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Performance analysis of MMF-based transmission network fault diagnosis via randomized hybrid simulations

机译:基于MMF的传输网络故障诊断性能的随机混合仿真分析

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In this paper, a hybrid simulation study is carried out on the 68-bus 16-machine test system to assess the performance of a recently developed fault diagnosis scheme using multiple-model filters (MMF) built on partitioned electric network models. Our main interest lies with the effectiveness of a secondary protection system, in which diagnosis plays a key role in enabling reliable and timely recovery from misoperations in the conventional primary protection. The hybrid simulation involves both event - driven and time - driven dynamics with arrivals of transmission short-circuit faults as independent Poisson processes among transmission lines and the fault location uniformly distributed along the short-circuited line. This paper reports only on the dependability enhancement through the diagnosis scheme, which is measured by the probability of successful fault diagnosis by the secondary protection given that the primary protection has failed to diagnose the fault.
机译:在本文中,在68总线16机测试系统上进行了混合仿真研究,以使用基于分区电网模型的多模型滤波器(MMF)评估最近开发的故障诊断方案的性能。我们的主要兴趣在于二级保护系统的有效性,在该系统中,诊断在确保可靠,及时地从常规一级保护中的误操作中恢复起着关键作用。混合仿真涉及事件驱动和时间驱动的动力学,其中传输短路故障的到来是传输线之间的独立泊松过程,并且故障位置沿着短路线均匀分布。本文仅报告了通过诊断方案增强的可靠性,这是通过在主保护未能诊断出故障的情况下通过二级保护成功诊断故障的概率来衡量的。

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