随着插入式电动汽车和氢燃料电动车的快速发展，将混合能源补给站引入到微电网中是实现绿色低碳能源系统的重要方式。混合能源补给站是一种新型能源基础设施，其不仅可为插入式电动车充电，也可为氢燃料电动车补氢。当前对含混合能源补给站的微电网能源调度尚缺乏深入研究。由此，重点研究了多异构设备接入场景下含混合能源补给站的多微电网与虚拟电厂分布式能源调度问题。首先，构建混合能源补给站的精细化模型，提出一种基于云边协同的双层分布式能源调度框架，实现对电动车、储能设备和清洁能源等异构设备的优化调度，其中框架的上、下层分别考虑虚拟电厂和各微电网的能源优化调度。然后，运用基于目标级联法的分布式优化算法实现上、下层问题的解耦，进而实现虚拟电厂和各微电网的分散自治。最后，通过算例验证了所提出的云边协同方法在实现虚拟电厂和多微电网协同分布式层级优化的有效性。

With the rapid development of plug-in electric vehicles （PEVs） and hydrogen fuel vehicles （HFVs）, introducing hybrid energy supply stations （HESSs） into microgrids is an important way to realize a green and low-carbon energy system. A HESS is a new type of energy infrastructure that can not only charge PEVs, but also refill HFVs. Currently, there is a lack of in-depth research on energy scheduling for microgrids with HESSs. Thus, this paper focuses on the distributed energy scheduling problem of multi-microgrids and virtual power plants with HESSs under the scenario of massive heterogeneous device integration. Firstly, a refined model of the HESS is formulated, and a cloud-edge collaboration based two-layer distributed energy scheduling framework is proposed to achieve optimal scheduling of heterogeneous devices such as electric vehicles, energy storage, and renewable energy sources. The upper and lower layers of the framework respectively consider the optimal scheduling of energy for a virtual power plant and multi-microgrids. Then, an analytical target cascading （ATC）-based distributed optimization algorithm is employed to decouple the upper- and lower-layer problems, thereby achieving the decentralized autonomy of the virtual power plant and microgrids. Finally, the effectiveness of the proposed cloud-edge collaborative method in achieving distributed optimization of the virtual power plant and microgrids is verified through case studies.