Xue Peng, Wan Yi, Takahashi Jun, Akimoto Hiromichi
Department of Systems Innovation, The University of Tokyo, Hongo 7-3-1, Bunkyo-Ku, Tokyo, 113-8656, Japan.
Heliyon. 2024 Jun 18;10(12):e33185. doi: 10.1016/j.heliyon.2024.e33185. eCollection 2024 Jun 30.
A wind turbine comprises multiple components constructed from diverse materials. This complexity introduces challenges in designing the blade structure. In this study, we developed a structural optimization framework for Vertical Axis Wind Turbines (VAWT). This framework integrates a parametric Finite Element Analysis (FEA) model, which simulates the structure's global behavior, with a Genetic Algorithm (GA) optimization technique that navigates the design domain to identify optimal parameters. The goal is to minimize the mass of VAWT structures while adhering to a suite of complex constraints. This framework quantifies the mass reduction impact attributable to material selection and structural designs. The optimization cases indicate that blades made from Carbon Fiber Reinforced Plastics (CFRP) materials are 47.1 % lighter than those made from Glass Fiber Reinforced Plastics (GFRP), while the structural parts are 44.8 % lighter. This work also provides further recommendations regarding the scale and design of the structures. With the materials and structural design established, future studies can expand to include more load cases and detailed designs of specific components.
风力涡轮机由多种不同材料制成的部件组成。这种复杂性给叶片结构设计带来了挑战。在本研究中，我们开发了一种用于垂直轴风力涡轮机（VAWT）的结构优化框架。该框架将模拟结构整体行为的参数化有限元分析（FEA）模型与在设计域中寻找最优参数的遗传算法（GA）优化技术相结合。目标是在遵守一系列复杂约束条件的同时，使VAWT结构的质量最小化。该框架量化了材料选择和结构设计对质量减轻的影响。优化案例表明，由碳纤维增强塑料（CFRP）材料制成的叶片比由玻璃纤维增强塑料（GFRP）制成的叶片轻47.1%，而结构部件则轻44.8%。这项工作还提供了关于结构规模和设计的进一步建议。随着材料和结构设计的确定，未来的研究可以扩展到包括更多的载荷工况和特定部件的详细设计。
