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Multi-Objective Structural Optimization of a Composite Wind Turbine Blade Considering Natural Frequencies of Vibration and Global Stability

Author

Listed:
  • Lucas de Landa Couto

    (Department of Mechanical Engineering, Faculty of Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil)

  • Nícolas Estanislau Moreira

    (Department of Mechanical Engineering, Faculty of Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil)

  • Josué Yoshikazu de Oliveira Saito

    (Department of Mechanical Engineering, Faculty of Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil)

  • Patricia Habib Hallak

    (Department of Applied and Computational Mechanics, Faculty of Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil)

  • Afonso Celso de Castro Lemonge

    (Department of Applied and Computational Mechanics, Faculty of Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil)

Abstract

Aspects concerning resonance and global stability of a wind turbine blade must be carefully considered in its optimal design. In this paper, a composite wind turbine blade with an external geometry based on the NREL 5 MW model was subjected to multi-objective structural optimization considering these aspects. Four multi-objective structural optimization problems are formulated considering the blade mass, the maximum blade tip displacement, the natural frequencies of vibration, and the critical load factor as objective functions. The design variables are the number of plies, material, and fiber orientation. The design constraints are the materials’ margin of safety, the blade’s allowable tip displacement, and the minimum load factor. The blade model is submitted to the loads determined by the actuator lines theory and discretized in a finite element parameterized model using the Femap software according to geometric design variables. Among many multi-objective evolutionary algorithms available in the literature concerning evolutionary computation, the NSGA-II is the adopted evolutionary algorithm to solve the multi-objective optimization problems. Pareto fronts are obtained and performance indicators are used to evaluate the distribution of the non-dominated solutions. Multi-criteria decision-making is used to extract the solutions from the Pareto fronts according to the decision-maker’s preferences. The values of the objective functions, design variables, and constraints are presented for each extracted solution. The proposed study is expected to contribute to the multi-objective optimization and the structural design of wind turbine blades.

Suggested Citation

  • Lucas de Landa Couto & Nícolas Estanislau Moreira & Josué Yoshikazu de Oliveira Saito & Patricia Habib Hallak & Afonso Celso de Castro Lemonge, 2023. "Multi-Objective Structural Optimization of a Composite Wind Turbine Blade Considering Natural Frequencies of Vibration and Global Stability," Energies, MDPI, vol. 16(8), pages 1-25, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3363-:d:1120713
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    References listed on IDEAS

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    1. Jie Zhu & Xin Cai & Pan Pan & Rongrong Gu, 2014. "Multi-Objective Structural Optimization Design of Horizontal-Axis Wind Turbine Blades Using the Non-Dominated Sorting Genetic Algorithm II and Finite Element Method," Energies, MDPI, vol. 7(2), pages 1-15, February.
    2. Chehouri, Adam & Younes, Rafic & Ilinca, Adrian & Perron, Jean, 2015. "Review of performance optimization techniques applied to wind turbines," Applied Energy, Elsevier, vol. 142(C), pages 361-388.
    3. Karolina Talarek & Anna Knitter-Piątkowska & Tomasz Garbowski, 2022. "Wind Parks in Poland—New Challenges and Perspectives," Energies, MDPI, vol. 15(19), pages 1-25, September.
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