔架的气动载荷问题。在AeroDyn中采用叶素动量理论计算气动载荷,并进行了气动修正。通过假设1D动量理论和2D叶素理论中的气动载荷相等,建立BEM理论,并通过Brent's Method (诱导因子的迭代计算)进行求解,确定作用在每个叶素上的气动载荷,更详细内容见参考文献[17]。
控制器包括发电机转矩控制器和统一变桨距控制器。当风速小于额定风速时,采用发电机转矩控制器进行控制,以获得最大的风电增益。相比之下,当风速超过额定风速条件时,发电机转矩控制器不能再限制转速和气动转矩的继续增加。在这种情况下,将通过统一变桨距控制器对风机叶片的桨距角进行控制,以达到稳定气动载荷从而稳定发电机转速和功率的目标,避免发生功率过载的情况。
本模型采用悬链线系泊方式。重力式悬链线系泊系统在海上大型浮式平台中多有应用,主要采用钢制锚链,一端连接浮体,另一端连接锚,利用锚链自身的重力产生的拉力来稳定浮体。由于锚链的密度远大于水且运动相对缓慢,所以在数值仿真中可以采用准静态的方法对其进行建模计算约束载荷。在数值模型中,仅考虑锚链伸长变形的影响,对于一些动态特性,如惯性力、阻尼力、弯矩等均忽略。
在建立系泊模型时,假设系泊线时刻处于静力平衡状态。缆绳张力与缆绳在导缆点处的位置在局部坐标系中的关系可以用下面的非线性方程组[18]来表示
$\begin{split}&{X}_\text{F}=L-\frac{{V}_\text{F}}{\omega }+\frac{{H}_\text{F}}{\omega }{\mathrm{ln}}\left[\frac{{V}_\text{F}}{{H}_\text{F}}+\sqrt{\left(1+{\left(\frac{{V}_\text{F}}{{H}_\text{F}}\right)}^{2}\right)}\right]+\frac{{H}_\text{F}L}{EA}+\frac{{C}_\text{B}\omega }{2EA}\left[-\left(L-\frac{{V}_\text{F}}{\omega }\right)^{2}+\right.\\&\qquad \left.\left(L-\frac{{V}_\text{F}}{\omega }-\frac{{H}_\text{F}}{{C}_\text{B}\omega }\right){\mathrm{MAX}}\left(L-\frac{{V}_\text{F}}{\omega }-\frac{{H}_\text{F}}{{C}_\text{B}\omega },0\right)\right]\end{split}$
$ {z}_\text{F}=\frac{{H}_\text{F}}{\omega }\left[\sqrt{\left(1+{\left(\frac{{V}_\text{F}}{{H}_\text{F}}\right)}^{2}\right)}-\sqrt{\left(1+{\left(\frac{{V}_\text{F}-\omega L}{{H}_\text{F}}\right)}^{2}\right)}\right]+\frac{1}{EA}\left({V}_\text{F}L-\frac{\omega {L}^{2}}{2}\right) $
式中:XFZF为局部坐标系中的领航点位置,ω为单位长度流体中的表观重量,EA为伸展刚度,CB为海底静摩擦阻力系数,$ L $为总无伸展长度。采用牛顿–拉夫逊迭代方法求解该非线性方程组。
流载荷计算公式如下
$ {F}^{\text{Current}}=\frac{\text{1}}{\text{2}}{C}_{{\mathrm{D}}}{\rho }_{{\mathrm{W}}}{V}^{2}A $
式中:CD为曳力系数,ρW为海水密度,V为涉及海流流速,A为构件在与流速垂直平面上的投影面积。Spar平台的曳力系数CD=0.6。
本研究将一体化分析模型分为3个主要模块,即Modelica模块、Aerodyn气动载荷模块、动态链接库(Dynamic Link Library, DLL)。除此之外,在进行仿真之前需要通过AQWA或WAMIT等频域势流软件获得相应的水动力参数。系统构成结构及数据传输关系如图2所示,图中主要展示了系统所涉及的浮式风机一体化分析的各种载荷。模型的准确性和可靠性验证详见文献[19]。
图2中模块的主要功能如下:Modelica模块主要用于构建浮式风机各部件的多体动力学模型,并且集成了水动力载荷计算模块,是本系统用于对浮式风机进行动力学仿真的核心模块。Aerodyn是美国可再生能源实验室(NREL)基于动量叶素理论开发的水平轴风机气动计算组件,可以与一体化仿真软件FAST进行耦合,也可以作为单独的模块计算气动载荷。本研究对Aerodyn气动仿真模块进行二次开发,添加了与OpenModelica平台仿真过程中进行数据交换的功能,叶片和塔架上节点的位置和速度由Modelica中搭建的多体模型提供。在完成一个时间步的迭代后,Aerodyn会将气动载荷上传到由步进控制模块搭建的共享内存中以待Modelica模块进行下一时间步的计算。
