JOINT DISTRIBUTION OF WAVE PERIOD AND HEIGHT BASED ON COPULA FUNCTION

Song Chunyan; Liu Pan; Wang Yuankun; Ma Huiqun

doi:10.19912/j.0254-0096.tynxb.2020-0766

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Acta Energiae Solaris Sinica ›› 2022, Vol. 43 ›› Issue (4) : 375-379. DOI: 10.19912/j.0254-0096.tynxb.2020-0766

Topics on Key Technologies for Safety of Electrochemical Energy Storage Systems and Echelon Utilization of Decommissioned Power Batteries

JOINT DISTRIBUTION OF WAVE PERIOD AND HEIGHT BASED ON COPULA FUNCTION

Song Chunyan¹, Liu Pan¹, Wang Yuankun², Ma Huiqun¹

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Abstract

In order to study joint distribution of peak period and effective wave height, Weibull distribution is used to fit edge cumulative distribution of peak period and effective wave height. Kendall τ, Gumbel-hougaard copula function are used to construct joint distribution function of peak period and effective wave height. Statistical results are compared with measured sequence values. Results show that Copula function method can better fit joint distribution of wave period and height, and it is a continuous function distribution, which provides a more detailed basis for design of fatigue calculation, and also provides a new way to study relationship between them.

Key words

offshore wind power / Weibull distribution / maximum likelihood / Copula function

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Song Chunyan, Liu Pan, Wang Yuankun, Ma Huiqun. JOINT DISTRIBUTION OF WAVE PERIOD AND HEIGHT BASED ON COPULA FUNCTION[J]. Acta Energiae Solaris Sinica. 2022, 43(4): 375-379 https://doi.org/10.19912/j.0254-0096.tynxb.2020-0766

References

[1] 陈小波, 李静, 陈健云.海上风电机组随机风浪荷载时程数值计算[J]. 太阳能学报, 2011, 32(3): 288-295.
CHEN X B, LI J, CHEN J Y.Numerical calculation of random wind and wave loads time history of offshore wind turbine[J]. Acta energiae solaris sinica, 2011, 32(3): 288-295.
[2] 赵俭斌, 席义博, 王振宇.海上风力机单桩基础疲劳损伤计算方法[J]. 浙江大学学报(工学版), 2019, 53(9): 1711-1719.
ZHAO J B, XI Y B, WANG Z Y.Fatigue damage calculation method of monopole supported offshore wind turbine[J]. Journal of Zhejiang University(engineering science), 2019, 53(9): 1711-1719.
[3] 李红涛, 李林斌.海上风力机支撑结构设计分析[J]. 海洋工程, 2011, 29(4): 74-80.
LI H T, LI L B.Design analysis for supports structure of offshore wind turbine[J]. The ocean engineering, 2011, 29(4): 74-80.
[4] 郄禄文, 张立丹, 蒋学炼.随机波浪联合分布概率模型[J]. 河北大学学报(自然科学版), 2014, 34(3): 239-243.
QIE L W, ZHANG L D, JIANG X L.Joint probability distribution model of random waves[J]. Journal of Hebei University(natural science edition), 2014, 34(3): 239-243.
[5] 陈子燊, 刘曾美, 路剑飞, 等. 基于广义极值分布的设计波高推算[J]. 热带海洋学报, 2011, 30(3): 24-29.
CHEN Z S, LIU Z M, LU J F, et al. Calculation of design wave heights based on generalized extreme value distribution[J]. Journal of tropical oceanography, 2011, 30(3): 24-29.
[6] 陈子燊, 曹深西.基于Copula函数的波高与周期长期联合分布[J]. 海洋通报, 2012, 31(6): 630-635.
CHEN Z S, CAO S X.Long-term joint distribution of wave height and period based on copula functions[J]. Marine science bulletin, 2012, 31(6): 630-635.
[7] 陈子燊, 施伟勇, 路剑飞.波高周期联合分布四种重现水平对比分析[J]. 热带海洋学报, 2018, 37(4): 18-23.
CHEN Z S, SHI W Y, LU J F.Comparative analysis on four recurrence levels of joint distribution of wave height and period[J]. Journal of tropical oceanography, 2018, 37(4): 18-23.
[8] 陈子燊, 路剑飞, 于吉涛.基于非对称Archimedean Copula的三变量风浪重现水平分析[J]. 海洋通报, 2017, 36(6): 631-637.
CHEN Z S, LU J F, YU J T.Analysis on return levels of tri-variant stormy waves based on asymmetric archimedean copula function[J]. Marine science bulletin, 2017, 36(6): 631-637.
[9] 董胜, 翟金金, 陶山山.基于Archimedean Copula函数的风浪联合统计分析[J]. 中国海洋大学学报, 2014, 44(10): 134-141.
DONG S, ZHAI J J, TAO S S.Joint statistical analysis of winds and waves based on archimedean copula function[J]. Periodical of Ocean University of China, 2014, 44(10): 134-141.
[10] 董胜, 李静静.海洋平台环境设计参数的Plackett Copula分布估计[J]. 工程力学, 2015, 32(11): 251-256.
DONG S, LI J J.Marine environmental design parameter estimation with plackett copula distribution for ocean platform[J]. Engineering mechanics, 2015, 32(11): 251-256.
[11] SKLAR A.Fonctions de répartition an dimensions et leurs marges[M]. Paris: Public Institute Statistic University, 1959.
[12] MURRAT D.Modelling sample selection using archimedean copulas[J]. Econometrics journal, 2003(6): 99-123.
[13] 杨谋存, 聂宏.三参数Weibull分布参数的极大似然估计数值解法[J]. 南京航空航天大学学报, 2007, 39(1): 22-25.
YANG M C, NIE H.Advanced algorithm for maximum likelihood estimation of three parameter weibull distribution[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2007, 39(1): 22-25.
[14] 李军, 胡非, 王丙兰, 等. 风速的Weibull分布参数[J]. 太阳能学报, 2012, 33(10): 1667-1671.
LI J, HU F, WANG B L, et al. Weibull parameters for wind speed[J]. Acta energiae solaris sinica, 2012, 33(10): 1667-1671.