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

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

Received 23 November 2021; Accepted 15 February 2022; Issue published 31 March 2022

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.

Keywords

Wind turbine tower; bionic bamboo tower; correlation analysis; multi-objective optimization

Cite This Article

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.



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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