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Experience-guided optimization of jacket foundations for offshore wind turbines in varying water depths based on finite element analysis and the genetic algorithm
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Jiajia HUANG1,2, Tao JIN1, Jianwu HUANG1, Shasha SONG3,4, Wei DAI1, Chaoqun ZUO1, Lizhong WANG2, Lilin WANG5, Zhen GUO2. Experience-guided optimization of jacket foundations for offshore wind turbines in varying water depths based on finite element analysis and the genetic algorithm[J]. Journal of Zhejiang University Science A, 1998, -1(-1): .
@article{title="Experience-guided optimization of jacket foundations for offshore wind turbines in varying water depths based on finite element analysis and the genetic algorithm",
author="Jiajia HUANG1,2, Tao JIN1, Jianwu HUANG1, Shasha SONG3,4, Wei DAI1, Chaoqun ZUO1, Lizhong WANG2, Lilin WANG5, Zhen GUO2",
journal="Journal of Zhejiang University Science A",
volume="-1",
number="-1",
pages="",
year="1998",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A2500232"
}
%0 Journal Article
%T Experience-guided optimization of jacket foundations for offshore wind turbines in varying water depths based on finite element analysis and the genetic algorithm
%A Jiajia HUANG1
%A 2
%A Tao JIN1
%A Jianwu HUANG1
%A Shasha SONG3
%A 4
%A Wei DAI1
%A Chaoqun ZUO1
%A Lizhong WANG2
%A Lilin WANG5
%A Zhen GUO2
%J Journal of Zhejiang University SCIENCE A
%V -1
%N -1
%P
%@ 1673-565X
%D 1998
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A2500232
TY - JOUR
T1 - Experience-guided optimization of jacket foundations for offshore wind turbines in varying water depths based on finite element analysis and the genetic algorithm
A1 - Jiajia HUANG1
A1 - 2
A1 - Tao JIN1
A1 - Jianwu HUANG1
A1 - Shasha SONG3
A1 - 4
A1 - Wei DAI1
A1 - Chaoqun ZUO1
A1 - Lizhong WANG2
A1 - Lilin WANG5
A1 - Zhen GUO2
J0 - Journal of Zhejiang University Science A
VL - -1
IS - -1
SP -
EP -
%@ 1673-565X
Y1 - 1998
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A2500232
Abstract: Structural optimization plays a crucial role in reducing the cost of offshore wind power, particularly in deep-water regions where the weight of jacket foundations increases substantially. However, there is ongoing debate regarding the water-depth range that is suitable for jacket foundations, and the threshold where floating foundations become more viable. Existing studies have not quantitatively analyzed how water depth affects jacket foundation mass, and have often struggled to handle the high dimensionality and stringent constraints inherent in jacket foundation optimization problems. In this study, we propose an optimization framework that couples parametric finite element analysis with a genetic algorithm to minimize the mass of jacket foundations based on three actual engineering projects at varying water depths. A novel population initialization strategy incorporating engineering experience-based solutions is introduced to improve convergence efficiency and solution quality. Comparative analysis against preliminary designs and existing offshore wind projects demonstrates the model's ability to achieve cost-effective solutions, specifically reducing required jacket masses by 18.66%, 20.98%, and 17.22% at depths of 30.06m, 60.23m, and 89.81m, respectively. The results reveal a 122.94% increase in jacket mass-from 1431.28t to 3190.90t-as water depth increases from 30.06m to 89.81m. The jacket foundation demonstrates superior cost effectiveness in shallow to moderate water depths, as the mass per MW of floating foundations is 97.51% and 35.74% higher at depths of 60.23m and 89.81m, respectively. Accordingly, the applicable water-depth threshold between the jacket and floating foundation is estimated to be approximately 100m. The proposed optimization model offers a novel methodology and practical insights for the optimal design of offshore wind turbine support structures in varying marine environments.
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