基于云边协同的充电设施协调控制系统设计
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1.中国南方电网有限责任公司;2.南京南瑞继保电气有限公司

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南方电网公司科技项目:基于云边融合的智能调度运行平台理论、框架、标准体系及平台关键技术研究(000000KK52200035)。
Foundation item: Supported by the? Science and? Technical Projects of China Southern Power Grid:Research on Theory, Framework, Standard System and Key Technologies of Smart Dispatch Platform Based on Cloud Edge (000000KK52200035) .


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    摘要:

    随着大规模充电设施的接入及其相关分析计算的日益精细化,原有的监控系统无法适应相应的大规模数据处理需求,因此本文提出基于云边协同的充电设施协调控制系统,结合云边协同特点和充电设施控制需求,构建了云端、边缘、充电设施聚合网关功能定位及交互模型,云端对边缘、聚合网关进行统一管理,接收采集信息并对控制系统分析计算服务进行管控和调度,边缘对分布式充电设施进行数据采集和实时控制;云边系统通过Docker容器技术实现服务器资源进行管理,并提出了基于最小变化率的容器部署调度算法实现服务器负载均衡以及资源的高效利用;所提系统实现了大数据通信压力下资源的有效分配,满足电力系统数据采集和多时间尺度控制的需求。最后给出所提系统的应用效果,进一步通过实例验证了Docker容器及其部署调度算法在资源管理方面的适应性和高效性。

    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.

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李映辰,何宇斌,何锡祺,许丹莉,陈州.基于云边协同的充电设施协调控制系统设计计算机测量与控制[J].,2024,32(6):111-117.

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  • 收稿日期:2023-06-12
  • 最后修改日期:2023-07-20
  • 录用日期:2023-07-24
  • 在线发布日期: 2024-06-18
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