Abstract

In complex-terrain wind farms (WFs), a serious uneven distribution of fatigue loads increases the operation and maintenance cost of wind power generation. Therefore, this study proposes a comprehensive optimization for fatigue loads of wind turbine (WT) components. The optimization is performed at two levels: WT and WF. The central controller of WF redispatches the active power reference for each WT, and the local controller of WT is performed to appropriately reduce the generator speed. For WT level, a variance-based sensitivity analysis is performed to assess the effect of generator speed and active power on component fatigue loads. The analysis results show a high sensitivity of all fatigue loads of components to the generator speed, while the load sensitivity of blade (Mz) and tower (My) to active power is considerably high. For WF level, a novel Multi-objective adaptive Yin-Yang pair optimization algorithm is proposed to coordinatively optimize fatigue load distribution and active power dispatch. The Pareto Front of optimized fatigue load deviations is obtained for the target components, which correspond to a series of optimization solutions. Then, weighted analysis is employed to evaluate the optimal solutions, and the solution with the smallest weighted value is selected as the appropriate solution. Finally, the simulation test using the real data from the complex-terrain WF is conducted, and the comparison results confirm the effectiveness of the proposed optimization approaches.

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