When wind travels through turbines: A new statistical approach for characterizing heterogeneous wake effects in multi-turbine wind farms
When wind travels through turbines: A new statistical approach for characterizing heterogeneous wake effects in multi-turbine wind farms
复制标题
当风穿过涡轮机时：一种新的统计方法，用于表征多涡轮机风电场中的异质尾流效应
DOI：
10.1080/0740817x.2016.1204489
复制
发表时间：
2017
影响因子：
2.6
通讯作者：
Giwhyun Lee
中科院分区：
文献类型：
--
作者：
Mingdi You;E. Byon;Jionghua Jin;Giwhyun Lee
摘要现代公用事业规模的风力发电场包括大量的风力涡轮机。为了提高风力涡轮机的发电效率，在风电场设计和运行控制中，多涡轮机的发电水平的准确量化是至关重要的。一个具有挑战性的问题是，多个风力涡轮机的功率输出水平是不同的，这是由于涡轮机之间的复杂相互作用，称为尾流效应。通常，风力发电场中的上游涡轮机从风中吸收动能。因此，下游涡轮机倾向于产生比上游涡轮机更少的功率。此外，取决于天气条件，下游涡轮机的功率不足表现出异质模式。这项研究提出了一种新的统计方法来表征非均匀尾流效应。所提出的方法将功率输出分解为所有涡轮机通常表现出的平均模式和由多个涡轮机相互作用引起的涡轮机到涡轮机的可变性。为了捕获尾流效应，使用高斯马尔可夫随机场对涡轮特定回归参数进行建模。使用实际风电场数据的案例研究表明，所提出的方法的上级性能。
ABSTRACT Modern utility-scale wind farms consist of a large number of wind turbines. In order to improve the power generation efficiency of wind turbines, accurate quantification of power generation levels of multi-turbines is critical, in both wind farm design and operational controls. One challenging issue is that the power output levels of multiple wind turbines are different, due to complex interactions between turbines, known as wake effects. In general, upstream turbines in a wind farm absorb kinetic energy from wind. Therefore, downstream turbines tend to produce less power than upstream turbines. Moreover, depending on weather conditions, the power deficits of downstream turbines exhibit heterogeneous patterns. This study proposes a new statistical approach to characterize heterogeneous wake effects. The proposed approach decomposes the power outputs into the average pattern commonly exhibited by all turbines and the turbine-to-turbine variability caused by multi-turbine interactions. To capture the wake effects, turbine-specific regression parameters are modeled using a Gaussian Markov random field. A case study using actual wind farm data demonstrates the proposed approach's superior performance.