本文以东经112.3°,北纬17°(三沙市坐标)为风浪统计节点,风浪数据在公共再处理数据库ERA5–Interim[20]中获得,其中包含了该坐标位置从2011年1月1日0:00至2020年12月31日23:00每小时的有义波高、平均波浪周期和10 m处的10分钟平均风速资料,总共有105168组数据点可供分析。由于该数据库提供的是平均波浪周期T1,需要将其转换为谱峰周期Tp,转换方法见 DNV船级社规范[21]。同时,由于本研究中设计的风机轮毂高度为90 m,应采用式(6)对10 m高处的风速进行转换,以得到90 m高度处的平均风速。
$ U(z)={U}_{10}{\left(\frac{z}{10}\right)}^{\alpha } $
式中:z为海平面以上高度值,$ {U}_{10} $为10 m高度处平均风速,α为粗糙度系数,海面取0.1。
本文采用Li等[22]提出的风浪联合概率密度分布进行分析,其中风浪联合概率密度函数可由下式表示
${f}_{{{U}_{\text{w}}}\text{,}{{H}_{\text{s}}}\text{,}{{T}_{\text{P}}}}\left({u}_{\text{w}},{h}_{\text{w}},{t}_{\text{w}}\right)={f}_{{{U}_{\text{w}}}}({u}_{\text{w}})\cdot {f}_{\left.{H}_{\text{s}}\right| {{U}_{\text{w}}}}(\left.{h}_{\text{w}}\right| {u}_{\text{w}})\cdot {f}_{{{T}_{\text{P}}}\left| {U}_{\text{w}}\text{,}{H}_{\text{s}}\right.}\left({t}_{\text{w}}\left| {u}_{\text{w}},{h}_{\text{w}}\right.\right)$
式中:$ {u}_{\text{w}} $为10分钟平均风速自变量,hw为有义波高自变量,tw为谱峰周期自变量,$ {f}_{{{U}_{\text{w}}}}({u}_{\text{w}}) $为10分钟平均风速的概率密度分布函数,$ {f}_{\left.{H}_{\text{s}}\right| {{U}_{\text{w}}}}(\left.{h}_{\text{w}}\right| {u}_{\text{w}}) $为在给定风速条件下的有义波高概率密度分布函数,$ {f}_{{{T}_{\text{P}}}\left| {U}_{\text{w}}\text{,}{H}_{\text{s}}\right.}\left({t}_{\text{w}}\left| {u}_{\text{w}},{h}_{\text{w}}\right.\right) $为给定风速和波高条件下的谱峰周期的概率密度函数。Uw表示轮毂高度处10分钟平均风速,Hs表示波浪的有义波高,Tp表示波浪的谱峰周期。
定义平均风速Uw的概率密度$ {f}_{{{U}_{\text{w}}}}(u) $由双参数Weibull分布近似拟合,如式(9)所示
$ {f}_{{{U}_{\text{w}}}}({u}_{\text{w}})=\frac{{\alpha }_{\text{U}}}{{\beta }_{\text{U}}}{\left(\frac{{u}_{\text{w}}}{{\beta }_{\text{U}}}\right)}^{{{\alpha }_{{\text{U}}}}-1}\cdot \exp \left[-{\left(\frac{{u}_{\text{w}}}{{\beta }_{\text{U}}}\right)}^{{{\alpha }_{{\text{U}}}}}\right] $
式中:$ {\alpha }_{\text{U}} $为形状参数,$ {\beta }_{\text{U}} $为尺度参数,可以采用最大似然法拟合,本文研究海域拟合结果如图3所示。
在不同风速条件下同样采用双参数Weibull分布来确定波高的条件概率密度函数$ {f}_{{{{H}}_{\text{s}}}\left| {{U}}_{\text{w}}\right.}\left({h}_{\text{w}}\left| {u}_{\text{w}}\right.\right) $,其表达式为
