Fault location algorithms for transmission lines use the parameters of the transmission line to locate faults after the faults have occurred along the line. Although these parameters can be estimated by the phasor measurement units (PMUs) at the terminal(s) of the transmission line continuously, the uncertainty in the measurements will give rise to stochastic errors in the measured values. Thus, the uncertainty in measurements definitely influences the estimations of the parameters of the transmission line, which, in turn, influences the results of fault location algorithms. Inaccurate results of fault location algorithms may lead to costly maintenance fees and prolonged outage time. Therefore, in this article, we estimate the parameters of the transmission line considering the uncertainty in the measurements so that a more accurate fault location can be derived. The uncertainty in the measurements will be modeled as a stochastic distribution, and the maximum likelihood estimation (MLE) method will be adopted to reduce the uncertainty in the measurements. In addition, as an illustration, the telegrapher’s equations will be used to calculate the parameters of the transmission line, and the two-terminal positive sequence network fault location algorithm will be used to locate the fault. In a simulation, a case study of a real-life transmission line the influence of the uncertainty in the measurements on the transmission line parameter estimations and the effectiveness of the MLE method for estimations are simulated and analyzed. The results show that the influence of the uncertainty in the measurements on the positive sequence network fault location algorithm should not be neglected and that the proposed method is very effective in significantly reducing the influence of the uncertainty in the measurements. Note to Practitioners —The objective of this article is to address the significant effects of inaccuracies in the measurements for fault location determination in transmission lines in power systems. These inaccuracies increase the cost and duration of the search process for the actual fault location, and they, thus, also enlarge the outage duration and reduce the power system reliability. This article aims to analyze and reduce the influence of the uncertainties in the measurements in order to obtain a much more accurate fault location estimate when a fault has occurred along the transmission line. One of the key contributions of this article is the development of a model for the uncertainties in the measurements based on a confidence level and deviation bounds; this model can then be used if the information on the distributions of the uncertainties in the measurements is not available. Another key contribution is a maximum likelihood estimation method to estimate line parameters more accurately and consequently to reduce the influence of the uncertainties in the measurements on the fault location estimate.

中文翻译：

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测量不确定度对传输线参数估计和故障位置的影响

传输线的故障定位算法在沿线路发生故障之后，使用传输线的参数来定位故障。尽管这些参数可以由传输线末端的相量测量单元（PMU）连续估算，但是测量中的不确定性将导致测量值中的随机误差。因此，测量中的不确定性无疑会影响传输线参数的估计，进而影响故障定位算法的结果。故障定位算法的不正确结果可能导致昂贵的维护费用和延长的停机时间。因此，在本文中，考虑到测量中的不确定性，我们估计传输线的参数，以便可以得出更准确的故障位置。测量中的不确定性将被建模为随机分布，并且将采用最大似然估计（MLE）方法来减少测量中的不确定性。另外，作为说明，将使用电报员方程式来计算传输线的参数，并使用两端正序网络故障定位算法来定位故障。在仿真中，模拟并分析了一个现实生活中的传输线的案例，分析了测量不确定性对传输线参数估计的影响以及MLE方法进行估计的有效性。执业者注意 —本文的目的是解决电力系统传输线中故障位置确定的测量中的不精确性的重大影响。这些不准确性增加了针对实际故障位置的搜索过程的成本和持续时间，因此也增加了停电时间并降低了电力系统的可靠性。本文旨在分析并减少测量中不确定性的影响，以便在沿传输线发生故障时获得更准确的故障位置估计。本文的主要贡献之一是根据置信度和偏差范围开发了测量不确定性模型。如果无法获得有关测量中不确定性分布的信息，则可以使用此模型。另一个主要贡献是最大似然估计方法，该方法可以更准确地估计线路参数，从而减少测量中的不确定性对故障位置估计的影响。