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首页> 外文期刊>IET Smart Grid >Data-driven online distributed disturbance location for large-scale power grids
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Data-driven online distributed disturbance location for large-scale power grids

机译：数据驱动的在线分布式干扰位置，用于大型电网

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Timely detecting disturbances and locating their sources are critical to the reliable operation of power grids. This capability enables operators to effectively diagnose disturbances over wide areas and earns time for remedial reactions. In this study, a travelling-wave based scheme, namely data-driven online distributed disturbance location (DODDL), is proposed to quickly detect disturbances and determine their geographic location in large-scale power grids when the grids' topology is not available. The proposed DODDL scheme consists of two function blocks: (i) a singular spectrum analysis-based change-point detection method, which can quickly detect disturbances and determine their arrival time at distributed sensors, and (ii) a novel temporal scanning algorithm, which can accurately determine the geographic location of the disturbance source point. Utilising field measurement data sets recorded by the frequency disturbance recorders from the frequency monitoring network, it is shown that the DODDL scheme is not only quicker and more robust to grid non-homogeneity than existing approaches, but also can capture and locate more subtle and concealed disturbances.
机译：及时检测干扰和定位它们的来源对于电网可靠运行至关重要。这种能力使运营商能够在广泛的区域上有效地诊断干扰并获得补救反应的时间。在该研究中，提出了一种基于行波基的方案，即数据驱动的在线分布式干扰位置（DoDDL），以便在网格的拓扑不可用时快速检测干扰并确定其在大规模电网中的地理位置。所提出的DoDDL方案包括两个功能块：（i）基于奇异的频谱分析的变化点检测方法，可以快速检测干扰并确定其在分布式传感器处的到达时间，以及（ii）一种新的时间扫描算法，它可以准确地确定干扰源点的地理位置。利用来自频率监测网络的频率干扰记录器记录的现场测量数据集，显示DODDL方案不仅比现有方法更快，而且对网格非同质性更快，而且可以捕获和定位更微妙和隐藏干扰。

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