PMU Optimal Placement using sensitivity analysis for power systems fault location

P. Mohammadi, S. Mehraeen
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引用次数: 4

Abstract

This article presents a novel algorithm to find optimal sets of Phasor Measurement Units (PMUs) in power systems using measurement sensitivity analysis aiming for fault detection without multi-estimation. The algorithm generalizes the impedance method in fault detection through optimizing PMU utilization in order to detect a fault with desired precision in interconnected power systems. By deriving bus voltage and currents sensitivity indices to the fault location and impedance, possible deviations of the estimated fault location and/or impedance due to measurement noise, accuracy, precision limits, or simply the inability of a measurement point to sense a fault is evaluated. Therefore, the algorithm can solve Optimal PMU Placement (OPP) for desired fault detection precision based on these indices for various points of measurement observing faults in the system. Finally, avoiding multi-estimation guarantees the unique mapping between measurements of the selected PMU sets and faults throughout the system. The proposed algorithm is performed on the IEEE 7-bus and 14-bus benchmark systems and the fault location capability is evaluated through neural networks.
基于灵敏度分析的PMU优化配置在电力系统故障定位中的应用
本文提出了一种利用测量灵敏度分析寻找电力系统中最优相量测量单元集的新算法,目的是在不需要多重估计的情况下进行故障检测。该算法通过优化PMU的利用率,将阻抗法推广到故障检测中,从而在互联电力系统中达到所需的故障检测精度。通过推导母线电压和电流对故障位置和阻抗的灵敏度指数,评估由于测量噪声、精度、精度限制或测量点无法感知故障而估计的故障位置和/或阻抗的可能偏差。因此,该算法可以根据这些指标对系统中观测故障的各个测点求解出满足所需故障检测精度的最优PMU放置(OPP)。最后,避免多重估计保证了所选PMU组的测量值与整个系统的故障之间的唯一映射。在IEEE 7总线和14总线基准系统上对该算法进行了测试,并通过神经网络对其故障定位能力进行了评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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