The effect of timescales on wind farm power variability with nonlinear model predictive control: Variability reduction in wind farm model predictive control
The effect of timescales on wind farm power variability with nonlinear model predictive control: Variability reduction in wind farm model predictive control
复制标题
非线性模型预测控制下时间尺度对风电场功率变异性的影响：风电场模型预测控制中的变异性降低
DOI：
10.1002/we.2128
复制
发表时间：
2017
期刊：
影响因子：
4.1
通讯作者：
Hines, Paul D.
中科院分区：
文献类型：
--
作者：
Curtis Saunders, D.;Marshall, Jeffrey S.;Hines, Paul D.
模型预测控制技术使运营商能够在大型风电场中平衡多个目标，但控制器的设计取决于在不同时间尺度传播的建模效果。本文采用非线性模型预测控制研究如何通过改变影响系统控制的三个时间尺度的比率和在控制器目标函数中包含功率变化最小化措施来降低风电场功率变化。进行了测试，以评估不同的时间尺度比率如何影响平均农场功率和功率变异性。功率变率的措施被证明是敏感的事件风周期和涡轮机的时间延迟的比率，特别是对于占主导地位的事件风频率的情况下。随着控制器时间范围的增加，平均农场功率以一系列步骤增加，这对应于尾流扰动传播到下游涡轮机所需的时间范围值。进行第二组测试，其中功率变化的各种措施被纳入控制器的目标函数，并显示产生显着减少农场功率的变化，而没有显着减少农场功率输出。控制器被发现利用两种不同的方法来实现功率变化减少取决于制定的控制器目标函数。这些结果对风力发电厂的设计和运行具有重要意义，包括在涡轮机选址期间考虑风的频率分量的重要性，以及通过使用农场级协调控制来降低功率变化的潜力。版权所有© 2017约翰威利父子有限公司
Model predictive control techniques enable operators to balance multiple objectives in large wind farms, but the controller design depends on modeling effects that propagate at different timescales. This paper uses nonlinear model predictive control to investigate how wind farm power variability can be reduced both by varying ratios of three timescales impacting the system control and by inclusion of a power variability minimization measure in the controller objective function. Tests were conducted to assess how different timescale ratios affect the average farm power and power variability. Power variability measures are shown to be sensitive to the ratio of the incident wind period and the turbine time delay, particularly for cases with dominant incident wind frequencies. The average farm power increases in a series of steps as the controller time horizon increases, which corresponds to time horizon values required for wakes disturbances to propagate to downstream turbines. A second set of tests was conducted in which various measures of power variability were incorporated into the controller objective function and shown to yield significant reductions in farm power variability without significant reductions in farm power output. The controller was found to utilize two different approaches for achieving power variability reduction depending on the formulation of the controller objective function. These results have important implications for the design and operation of wind power plants, including the importance of considering the frequency components of wind during turbine siting and the potential to reduce power variability through the use of farm‐level coordinated control. Copyright © 2017 John Wiley & Sons, Ltd.