Practical Event Location Estimation Algorithm for Power Transmission System Based on Triangulation and Oscillation Intensity
Practical Event Location Estimation Algorithm for Power Transmission System Based on Triangulation and Oscillation Intensity
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DOI：
10.1109/tpwrd.2022.3173974
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发表时间：
2022-12
影响因子：
4.4
通讯作者：
Shengyuan Liu;Kaiqi Sun;Chujie Zeng;Shutang You;Hongyu Li;Wenpeng Yu;Xianda Deng;Zhenzhi Lin;Yilu Liu
中科院分区：
文献类型：
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作者：
Shengyuan Liu;Kaiqi Sun;Chujie Zeng;Shutang You;Hongyu Li;Wenpeng Yu;Xianda Deng;Zhenzhi Lin;Yilu Liu
电力系统中的事件定位是系统运行人员提高控制室态势感知能力的重要信息。因此，研究一种高精度的输电系统事件位置估计算法具有重要意义。随着广域测量系统（WAMS）如FNET/GridEye和同步相量测量设备（SMD）如频率扰动记录器（FDR）的发展，可以采集包括频率、电压幅值和相角在内的同步测量数据并用于事件定位。首先，相位角和频率变化率（RoCoF）轨迹分别用于确定与每个FDR相关联的两组波到达时间。然后，利用卷积神经网络（CNN）来确定波到达顺序，以针对给定情况选择更合适的波到达时间集合，并执行相应的修改。接下来，基于惯性中心（COI）坐标系中的相位角轨迹来确定与每个FDR相关联的振荡强度。最后，事件位置估计的多个标准。通过对美国电力系统中的实际算例和已证实算例的分析，验证了所提算法在实际应用中的有效性和改进性。
Event location in power systems is quite essential information for system operators to enhance control-room situational awareness capability. Therefore, it is of great importance to develop an event location estimation algorithm for transmission systems with high accuracy. With the development of wide-area measurement system (WAMS) such as FNET/GridEye, and the synchrophasor measurement devices (SMDs) such as frequency disturbance recorders (FDRs), the synchronous measurement data including frequency, voltage amplitude and phase angle can be collected and used for event location estimation. First, the phase angle and rate of change of frequency (RoCoF) trajectories are respectively used for determining two sets of wave arrival time associated with each FDR. Then, a convolutional neural network (CNN) is utilized to determine the wave arrival order to select the more suitable set of wave arrival times for a given case and to perform corresponding modifications. Next, the oscillation intensity associated with each FDR is determined based on phase angle trajectories in the center of inertia (COI) coordinate system. Finally, the multiple criteria for event location estimation are represented. Case studies and comparisons between the proposed and previous algorithms using actual and confirmed cases in U.S. power systems are performed to demonstrate the effectiveness and improvement of the proposed algorithm in practical applications.