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Improving the wide-area PMU-based fault location method using ordinary least squares estimation

机译:使用普通最小二乘估计改进基于广域的PMU的故障定位方法

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This paper presents an approach which allows system-wide fault location using only a sparse set of synchronized phasor measurements. The proposed algorithm combines post-fault voltage prediction and sparse estimation. The resulting method enables practical application of the sparse estimation formulation by using Prony analysis to predict post-fault steady-state voltages at those buses equipped with phasor measurement units. The prediction requires only a short transient recording which is typically available before the actuation of protective relays. Following the prediction step, the least angle regression based sparse estimation algorithm is employed to identify the fault location. However, for particular conditions usually associated with small fault currents, the sparse estimation algorithm may not be able to correctly identify the fault location. To mitigate this problem, ordinary least squares is used to increase the robustness of the proposed method. A 3-Phase model of the IEEE 118 bus system is developed on the alternative transients program to simulate realistic fault transients and test the performance and accuracy of the proposed fault location method.
机译:本文介绍了一种方法,该方法仅使用稀疏的同步相位测量集进行系统宽故障位置。该算法结合了故障后电压预测和稀疏估计。通过使用Proy分析来实现稀疏估计配方的实际应用,以预测配备相像测量单元的那些总线的故障后稳态电压。预测仅需要短暂的瞬态记录,该短瞬态记录通常可在保护继电器致动之前获得。在预测步骤之后,采用基于角度回归的基于角度回归估计算法来识别故障位置。然而,对于通常与小故障电流相关联的特定条件,稀疏估计算法可能无法正确识别故障位置。为了缓解这个问题,使用普通的最小二乘来增加所提出的方法的鲁棒性。 IEEE 118总线系统的3阶段模型是在替代瞬态程序开发的,以模拟现实故障瞬变并测试所提出的故障定位方法的性能和准确性。

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