Grand challenges in the design, manufacture, and operation of future wind turbine systems

IF 3.6 Q3 GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY
P. Veers, C. Bottasso, L. Manuel, J. Naughton, L. Pao, J. Paquette, A. Robertson, M. Robinson, S. Ananthan, T. Barlas, A. Bianchini, Henrik Bredmose, S. G. Horcas, J. Keller, H. A. Madsen, J. Manwell, P. Moriarty, S. Nolet, J. Rinker
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引用次数: 13

Abstract

Abstract. Wind energy is foundational for achieving 100 % renewable electricity production, and significant innovation is required as the grid expands and accommodates hybrid plant systems, energy-intensive products such as fuels, and a transitioning transportation sector. The sizable investments required for wind power plant development and integration make the financial and operational risks of change very high in all applications but especially offshore. Dependence on a high level of modeling and simulation accuracy to mitigate risk and ensure operational performance is essential. Therefore, the modeling chain from the large-scale inflow down to the material microstructure, and all the steps in between, needs to predict how the wind turbine system will respond and perform to allow innovative solutions to enter commercial application. Critical unknowns in the design, manufacturing, and operability of future turbine and plant systems are articulated, and recommendations for research action are laid out. This article focuses on the many unknowns that affect the ability to push the frontiers in the design of turbine and plant systems. Modern turbine rotors operate through the entire atmospheric boundary layer, outside the bounds of historic design assumptions, which requires reassessing design processes and approaches. Traditional aerodynamics and aeroelastic modeling approaches are pressing against the limits of applicability for the size and flexibility of future architectures and flow physics fundamentals. Offshore wind turbines have additional motion and hydrodynamic load drivers that are formidable modeling challenges. Uncertainty in turbine wakes complicates structural loading and energy production estimates, both around a single plant and for downstream plants, which requires innovation in plant operations and flow control to achieve full energy capture and load alleviation potential. Opportunities in co-design can bring controls upstream into design optimization if captured in design-level models of the physical phenomena. It is a research challenge to integrate improved materials into the manufacture of ever-larger components while maintaining quality and reducing cost. High-performance computing used in high-fidelity, physics-resolving simulations offer opportunities to improve design tools through artificial intelligence and machine learning, but even the high-fidelity tools are yet to be fully validated. Finally, key actions needed to continue the progress of wind energy technology toward even lower cost and greater functionality are recommended.
未来风力涡轮机系统的设计、制造和运行面临的巨大挑战
摘要风能是实现100 % 可再生电力生产,随着电网的扩展和适应混合动力发电厂系统、燃料等能源密集型产品以及转型的交通部门,需要进行重大创新。风电场开发和集成所需的大量投资使所有应用程序(尤其是海上应用程序)的财务和运营风险都非常高。依赖高水平的建模和模拟精度来降低风险和确保运营性能至关重要。因此,从大规模流入到材料微观结构的建模链,以及其间的所有步骤,都需要预测风力涡轮机系统将如何响应和执行,以允许创新解决方案进入商业应用。阐明了未来涡轮机和电厂系统的设计、制造和可操作性中的关键未知因素,并提出了研究行动建议。本文关注的是影响涡轮机和发电厂系统设计突破前沿能力的许多未知因素。现代涡轮机在整个大气边界层运行,在历史设计假设的边界之外,这需要重新评估设计过程和方法。传统的空气动力学和气动弹性建模方法正在挑战未来结构的尺寸和灵活性以及流动物理基础的适用性极限。海上风力涡轮机具有额外的运动和流体动力学负载驱动器,这是巨大的建模挑战。涡轮机尾流的不确定性使单个工厂和下游工厂的结构负荷和能源生产估计复杂化,这需要在工厂运营和流量控制方面进行创新,以实现完全的能源捕获和负荷减轻潜力。若在物理现象的设计级模型中捕捉到,联合设计中的机会可以将控制流带入设计优化。在保持质量和降低成本的同时,将改进的材料集成到更大部件的制造中是一项研究挑战。高保真度、物理解析模拟中使用的高性能计算为通过人工智能和机器学习改进设计工具提供了机会,但即使是高保真度工具也有待充分验证。最后,建议采取关键行动,继续推动风能技术朝着更低、更大的功能发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Wind Energy Science
Wind Energy Science GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY-
CiteScore
6.90
自引率
27.50%
发文量
115
审稿时长
28 weeks
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