With the complexity of large-scale wind farm

modeling for each turbine in wind farm will lead to excessive computing. Wind farm need to be simplified. This paper infers the correlation coefficient which can reflect spatial correlation between wind turbines on the basis of study on wake effect

altitude

shelter of and outage of turbine. The correlation coefficient is used as clustering index of K-means clustering algorithm. Cluster number need to be given for K-means clustering algorithm. This paper proposes an effectiveness indicator to determine the number of the optimal clustering and gives the parameter calculating method to get a wind farm model represented by multi equivalent wind turbines. The simulation results show that the proposed method has high precision and the improvement of K-means clustering algorithm is effective.