$ {f}_{\left.{H}_{\text{s}}\right| {{U}_{\text{w}}}}(\left.{h}_{\text{w}}\right| {u}_{\text{w}})=\frac{{\alpha }_{\text{HC}}}{{\beta }_{\text{HC}}}{\left(\frac{{h}_{\text{w}}}{{\beta }_{{\text{HC}}}}\right)}^{{{\alpha }_{{\text{HC}}}}-1}\cdot \exp \left[-{\left(\frac{{h}_{\text{w}}}{{\beta }_{{\text{HC}}}}\right)}^{{{\alpha }_{{\text{HC}}}}}\right] $
式中:$ {\alpha }_{\text{HC}} $为形状参数,$ {\beta }_{\text{HC}} $为尺度参数。当获得多组形状参数和尺度参数后,对其进行非线性拟合,如下所示
$ {\alpha }_{\text{HC}}={a}_{1}+{a}_{2}\cdot u_{\text{w}}^{{a}_{{3}}} $
$ {\beta }_{\text{HC}}={b}_{1}+{b}_{2}\cdot u_{\text{w}}^{{b}_{{3}}} $
式中:a1a2a3b1b2b3分别为非线性拟合曲线的参数,可通过最小二乘法获得。图4为采用拟合结果得到的平均值和标准差与原始数据对比的结果,可以看到拟合后的结果与原始数据吻合较好。
以上完成了风和浪的概率密度函数的构建,下面建立谱峰周期相对风速和有义波高的条件概率密度函数,谱峰周期满足对数正态分布,其概率密度函数如下式所示
${f}_{{{T}_{\text{P}}}\left| {U}_{\text{w}}\text{,}{H}_{\text{s}}\right.}\left({t}_{\text{w}}\left| {u}_{\text{w}},{h}_{\text{w}}\right.\right)=\frac{1}{\sqrt{2{\text{π}} }{\sigma }_{\ln ({{T}_{\text{P}}})t}}\cdot \exp \left[-\frac{1}{2}{\left(\frac{\ln \left({t}_{\text{w}}\right)-{\mu }_{\ln ({{T}_{\text{P}}})}}{{\sigma }_{\ln ({{T}_{\text{P}}})}}\right)}^{2}\right] $
其中,
$ {\mu }_{\ln ({{T}_{\text{P}}})}=\ln \left(\frac{{\mu }_{{{T}_{\text{P}}}}}{\sqrt{1+\nu _{{T}_{\text{P}}}^{2}}}\right) $
$ \sigma _{\ln ({T}_{\text{P}})}^{2}=\ln \left(\nu _{{T}_{\text{P}}}^{2}+1\right) $
$ {\nu }_{{{T}_{\text{P}}}}=\frac{{\sigma }_{{{T}_{\text{P}}}}}{{\mu }_{{{T}_{\text{P}}}}} $
式中:$ {\mu }_{{{T}_{\text{P}}}} $$ {\sigma }_{{{T}_{\text{P}}}} $为不同风浪条件下谱峰周期Tp的平均值和标准差,$ {\nu }_{{{T}_{\text{P}}}} $为协方差。
通过Johannessen提出的关于Tp正态分布的参数化表示方法,可得
$ {\mu }_{{{T}_{\text{P}}}}=\overline{t}\left({u}_{\text{w}},{h}_{\text{w}}\right)=\overline{t}\left({h}_{\text{w}}\right)\left(1+\theta {\left(\frac{u-\overline{u}\left({h}_{\text{w}}\right)}{\overline{u}\left({h}_{\text{w}}\right)}\right)}^{\gamma }\right) $
式中:θγ为拟合系数,$ \overline{t}\left(h\right) $$ \overline{u}\left(h\right) $分别为给定Hs条件下的波浪周期期望值和平均风速,通过非线性拟合方法来对波浪周期期望值和平均风速进行参数化处理,如式(18)和式(19)所示
$ \overline{t}\left({h}_{\text{w}}\right)={e}_{1}+{e}_{2}\cdot h_{\text{w}}^{{e}_{{3}}} $
