The emergency control strategy for mitigating cascading failures plays an important role in the safe and stable operation of power systems with high integration of renewable energy sources (RESs). To mitigate the high control costs associated with active splitting, this paper proposes a novel tree-partitioning based emergency control strategy. Initially, a coherency grouping model for power system integrated with wind turbines is established, incorporating an improved phase motion equation to facilitate the identification of unit homology. Furthermore, a modified fuzzy c-means (FCM) clustering algorithm is proposed to achieve the grouping of the generators. Then, the cluster partitioning issue is converted into an eigenvalue solution problem. This allows for a rapid and accurate cluster partitioning of the power system, taking into account both the random fluctuations of renewable energy output and the unit homology constraints. Based on the modified Prim’s algorithm, the tree-partitioning method is used to select the optimal bridge, whereby other bridges are disconnected and the inter-cluster power imbalances remain stable. A power adjustment measure is proposed to determine the power adjustment amount within each cluster based on the power flow tracing. Simulations on the IEEE 118-bus system and the actual case system demonstrate that the proposed strategy reduces control costs by 55.60% and 43.26% compared with active splitting, while also accelerating the post-fault recovery. These results highlight the potential of the proposed strategy for mitigating cascading failures in real-world applications. Index Terms—Cascading failure, emergency control, tree-par‐ titioning, cluster partitioning, coherency grouping, spectral clus‐ tering.