Abstract

Summary To optimize the fatigue distribution and the active power output of an onshore wind farm, we develop a new centralized approach for optimizing active power references for each wind turbine. The fatigue of a turbine is modeled by a fatigue coefficient integrated with wind characteristics. In the active power dispatching optimization model, the objective function is designed to minimize the standard deviation of the fatigue coefficient for every turbine. Moreover, the optimization is constrained by active power limitations of the turbines and the wind farm. To solve this problem in real time, we propose an improved genetic algorithm that is embedded with partial constraints of the optimization model. Detailed simulation results demonstrate that the fatigue level among turbines becomes balanced, and active power demands for the farm are satisfied. The proposed approach is a feasible way to use the active power curtailment to reduce the maintenance frequency of wind farms.

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