Treffer: Weighted graph wake decoupling (WGWD) method for efficient optimal active yaw control of wake-effect mitigation in large wind farm.

Through wind farm control, the negative impact of the wake effect on power production could be mitigated. In previous research on wind farm control, the centralized optimization method was mostly employed due to its simplicity. However, centralized optimization control methods will face difficulties for large wind farms, in which more complex wake coupling relationships among wind turbines will make the optimization highly inefficient. In order to boost the efficiency of the optimization, the weighted graph wake decoupling (WGWD) method is proposed in the current research, which decomposes the complex optimization problem into accessible sub-problems solved in parallel. A wake weighted graph portraying the wake coupling relationship among wind turbines has been established. The decoupling approach applied on a weighted graph partitions the wind farm into uncoupled subsets of wind turbines, simplifying the optimization problem. By using distributed optimization method, the yaw angles of wind turbines in each subset have been optimized to maximize the power generation of the subset. The results show that the proposed method has high computational efficiency and can also improve wind farm total power production. Taking advantage of its high efficiency, the proposed wind farm optimization control method is suitable for future real-time active yaw control of large wind farms. [ABSTRACT FROM AUTHOR]

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