在新型能源与配电网协调发展的背景下，针对分布式储能的优化配置问题，提出了一种混合储能双层优化配置模型。通过上层优化确定储能接入位置和容量，并通过傅里叶变换对功率进行分频，利用超级电容器和蓄电池分别承担不同频率部分的功率。下层优化以低储高放效益为目标函数，通过结合Pareto档案的粒子群算法进行优化。通过IEEE33节点的仿真实验，验证了该模型的可行性。结果表明：该模型能够实现多目标综合优化，包括降低网络损耗、优化电能指标和降低储能设备投资成本，为配电网接入分布式储能的优化配置提供了有效的解决方案。

In the context of the coordinated development of new energy sources and distribution networks, a hybrid energy storage two-layer optimal configuration model was proposed for the optimal configuration of distributed energy storage connected to distribution networks. The upper layer optimization determined the energy storage access location and capacity, and divided the power by Fourier transform, using super capacitor and battery to bear the power of different frequency parts respectively. The lower layer optimization was designed with the objective function of maximizing the benefits from low storage and high discharge operations. It was optimized using a combination of the particle swarm algorithm and the Pareto file. The model's rationality and effectiveness were confirmed through simulation experiments conducted on the IEEE33 nodes network. The results show that the model can achieve multi-objective comprehensive optimization, including reducing network losses, optimizing power index and reducing investment costs of energy storage equipment, which provides an effective solution for the optimal configuration of distributed energy storage connected to distribution networks.