Abstract:With the access of large-scale charging facilities and the increasing refinement of related analysis and calculation, the original monitoring system can not adapt to the large-scale data processing requirements. Therefore, this paper proposes a collaborative control system of charging facilities based on cloud-edge collaboration. The characteristics of cloud-edge collaboration and the control requirements of charging facilities are combined. The functional positioning and interaction model of the cloud, edge and charging facilities are constructed. The cloud manages the edge and aggregation gateway uniformly. The cloud system receives the collected information and controls and schedules the analysis and calculation services of the control system. The edge system performs data acquisition and real-time control of distributed charging facilities. The cloud edge system manages server resources through Docker container technology. And a container deployment scheduling algorithm based on minimum change rate to achieve server load balancing and efficient use of resources is proposed. The proposed system realizes the effective allocation of resources under the pressure of big data communication, and meets the needs of power system data acquisition and multi-time scale control. Finally, the application effect of the proposed system is given, and the adaptability and efficiency of Docker container and its deployment scheduling algorithm in resource management are further verified by examples.