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基于云邊協(xié)同的充電設施協(xié)調控制系統設計
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1.中國南方電網(wǎng)有限責任公司;2.南京南瑞繼保電氣有限公司

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南方電網(wǎng)公司科技項目:基于云邊融合的智能調度運行平臺理論、框架、標準體系及平臺關(guān)鍵技術(shù)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:

    隨著(zhù)大規模充電設施的接入及其相關(guān)分析計算的日益精細化,原有的監控系統無(wú)法適應相應的大規模數據處理需求,因此本文提出基于云邊協(xié)同的充電設施協(xié)調控制系統,結合云邊協(xié)同特點(diǎn)和充電設施控制需求,構建了云端、邊緣、充電設施聚合網(wǎng)關(guān)功能定位及交互模型,云端對邊緣、聚合網(wǎng)關(guān)進(jìn)行統一管理,接收采集信息并對控制系統分析計算服務(wù)進(jìn)行管控和調度,邊緣對分布式充電設施進(jìn)行數據采集和實(shí)時(shí)控制;云邊系統通過(guò)Docker容器技術(shù)實(shí)現服務(wù)器資源進(jìn)行管理,并提出了基于最小變化率的容器部署調度算法實(shí)現服務(wù)器負載均衡以及資源的高效利用;所提系統實(shí)現了大數據通信壓力下資源的有效分配,滿(mǎn)足電力系統數據采集和多時(shí)間尺度控制的需求。最后給出所提系統的應用效果,進(jìn)一步通過(guò)實(shí)例驗證了Docker容器及其部署調度算法在資源管理方面的適應性和高效性。

    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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引用本文

李映辰,何宇斌,何錫祺,許丹莉,陳州.基于云邊協(xié)同的充電設施協(xié)調控制系統設計計算機測量與控制[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
  • 錄用日期:2023-07-24
  • 在線(xiàn)發(fā)布日期: 2024-06-18
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