Multi-Objective Structural Optimization of a Wind Turbine Tower

doi:10.1007/s12204-020-2190-3

Journal of Shanghai Jiao Tong University(Science) ›› 2020, Vol. 25 ›› Issue (4): 538-544.doi: 10.1007/s12204-020-2190-3

• • 上一篇

Multi-Objective Structural Optimization of a Wind Turbine Tower

ZHENG Yuqiao (郑玉巧), ZHANG Lu (张璐), PAN Yongxiang (潘永祥), HE Zhe (和哲)

(School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou 730050, China)

出版日期:2020-08-28 发布日期:2020-07-29
通讯作者: ZHENG Yuqiao (郑玉巧) E-mail:zhengyuqiaolut@163.com

Multi-Objective Structural Optimization of a Wind Turbine Tower

ZHENG Yuqiao (郑玉巧), ZHANG Lu (张璐), PAN Yongxiang (潘永祥), HE Zhe (和哲)

(School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou 730050, China)

Online:2020-08-28 Published:2020-07-29
Contact: ZHENG Yuqiao (郑玉巧) E-mail:zhengyuqiaolut@163.com

摘要/Abstract

摘要： The 2MW wind turbine tower is considered as the baseline configuration for structural optimization.
The design variables consist of the thickness and height located at the top tower junction. The relationships
between the design variables and the optimization objectives (mass, equivalent stress, top displacement and
fatigue life) are mapped on the basis of uniform design and regression analysis. Subsequently, five solutions are
developed by an algorithm, NSGA-III. According to their efficiency and applicability, the most suitable solution
is found. This approach yields a decrease of 0.48% in the mass, a decrease of 54.48% in the equivalent stress and
an increase of 8.14% in fatigue life, as compared with existing tower designs. An improved wind turbine tower is
obtained for this practice.

关键词: structural optimization, wind turbine tower, multi-objective optimization algorithm, uniform design

Abstract: The 2MW wind turbine tower is considered as the baseline configuration for structural optimization.
The design variables consist of the thickness and height located at the top tower junction. The relationships
between the design variables and the optimization objectives (mass, equivalent stress, top displacement and
fatigue life) are mapped on the basis of uniform design and regression analysis. Subsequently, five solutions are
developed by an algorithm, NSGA-III. According to their efficiency and applicability, the most suitable solution
is found. This approach yields a decrease of 0.48% in the mass, a decrease of 54.48% in the equivalent stress and
an increase of 8.14% in fatigue life, as compared with existing tower designs. An improved wind turbine tower is
obtained for this practice.

Key words: structural optimization, wind turbine tower, multi-objective optimization algorithm, uniform design

中图分类号:

TK 83

ZHENG Yuqiao, ZHANG Lu, PAN Yongxiang, HE Zhe . Multi-Objective Structural Optimization of a Wind Turbine Tower[J]. Journal of Shanghai Jiao Tong University(Science), 2020, 25(4): 538-544.

参考文献 18

[1]	LEE D Y, DOBLASREYES F J, TORRALBA V, et al. Multi-model seasonal forecasts for the wind energy sector [J]. Climate Dynamics, 2019, 53(5/6): 2715-2729.
[2]	KARNI A, LUO L W, MUMTAZ M A, et al. Simple approach on intermixing solar and wind energy and minimizing their intermittent effect [J]. Journal of Shanghai Jiao Tong University (Science), 2019, 24(1):24-30.
[3]	HERATH M T, LEE A K L, PRUSTY B G. Design of shape-adaptive wind turbine blades using differential stiffness bend-twist coupling [J]. Ocean Engineering,2015, 95: 157-165.
[4]	ZAVALA G R, NEBRO A J, LUNA F, et al. A survey of multi-objective metaheuristic applied to structural optimization [J]. Structural and Multidisciplinary Optimization,2014, 49(4): 537-558.
[5]	DAI J C, LIU Z Q, LIU X, et al. Structural parameters multi-objective optimization and dynamic characteristics analysis of large-scale wind turbine towers [J].Australian Journal of Mechanical Engineering, 2017,16(1): 1-7.
[6]	PERELMUTER A, YURCHENKO V. Parametric optimization of steel shell towers of high-power wind turbines[J]. Procedia Engineering, 2013, 57: 895-905.
[7]	HAGHI R, ASHURI T, VAN DER VALK P L C, et al.Integrated multidisciplinary constrained optimization of offshore support structures [J]. Journal of Physics:Conference Series, 2014, 555: 012046.
[8]	GENCTURK B, ATTAR A, TORT C. Selection of an optimal lattice wind turbine tower for a seismic region based on the cost of energy [J]. KSCE Journal of Civil Engineering, 2015, 19(7): 2179-2190.
[9]	DEB K, JAIN H. An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, Part I: Solving problems with box constraints [J]. IEEE Transactions on Evolutionary Computation, 2014, 18(4): 577-601.
[10]	CHAHARDOLIA S, HADIAN H, VAHEDI R. Optimization of hole height and wall thickness in perforated capped-end conical absorbers under axial quasi-static loading (using NSGA-III and MOEA/D algorithms)[J]. Thin-Walled Structures, 2018, 127: 540-555.
[11]	BI X J, WANG C. An improved NSGA-III algorithm based on objective space decomposition for manyobjective optimization [J]. Soft Computing, 2017,21(16): 4269-4296.
[12]	HE Z. Study on multi-objective optimization structural parameters of MW wind turbine tower [D].Lanzhou, China: Lanzhou University of Technology,2019 (in Chinese).
[13]	International Electrotechnical Commission. Wind energy generation systems. Part 6. Tower and foundation requirements: IEC61400-6 ED1 [S]. Geneva: IEC,2018.
[14]	WU L, LIUWY, SU ZM, et al. Buckling design of conical shells based on palm trunks: Survey of power-law distributed thin-walled conical [J]. Journal of Shanghai Jiao Tong University (Science), 2016, 21(3): 313-319.
[15]	ZHENG Y Q, ZHAO R Z. Characteristics for wind energy and wind turbines by considering vertical wind shear [J]. Journal of Central South University, 2015,22(6): 2393-2398.
[16]	BREEZE P. Wind power generation [M]. New York,USA: Academic Press, 2016.
[17]	LUND E, STEGMANN J. Structural optimization of composite shell structures using a discrete constitutive parameterization [J]. Wind Energy, 2005, 8(1): 109-124.
[18]	IERIMONTI L, VENANZI I, CARACOGLIA L. Lifecycle damage-based cost analysis of tall buildings equipped with tuned mass dampers [J]. Journal of Wind Engineering and Industrial Aerodynamics, 2018,176: 54-64.

Multi-Objective Structural Optimization of a Wind Turbine Tower

Multi-Objective Structural Optimization of a Wind Turbine Tower

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献 18

相关文章 2

编辑推荐

Metrics

本文评价

[1]	YU Zelin, SUN Pengwen, WANG Dong. Fatigue Life Prediction for Flange Connecting Bolts of Wind Turbine Tower[J]. Journal of Shanghai Jiao Tong University(Science), 2020, 25(4): 526-530.
[2]	GUO Wenqiang (郭文强), SUN Pengwen (孙鹏文), NIU Lei (牛磊), WANG Zongtao (王宗涛). Fatigue Life Analysis of Longitudinal Welding Seam for Wind Turbine Tower[J]. Journal of Shanghai Jiao Tong University (Science), 2020, 25(2): 261-265.