As large-scale wind turbines are connected to the grid, modeling studies of wind farms are essential to the power system dynamic research. Due to the large number of wind turbines in the wind farm, detailed modeling of each wind turbine leads to high model complexity and low simulation efficiency. An equivalent modeling method for the wind farm is needed to reduce the complexity. For wind farms with widely used doubly-fed induction generators (DFIGs), the existing equivalent studies mainly focus on such continuous control parts as electrical control. These methods are unsuitable for the low voltage ride through (LVRT) part which is discontinuous due to switching control. Based on particle swarm optimization (PSO) and density-based spatial clustering of applications (DBSCAN), this paper proposes an equivalent method for LVRT characteristics of wind farms. Firstly, the multi-turbine equivalent model of the wind farm is established. Each wind turbine in the model represents a cluster of wind turbines with similar voltage variation characteristics. A single equivalent transmission line connects all wind turbines to the power grid. By changing the terminal voltage threshold to enter LVRT, each equivalent turbine can be in different LVRT states. Secondly, an LVRT parameter optimization method based on PSO is used to obtain the dynamic parameters of the equivalent wind turbines. This method of parameter optimization is applicable to the equivalent of LVRT parameters. Thirdly, a clustering method based on DBSCAN is used to obtain suitable clusters of wind turbines. This clustering method can classify wind turbines with similar electrical distances into the same cluster. Finally, two examples are set up to verify the proposed method.