When combining K-means clustering with Copula theory to build scenario-based probabilistic model, K-means clustering can’t spontaneously determine the optimal number of clustering. For this deficiency, this paper proposes a density-based index to determine the optimal number of clustering. Then the optimal scenario-based probabilistic model is built, based on which reactive power optimization is conducted by adopting modified backtracking search algorithm (BSA). At last, the proposed method is verified in IEEE30 system with data measured from two adjacent wind farms in Australia, and simulation results indicate that adopting optimal number of clustering determined by proposed method could get an accurate description of correlation between wind farms. This work is supported by National Key Technology Support Program (No. 2014BAG08B01), National Natural Science Foundation of China (No. 51177138, No. 61473238, and No. 51407146), and National Science Fund for Distinguished Young Scholars (No. 2015JQ0016).