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Article Navigation> JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY> 2020> 29(3): 417-424
Yuqiao Zheng, Lu Zhang, Fugang Dong, Bo Dong. Multi-Objective Structural Optimization of Wind Turbine Tower Using Nondominated Sorting Genetic Algorithm[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2020, 29(3): 417-424. doi: 10.15918/j.jbit1004-0579.20050
Citation: Yuqiao Zheng, Lu Zhang, Fugang Dong, Bo Dong. Multi-Objective Structural Optimization of Wind Turbine Tower Using Nondominated Sorting Genetic Algorithm[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2020, 29(3): 417-424.doi:10.15918/j.jbit1004-0579.20050
shu

Multi-Objective Structural Optimization of Wind Turbine Tower Using Nondominated Sorting Genetic Algorithm

doi:10.15918/j.jbit1004-0579.20050

  • School of Mechanical and Electronic Engineering, Lanzhou University of Technology, Lanzhou 730050, China

Funds:the National Natural Science Foundation of China (51965034); Foudamental Research Funds for the Lanzhou City Innovation and Entrepreneurship Projct (2018-RC-25）
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  • Corresponding author:associate professor, Ph.D. E-mail:zhengyuqiaolut@163.com
  • Received Date:2020-05-24
  • Publish Date:2020-09-30
    Abstract
  • A multi-objective optimization process for wind turbine steel towers is described in present work. The objective functions are tower top deformation and mass. The tower's height, radius and thickness are considered as design variables. The mathematical relationships between objective functions and variables were predicted by adopting a response surface methodology (RSM). Furthermore, the multi-objective non-dominated sorting genetic algorithm-II (NSGA-II) is adopted to optimize the tower structure to achieve accurate results with the minimum top deformation and total mass. A case study on a 2MW wind turbine tower optimization is given, which computes the desired tower structure parameters. The results are compared with the original tower: a reduction of tower top deformation reduction by about 16.5% and a reduction of a mass by about 1.5% could be achieved for such an optimization process.
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