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A New Approach for Structural Optimization with Application to Wind Turbine Tower

Fugang Dong, Yuqiao Zheng*, Hao Li, Zhengwen He

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

* Corresponding Author: Yuqiao Zheng. Email: email

(This article belongs to the Special Issue: Wind Energy Development and Utilization)

Energy Engineering 2022, 119(3), 1017-1029. https://doi.org/10.32604/ee.2022.020430

Abstract

This work takes the bionic bamboo tower (BBT) of 2 MW wind turbine as the target, and the non-dominated sorting genetic algorithm (NSGA-II) is utilized to optimize its structural parameters. Specifically, the objective functions are deformation and mass. Based on the correlation analysis, the target optimization parameters were determined. Furthermore, the Kriging model of the BBT was established through the Latin Hypercube Sampling Design (LHSD). Finally, the BBT structure is optimized with multiple objectives under the constraints of strength, natural frequency, and size. The comparison shows that the optimized BBT has an advantage in the Design Load Case (DLC). This advantage is reflected in the fact that the overall stability of the BBT has increased by 2.45%, while the displacement of the BBT has decreased by 0.77%. In addition, the mass of the tower is decreased by 1.49%. Correspondingly, the steel consumption of each BBT will be reduced by 2789 Kg. This work provides a scientific basis for the structural design of the tower in service.

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Cite This Article

APA Style
Dong, F., Zheng, Y., Li, H., He, Z. (2022). A new approach for structural optimization with application to wind turbine tower. Energy Engineering, 119(3), 1017-1029. https://doi.org/10.32604/ee.2022.020430
Vancouver Style
Dong F, Zheng Y, Li H, He Z. A new approach for structural optimization with application to wind turbine tower. Energ Eng. 2022;119(3):1017-1029 https://doi.org/10.32604/ee.2022.020430
IEEE Style
F. Dong, Y. Zheng, H. Li, and Z. He, “A New Approach for Structural Optimization with Application to Wind Turbine Tower,” Energ. Eng., vol. 119, no. 3, pp. 1017-1029, 2022. https://doi.org/10.32604/ee.2022.020430



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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