Waveform Measurement Unit-Based Fault Location in Distribution Feeders via Short-Time Matrix Pencil Method and Graph Neural Network
Waveform Measurement Unit-Based Fault Location in Distribution Feeders via Short-Time Matrix Pencil Method and Graph Neural Network
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DOI：
10.1109/tia.2022.3231586
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发表时间：
2023-03
影响因子：
4.4
通讯作者：
Mohammad MansourLakouraj;Hadi Hosseinpour;H. Livani;M. Benidris
中科院分区：
文献类型：
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作者：
Mohammad MansourLakouraj;Hadi Hosseinpour;H. Livani;M. Benidris
本文提出了一种基于新兴的传感器（称为波形测量单元（WMU））的有源配电馈线故障定位的短时矩阵重构方法（STMPM）和图形神经网络（GNN）。WMU以高采样率在时域中记录同步的电压和电流波形。建议的故障定位框架包括两个阶段。在第一阶段中，STMPM被用来捕获由于配电网的不同位置的故障引起的WMU的正弦信号的瞬态变化的主导模式。第二阶段是使用网格通知的GNN模型，使用STMPM在故障前、故障期间和故障后捕获的信号特征来识别故障位置和类型。GNN可以捕获来自不同位置的不同传感器的数据之间的时空关系，以增强态势感知和故障定位精度。该方法是检查修改后的IEEE网络与分布式能源（DER）和不同的负载下的瞬态对称和不对称故障，DER发电水平，噪声，和传感器的采样率条件。结果表明，所提出的两阶段的故障定位框架相比，传统的方法的优点，而一个具有挑战性的问题是解决主动配电网。
This article proposes the use of the Short-Time Matrix Pencil method (STMPM) and Graph Neural Network (GNN) for fault location in active distribution feeders based on an emerging class of sensors, known as Waveform Measurement Units (WMUs). WMUs record synchronized voltage and current waveforms in the time domain with high sampling rates. The proposed fault location framework consists of two stages. In the first stage, STMPM is adopted to capture the dominant modes of the transient changes of WMUs' sinusoidal signals due to faults in different locations of the distribution grid. The second stage is to use a grid-informed GNN model to identify the fault location and type using the captured features of the signal before, during, and post-fault with STMPM. GNN can capture the spatial-temporal relationship between data from different sensors in different locations to enhance situational awareness and fault location accuracy. The proposed method is examined on a modified IEEE network with distributed energy resource (DER) and for transient symmetrical and asymmetrical faults under different loading, DER generation level, noises, and sensors' sampling rate conditions. The results show the merits of the proposed two-stage fault location framework compared to the conventional approaches; while a challenging problem is addressed in active distribution grids.