冷贵峰, 连欣乐, 黄佐林, 樊国盛, 王荣, 谭宇, 张荣华. 基于故障率和云平台的电网实时风险预警策略及实现[J]. 电力信息与通信技术, 2022, 20(2): 82-88. DOI: 10.16543/j.2095-641x.electric.power.ict.2022.02.012
引用本文: 冷贵峰, 连欣乐, 黄佐林, 樊国盛, 王荣, 谭宇, 张荣华. 基于故障率和云平台的电网实时风险预警策略及实现[J]. 电力信息与通信技术, 2022, 20(2): 82-88. DOI: 10.16543/j.2095-641x.electric.power.ict.2022.02.012
LENG Guifeng, LIAN Xinle, HUANG Zuolin, FAN Guosheng, WANG Rong, TAN Yu, ZHANG Ronghua. Power Grid Real-Time Risk Warning Strategy and Implementation Based on Failure Rate and Cloud Platform[J]. Electric Power Information and Communication Technology, 2022, 20(2): 82-88. DOI: 10.16543/j.2095-641x.electric.power.ict.2022.02.012
Citation: LENG Guifeng, LIAN Xinle, HUANG Zuolin, FAN Guosheng, WANG Rong, TAN Yu, ZHANG Ronghua. Power Grid Real-Time Risk Warning Strategy and Implementation Based on Failure Rate and Cloud Platform[J]. Electric Power Information and Communication Technology, 2022, 20(2): 82-88. DOI: 10.16543/j.2095-641x.electric.power.ict.2022.02.012

基于故障率和云平台的电网实时风险预警策略及实现

Power Grid Real-Time Risk Warning Strategy and Implementation Based on Failure Rate and Cloud Platform

  • 摘要: 风险预警是系统安全的关键,急需开发与当前大规模风险预警要求相适应的分析计算系统。文章提出了基于故障率和云平台的电网实时风险预警系统策略,从软件和硬件角度提高大规模风险预警的准确性和实时性,分析设备工况变化情况下的实时故障率,将高风险设备逐一进行N–1安全校核,构建实时预想事故集合,进而通过对预想事故的分析实现电网风险预警,并在基于Docker技术的云平台中实现。最后通过运行实例验证了该策略的有效性和快速性。

     

    Abstract: Risk early warning is the key to system security. To develop an analysis and calculation system is an urgent task to meet the requirements of current large-scale risk early warning. This paper proposes a strategy of power grid real-time risk early warning system based on failure rate and cloud platform, which improves the accuracy and real-time of large-scale risk early warning from the perspective of software and hardware. First, the real-time failure rate under the condition of equipment condition change is analyzed. The N–1 security checks for high-risk equipment are calculated one by one. Then a real-time contingency set are constructed. The power grid risk warning is realized through the analysis of contingency. And it is implemented in the cloud platform based on Docker technology. Finally, an example is given to verify the effectiveness and rapidity of the strategy.

     

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