$ \overline{u}\left({h}_{\text{w}}\right)={f}_{1}+{f}_{2}\cdot h_{\text{w}}^{{f}_{{3}}} $
式中:e1e2e3f1f2f3分别是非线性拟合曲线的参数。在给定有义波高Hs后,可确定$ \overline{t}\left({h}_{\text{w}}\right) $$ \overline{u}\left({h}_{\text{w}}\right) $的值。为了能够更容易地确定θγ的值,可将式(17)改写为如下形式
$ \frac{\overline{t}({u}_{\text{w}},{h}_{\text{w}})-\overline{t}({h}_{\text{w}})}{\overline{t}({h}_{\text{w}})}=\theta {\left(\frac{u-\overline{u}({h}_{\text{w}})}{\overline{u}({h}_{\text{w}})}\right)}^{\gamma } $
上式中左侧项为归一化的周期,$ (u-\overline{u}({h}_{\text{w}}))/\overline{u}({h}_{\text{w}}) $为归一化的风速,根据文献[22]的描述,归一化周期通常与归一化风速呈现线性关系,所以一般情况下γ取值为1,θ则可以通过最小二乘法进行数据拟合获得。协方差$ {\nu }_{{{\text{T}}_{\text{P}}}} $简化为关于有义波高的表达式,如下式所示
$ {\nu }_{{{T}_{\text{P}}}}({h}_{\text{w}})={k}_{1}+{k}_{2}\cdot \exp ({h}_{\text{w}}{k}_{3}) $
上述内容已确定了联合概率密度函数的所有拟合参数,由本文数据进行拟合得到的参数如表4所示,可获得风浪联合分布结果。
由前文所述得到风浪联合分布后,通过罗森不拉特变换[23]可以得到3个独立的标准高斯变量,分别反应了平均风速Uw的边缘变化、给定Uw条件下Hs的变换变化和给定UwHs条件下的TP边缘变化,所在重现周期的所有变量组合都位于一个半径为r的球面上。
$ \Theta \left(r\right)=1-\frac{1}{{N}_{Y}} $
式中:$ \Theta \left(r\right) $为标准正态分布函数,NY表示Y年重现期内的海况总数量,将式(22)的球体坐标转换回对应的物理参数,得到对应的UwHsTpY年重现期等高线表面。
根据《海上浮式风电平台指南》[24]中对于海上浮式风机平台的定位系泊系统的相关规定,考虑在重现期为N年的风,加上相对应的波浪和流的设计准则进行设计。
数据中8 m/s附近的风速出现的概率最大,因此取8 m/s作为正常风况的风速,而风机的额定风速为11.4 m/s,所以作为额定工况进行分析。取1年重现期中有义波高Hs最大值所对应的谱峰周期Tp作为作业工况和额定工况的波浪条件,1年重现期的风浪联合分布如图5所示,可得作业工况的有义波高和谱峰周期分别为Hs=2.59 m,Tp=10.2 s;额定工况的有义波高和谱峰周期为Hs=3.24 m,Tp=10.5 s。
对于自存工况,《海上浮式风机平台指南》中取1年或50年重现期的风况、海况条件,由于1年重现期的最大边缘分布风速仅为24.82 m/s,小于《海上移动平台入级规范》[25]中规定的最小持续风速25.8 m/s,不符合规范要求,所以舍弃此工况。而50年重现期的最大边缘分布风速为28.99 m/s,满足该风速要求,所以本文选取50年重现期作为分析的依据。图6为50年重现期对应的风浪联合分布,可以看到在最大风速28.99 m/s的条件下,有义波高和谱峰周期分别为Hs=7.28 m,Tp=12.75 s。表5展示了设计工况的相关参数。风选择湍流风,湍流模型为Kaimal,湍流强度为0.14。
由于缺少三沙市附近的流速相关数据,本文流速依据参考文献[26]选择南海1年重现期流速为0.62 m/s,50年重现期流速为0.89 m/s。风浪流始终沿X轴正方向作用于结构物。
图7为风机时域运动响应统计值,表6为风机时域运动响应统计值。可以看出,作业工况下的纵荡最大值为26.08 m,自存工况下的纵荡最大值为12.85 m。两种工况下的纵荡最大值相差较大,这是因为自存工况的风速已超过风机的切出风速,此时风力机处于刹车状态,并且叶片转向到受气动力最小的桨距角状态以避免过大的气动载荷使平台倒伏,而作业和额定工况下风机正常工作受到更大的推力作用。对于垂荡结果,自存工况下的结果明显大于作业工况和额定工况,说明垂荡自由度主要受到波浪的作用。在目标海域的作业工况下,纵摇最大值为4.74°,满足常见的海上漂浮式风机在发电工况下的纵摇要求,即不大于5°。
