陈亚鹏, 于子淇, 谢文正, 杨阳, 周振宇, 刘春秀. 电网光通信系统双向运行风险关联分析技术[J]. 电力信息与通信技术, 2024, 22(10): 32-37. DOI: 10.16543/j.2095-641x.electric.power.ict.2024.10.05
引用本文: 陈亚鹏, 于子淇, 谢文正, 杨阳, 周振宇, 刘春秀. 电网光通信系统双向运行风险关联分析技术[J]. 电力信息与通信技术, 2024, 22(10): 32-37. DOI: 10.16543/j.2095-641x.electric.power.ict.2024.10.05
CHEN Yapeng, YU Ziqi, XIE Wenzheng, YANG Yang, ZHOU Zhenyu, LIU Chunxiu. Bidirectional Operation Risk Correlation Analysis Technology for Power Grid Optical Communication System[J]. Electric Power Information and Communication Technology, 2024, 22(10): 32-37. DOI: 10.16543/j.2095-641x.electric.power.ict.2024.10.05
Citation: CHEN Yapeng, YU Ziqi, XIE Wenzheng, YANG Yang, ZHOU Zhenyu, LIU Chunxiu. Bidirectional Operation Risk Correlation Analysis Technology for Power Grid Optical Communication System[J]. Electric Power Information and Communication Technology, 2024, 22(10): 32-37. DOI: 10.16543/j.2095-641x.electric.power.ict.2024.10.05

电网光通信系统双向运行风险关联分析技术

Bidirectional Operation Risk Correlation Analysis Technology for Power Grid Optical Communication System

  • 摘要: 面向电网通信业务的高可靠传输与处理需求,针对多源风险隐患数据融合处理问题,文章提出一种电网光通信系统双向运行风险关联分析技术。首先,构建基于数字孪生的电网光通信系统风险隐患数据处理分析架构,实现TMS2.0与数字孪生的统一集成。进一步提出风险隐患数据预处理及关联分析技术,实现异常数据的剔除与多系统来源风险隐患数据的融合处理。仿真结果表明,所提技术可有效提升风险隐患数据分析速度与精度,为电网安全稳定运行提供支撑。

     

    Abstract: Aiming at the high reliability transmission and processing requirements of power grid communication ser-vices, a bidirectional operation risk correlation analysis technology for power grid optical communication system is proposed to address the problem of multi-source risk and hidden danger data fusion processing. Firstly, the data processing and analysis framework of potential risks in power grid optical communication system based on digital twinning is constructed to realize the unified integration of TMS2.0 and digital twinning. Furthermore, the technology of risk hidden data preprocessing and correlation analysis is put for-ward to realize the elimination of abnormal data and the fusion of risk hidden data from multiple systems. The simulation results show that the proposed technology can effectively improve the speed and accuracy of data analysis of potential risks and provide support for the safe and stable operation of power grid.

     

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