Surrogate models for substructure fatigue load estimation of offshore wind turbines

风电行业对清洁能源的需求日益增长，为世界提供低成本和低碳足迹的能源的愿望越来越强烈。与化石燃料发电相比，成本效益一直是使风力发电具有竞争力的主要驱动力。风力涡轮机子结构是风力涡轮机的最昂贵和最复杂的部分之一，通常使用不同的材料例如混凝土或钢构造。根据具体的涡轮机型号和现场条件，下部结构的尺寸可以延伸到直径几米和高度几十米。对于这些坚固的结构，气动载荷和结构阻尼成为分析的一个越来越重要的特征。准确的建模，然后是至关重要的优化性能和稳定性的子结构在风力发电系统，为了加快设计过程中，代理模型的发展具有重要意义。通过数据驱动和基于物理的方法创建的代理模型可以近似子结构的行为和响应，从而实现更快的评估和迭代。通过利用代理模型，工程师可以节省时间和资源，加快风电项目的设计优化和决策过程。

The wind power industry has witnessed a growing demand for cleaner energy resources, with an increasingly strong aspiration to provide the world with a low-cost and low carbon footprint energy source. Cost effectiveness has been the primary driving force in making wind power competitive compared to fossil fuel energy generation. Wind turbine substructures are among the most expensive and intrincate parts of the wind turbine, typically constructed using different materials such as concrete or steel. With sizes that vary depending on the specific turbine model and site conditions, substructure can extend several meters in diameter and tens of meters in height. With these substantial structures, the aerodynamic loads and structural damping becomes an increasingly critical feature to analyze. The accurate modelling then is crucial for optimizing the performance and stability of substructures in wind power systems and in order to expedite the design process, the development of surrogate models holds great importance. Surrogate models, created through data-driven and physics-based approaches, can approximate the behavior and response of substructures allowing for faster evaluations and iterations. By utilizing surrogate models, engineers can save time and resources, accelerating the design optimization and decision-making processes in wind power projects.