期刊
CONTROL ENGINEERING PRACTICE
卷 84, 期 -, 页码 48-62出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.conengprac.2018.11.005
关键词
Nonlinear model predictive control; Adjoint approach; Wind farm control; Wake interactions; Maximal energy extraction
资金
- German Ministry of Economic Affairs and Energy (BMWi) in the scope of the WIMS-Cluster project [FKZ 0324005]
- Ministry for Science and Culture of Lower Saxony, Germany through the funding initiative Niedersachsisches Vorab in the scope of the ventus efficiens [ZN3024]
- Hanse-Wissenschaftskolleg in Delmenhorst, Germany
In this paper, a model predictive control (MPC) is proposed for wind farms to minimize wake-induced power losses. A constrained optimization problem is formulated to maximize the total power production of a wind farm. The developed controller employs a two-dimensional dynamic wind farm model to predict wake interactions in advance. An adjoint approach as an efficient tool is utilized to compute the gradient of the performance index for such a large-scale system. The wind turbine axial induction factors are considered as the control inputs to influence the overall performance by taking the wake interactions into account. A layout of a 2 x 3 wind farm is considered in this study. The parameterization of the controller is discussed in detail for a practical optimal energy extraction. The performance of the adjoint-based model predictive control (AMPC) is investigated with time-varying changes in wind direction. The simulation results show the effectiveness of the proposed approach. The computational complexity of the developed AMPC is also outlined with respect to the real time control implementation.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据