针对含风电场电力系统多目标无功优化的应用需求及优化算法存在局部易收敛和全局性搜索能力差的问题，提出一种应用于多目标无功优化的矢量烟花算法。首先，改变烟花算法爆炸方式，并将烟花爆炸的维度进行关联，避免迭代过程中陷入局部最优解，增强算法全局搜索能力；其次，引入新型拥挤度选择策略以加快算法的收敛速度；最后，建立有功网损和电压偏差最小的含风电场电力系统多目标无功优化模型，并以风电场接入IEEE 14节点电力网络为算例进行模型求解。结果表明：所提算法避免了局部易收敛问题，增强了算法全局搜索能力，能在不同优化要求下得到有效的无功优化方案。

In response to the application demand for multi-objective reactive power optimization in power systems containing wind farms and the issues of local easy convergence and poor global search ability of optimization algorithms, a vector fireworks algorithm is proposed for multi-objective reactive power optimization. Firstly, the explosion method of the fireworks algorithm is modified, and the dimensions of the fireworks explosion are correlated to avoid falling into a local optimal solution during the iteration process and to enhance the global search capability of the algorithm. Secondly, a novel congestion selection strategy is introduced to accelerate the convergence speed of the algorithm. Lastly, a multi-objective reactive power optimization model for power systems containing wind farms is established, with the objectives of minimizing active network loss and voltage deviation. The model is solved as an example of an IEEE 14-node power network with a wind farm. The results indicate that the proposed algorithm mitigates the issue of local convergence, enhances the global search capability of the algorithm, and can obtain effective reactive power optimization solutions under different optimization requirements.