Considering the traditional methods of voltage adjusting in distribution network reactive power optimization is discretized, and difficult to realize the continuous voltage adjustment, this paper studies the reactive power optimization model and algorithm in distribution network with wind farm. The limitation of reactive power capacity of doubly-fed induction generator is considered and the wind farm is taken as a continuous reactive power adjustment means to participate in the optimization. Scenario power is used to describe the random power of wind farm in respect to the random characteristic of wind power. The network loss, deviation of voltage and stability of voltage are included in the multi-objective reactive power optimization model. Reactive power optimization based on quantum particle swarm optimization(QPSO) is proposed. The algorithm describes particle state by wave function, which not only increases the diversity of population, but also avoids premature of population. The comparison of results between QPSO with PSO on the modified IEEE 33-bus system demonstrates the effectiveness and advantage of quantum particle swarm optimization model, which can achieve a better global optimal solution and shows a faster convergence speed.