用于中保真度风电场模拟中控制集成的交互式接口
An Interactive Interface for Control Integration in Mid-Fidelity Wind Farm Simulation
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中文总结 AI 辅助
研究针对风电场控制，提出基于Python的通用开源接口ffconnect，通过引入重组API、集成现代计算与机器学习生态系统，实现交互式设计与验证，经实验证明其运行时开销小且有效，并提供了源代码。
中文摘要 AI 辅助
风电场控制在减轻尾流效应（风力涡轮机之间的负面空气动力学相互作用）方面起着关键作用。数据驱动控制和人工智能的最新进展为设计更智能的风电场控制系统提供了新机会，因此需要一个支持模拟中交互式设计和验证的工具。为此，我们提出了ffconnect，这是一个基于Python的通用开源接口，用于中保真度风电场模拟器。与先前工作相比，ffconnect引入了具有丰富状态访问的重组应用程序编程接口（API），并通过完全基于Python构建，支持将该模拟器与现代科学计算和机器学习生态系统集成。实验表明，ffconnect在一系列模拟长度和农场规模下与原始模拟器相比运行时开销可忽略不计，并通过偏航跟踪案例研究证明了其有效性。最后，我们提供了ffconnect的源代码供普通用户使用。
英文摘要
Wind farm control (WFC) plays a crucial role in mitigating the wake effect, the negative aerodynamic interactions among wind turbines. Recent advances in data-driven control and artificial intelligence offer new opportunities to design more intelligent WFC systems, motivating the need for a tool that supports interactive design and validation in simulation. To address this, we present ffconnect, a general, open-source Python-based interface for FAST.Farm, a mid-fidelity wind farm simulator. Compared to prior work, ffconnect introduces a restructured Application Programming Interface (API) with enriched state access and supports integrating FAST.Farm with modern scientific computing and machine learning ecosystems by building entirely on Python. In experiments, ffconnect shows negligible runtime overhead compared to the original FAST.Farm across a range of simulation lengths and farm sizes, and demonstrates its effectiveness through a yaw-tracking case study. Finally, we provide the source code of ffconnect to keep it accessible for general users.
