This paper studies reactive power optimization in distribution network connected with wind farm, which contains doubly-fed induction generators. Considering the random output of DFIG, it’s difficult to dispose reactive power optimization by the traditional model. As a result, the scenario analysis method is adopted to deal with this problem. The scenario model is established for reactive power optimization of distribution network with DFIG. Considering the flexible reactive power regulation capability of DFIG, a model for fuzzy reactive power optimization model is presented with a comprehensive objective function of reducing the network loss and restricting node voltage variations of distribution network. The location of reactive power compensation device for distribution network is determined by Monte Carlo simulation. Quantum particle swarm optimization is used to solve reactive power optimization in distribution network with DFIG. Finally, the IEEE 33-bus system is used as a test case to simulate the model of reactive power optimization presented by this paper. Simulation results show that the active power loss of distribution network is reduced significantly, and its voltage profile is also improved. It proves that the proposed method in the paper is feasible and effective.