English(EN) Noise Steering: Exploiting Wake Steering and Acoustic Directivity for Noise-Constrained Wind Farm Control via Reinforcement Learning

噪声转向RL策略优化风电场功率和噪声水平

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-28 04:00

研究人员开发了一种名为噪声转向的新型强化学习策略，通过同时管理涡轮机偏航角和功率输出来优化风电场运行。该方法旨在在遵守当地噪声限制的同时最大限度地提高能源产量，其性能优于传统的降噪方法。该策略有效地将尾流和噪声重定向到远离敏感区域，与标准运行相比，显示出显著的功率增益。 AI

影响这项研究可能通过人工智能平衡发电和降噪，从而实现更高效的风电场运行。

排序理由该集群包含一篇详细介绍风电场控制新方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]

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arXiv cs.AI TIER_1 English(EN) · Mart\'in de Frutos, Baptiste Corban, Claire Bizon Monroc, Ana Bu\v{s}i\'c, Donatien Dubuc, Jiamin Zhud, Esteban Ferrer · 2026-10-28 04:00

噪声转向：利用尾流转向和声学指向性通过强化学习进行噪声约束的风电场控制

arXiv:2610.36888v1 Announce Type: new Abstract: Existing noise mitigation strategies for wind farms usually consist in reducing turbines power output, without accounting for the wake interactions between them and the noise emission directivity. This leads to over-conservative pol…