本研究的风机系泊系统布置如图8所示。系泊系统的设计不仅要满足浮体所规定的回复力要求,还需要满足对于锚链的强度要求。在作业工况和生存工况下,系泊设计能够保证浮体不发生倾覆,锚链不会断裂等情况。按照CCS的《海上移动平台入级规范》对锚链不同状态下的张力安全系数应不小于表7中的规定值,准静力分析法不适用于瞬态工况动力分析。
由于风机并不需要常驻的作业人员,因此运动响应只需要保证在作业工况和生存工况下系泊达到规定的安全系数即可。本文锚链采用R4级别标准,弹性极限张力为6437 kN,破断张力为8167 kN。
对系泊系统开展基于时域的动力安全评估。表8为系泊受力情况统计表。无论是在作业工况下还是自存工况下,各锚链的安全系数均满足系泊系统安全系数要求。从表中可以看出,完整系泊系统处于作业工况和自存工况时,2号张力最大,分别为1329.167 kN和1057.611 kN。2号和3号锚链张力大小相近,这是由于这两条锚链处于上游位置。自存工况下风机处于变桨停机状态,故其风载荷相对于作业工况下的明显减小,此时系泊力主要受波浪载荷的影响。对于破损和瞬态工况,考虑锚链失效下风机处于停机状态。对于破损工况,由于三根锚链的三点系泊,单锚失效引发平台偏移,导致剩余锚链悬链线躺底段长度增加,进而导致锚链的最大张力减小。对于瞬态工况,设定锚链在计算1000 s时失效,失效后剩余锚链张力减小,锚链的最大张力出现在锚链失效前。
图9图10分别为风机转速时域曲线和功率时域曲线。作业工况下的转速和功率平均值分别为9.26 rpm和1.96 MW。额定工况下转速和功率平均值分别为11.98 rpm和4.60 MW,可以看出风轮控制系统很好地实现了风轮在不同设计风速下的转速和功率输出控制。额定工况下转速均值11.98 rpm接近额定转速(12.1 rpm),输出功率4.60 MW略小于额定功率5 MW,主要是由于风机纵摇运动和湍流风的平均风速对风机输出功率的影响。
本研究通过构建南海岛礁海域风–浪–流联合作用模型与Modelica耦合仿真框架,建立了适用于南海岛礁环境的浮式风机一体化仿真分析方法。以中国南海三沙市附近为目标海域,对5 MW–Spar型浮式风机进行一体化分析,得到如下主要结论:
(1) 在浮式风机的一体化分析中,应当合理考虑风–浪联合作用。基于目标场址的长期风–浪观测数据建立风–浪联合概率分布模型,从而合理考虑风浪对浮式风机的作用。
(2) 该型风机在目标海域作业工况和额定工况下的纵荡值相近,且都远大于自存工况下的纵荡值,这说明了风机推力对风机纵荡的影响。自存工况下的垂荡最大值均大于作业工况和额定工况,这说明了波浪对垂荡的影响。作业工况下的纵摇最大值为4.75°,满足常见的海上漂浮式风机在正常工况下的纵倾要求,即不大于5°。
(3) 在目标海域下的风机系泊系统均满足CCS的安全系数要求。自存工况下的系泊张力最大值为1329.167 kN,远小于破断张力8167 kN。
综上所述,该型风机方案布放在三沙市周围切实可行,可为未来三沙市周围海域部署浮式风机提供参考。本研究也验证了所提方法体系的工程适用性,为南海岛礁浮式风电工程部署提供了仿真分析框架。

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2026年第30卷第2期
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doi: 10.3969/j.issn.1007-7294.2026.02.005
  • 接收时间:2025-06-26
  • 首发时间:2026-07-07
  • 出版时间:2026-02-15
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  • 收稿日期:2025-06-26
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    1.中山大学 海洋工程与技术学院,广东 珠海 519082
    2.招商局海洋装备研究院有限公司,广东 深圳 518067
    3.蓬莱巨涛海洋工程重工有限公司,山东 烟台 264000
    4.南方海洋科学与工程广东省实验室(珠海),广东 珠海 519082

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胡 超(1991–),男,博士,通讯作者,E-mail:
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2种不同金属材料的力学参数

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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