In response to the limited power operation mode of wind farms, an active power optimization scheduling method for wind farms is proposed based on the state evaluation of wind turbines. This method achieves optimal operational control of wind farms. The computational complexity is relatively low. Firstly, the indicators in the comprehensive scoring system for wind turbines are defined. Additionally, the fuzzy entropy method is employed to calculate and rank the overall deterioration of power up-regulation/down-regulation. Then, wind turbines are classified according to their operational state, and the power regulation capacity of each class of wind turbines is determined. Subsequently, the active power optimization scheduling of wind farms is implemented based on the classification and ranking of wind turbines. Finally, a simulation test is conducted using historical data from a wind farm. The results demonstrate that the proposed method can achieve higher power command tracking accuracy under different power limitation levels of wind farms. Moreover, power scheduling based on the comprehensive deterioration ranking of the turbines can effectively reduce power fluctuation differences, load fatigue differences, and overall power fluctuations between the turbines. The standard deviation of the power fluctuation coefficient has been reduced to 0.0705, marking a 9.85% decrease compared to the previous scheme.
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