伴随分布式电源（distributed generation, DG）接入配电网，高渗透率DG导致的电压失稳，在考虑DG出力波动性和柔性负荷调度灵活性的同时，提出了一种配电网双层优化调度模型。在上层构建基于用户联合风光利益分配模型的补偿机制以改变用户用电行为。以提高电压质量为目标，提出一种计及需求侧响应的配电网动态有功-无功优化策略，先通过需求侧无功响应和无功装置补偿出力优化配电网电压波动，再对需求侧无功耦合的有功进行调度，最大程度平抑DG波动的同时降低网损，使配电网综合运行成本最小；在下层构建满意度模型，利用上层需求响应优化获得有功功率，将其作为下层用户满意度的决策变量，对用户满意度指标进行量化。在此基础上，针对模型特征，提出改进多目标灰狼算法生成Pareto最优调度策略。最后，以IEEE-33节点系统为例进行分析，验证了所提策略的有效性。

With distributed generation (DG) connected to the distribution network, in order to reduce voltage instability caused by high permeability DG, while considering the output fluctuation of DG and flexible load scheduling flexibility, a two-layer optimal dispatching model was proposed. A compensation mechanism based on the user's joint landscape benefit distribution model was constructed in the upper layer to change the user's consumption behavior, in order to improve the voltage quality as the goal. A dynamic active-reactive power optimization strategy of distribution network taking demand-side response into account was proposed. Firstly, the voltage fluctuation of distribution network was optimized by demand-side reactive response and reactive device compensation output, then the reactive power coupled active power was scheduled on the demand side to suppress DG fluctuation and reduce the network loss, the integrated operation cost of the distribution network was minimized. The satisfaction model was constructed in the lower-level, and the active power was obtained by the optimization of the upper-level demand response, which was used as the decision variable of the lower level user satisfaction, and the user satisfaction index was quantified. For the model features, an improved multi-objective gray wolf optimizer algorithm was proposed to generate Pareto optimal scheduling strategy. Finally, the IEEE-33 node system was taken as an example to verify the effectiveness of the proposed strategy.