To address the problem that the reactive power compensation configuration of new energy power systems is mostly based on a single operating scenario and is often solved by single-objective optimization algorithms, a reactive power compensation configuration scheme considering multiple operating scenarios and multiple optimization objectives simultaneously was proposed. Considering the randomness of wind power output, typical wind power output scenarios were generated by the Monte Carlo sampling method and K -means clustering method. An optimal configuration model of reactive power compensation devices under multiple typical wind power output scenarios was established by taking system voltage deviation, active power loss, and configuration cost of reactive power compensation devices as optimization objectives, taking installation locations and compensation capacities of reactive power compensation devices as optimization variables, and setting power flow, node voltages, and power source outputs as constraints. At the same time, a multi-objective particle swarm optimization algorithm was used to solve the optimal configuration model to obtain the optimal installation locations and compensation capacities of reactive power compensation devices. The simulation analysis on the IEEE 39-node system with wind power shows that under multiple operating scenarios of the system, the proposed reactive power compensation configuration method can effectively reduce system voltage deviation and active power loss, and the configuration schemes are more diverse.