Gao Linyue, Milliren Christopher, Dasari Teja, Knoll Alexander A, Hong Jiarong
Department of Mechanical Engineering, University of Colorado Denver, 1200 Larimer Street, Denver, CO 80204, USA.
St. Anthony Falls Laboratory, University of Minnesota, Minneapolis, 2 Third Ave. SE Minneapolis, MN 55414, USA.
PNAS Nexus. 2024 Nov 4;3(11):pgae480. doi: 10.1093/pnasnexus/pgae480. eCollection 2024 Nov.
Wind direction variability with height, known as "wind veer," results in power losses for wind turbines (WTs) that rely on single-point wind measurements at the turbine nacelles. To address this challenge, we introduce a yaw control strategy designed to optimize turbine alignment by adjusting the yaw angle based on specific wind veer conditions, thereby boosting power generation efficiency. This strategy integrates modest yaw offset angles into the existing turbine control systems via a yaw-bias-look-up table, which correlates the adjustments with wind speed, and wind veer data. We evaluated the effectiveness of this control strategy through extensive month-long field campaigns for an individual utility-scale WT and at a commercial wind farm. This included controlling one turbine using our strategy against nine others in the vicinity using standard controls with LiDAR-derived wind veer data and a separate 2.5 MW instrumented research turbine continuously managed using our method with wind profiles provided by meteorological towers. Results from these campaigns demonstrated notable energy gains, with potential net gains exceeding 10% during extreme veering conditions. Our economic analysis, factoring in various elements, suggests an annual net gain of up to approximately $700 K for a 100-MW wind farm, requiring minimal additional investment, with potential for even larger gains in offshore settings with the power of individual turbines exceeding 10 MW nowadays. Overall, our findings underscore the considerable opportunities to improve individual turbine performance under realistic atmospheric conditions through advanced, cost-effective control strategies.
风向随高度的变化，即所谓的“风向偏差”，会导致依赖于涡轮机舱单点风速测量的风力涡轮机（WT）功率损失。为应对这一挑战，我们引入了一种偏航控制策略，旨在根据特定的风向偏差条件调整偏航角，从而优化涡轮机的对准，进而提高发电效率。该策略通过一个偏航偏差查找表将适度的偏航偏移角集成到现有的涡轮机控制系统中，该查找表将这些调整与风速和风向偏差数据相关联。我们通过对一台公用事业规模的单个风力涡轮机以及一个商业风电场进行为期一个月的广泛现场测试，评估了这种控制策略的有效性。这包括使用我们的策略控制一台涡轮机，同时对附近其他九台涡轮机使用基于激光雷达得出的风向偏差数据的标准控制，以及对一台单独的2.5兆瓦仪器化研究涡轮机使用我们的方法进行持续管理，并由气象塔提供风速剖面数据。这些测试结果表明有显著的能量增益，在极端风向偏差条件下潜在净增益超过10%。我们的经济分析考虑了各种因素，结果表明对于一个100兆瓦的风电场，每年净增益可达约70万美元，所需额外投资极少，在如今单机功率超过10兆瓦的海上环境中甚至可能有更大的增益。总体而言，我们的研究结果强调了通过先进且经济高效的控制策略在实际大气条件下改善单个涡轮机性能的巨大机会。
