Practical Event Location Estimation Algorithm for Power Transmission System Based on Triangulation and Oscillation Intensity

作     者：Liu, Shengyuan Sun, Kaiqi Zeng, Chujie You, Shutang Li, Hongyu Yu, Wenpeng Deng, Xianda Lin, Zhenzhi Liu, Yilu 

作者机构：Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN 37996 USA Zhejiang Univ Sch Elect Engn Hangzhou 310027 Peoples R China Shandong Univ Sch Elect Engn Jinan 250061 Peoples R China Oak Ridge Natl Lab Oak Ridge TN 37830 USA 

出 版 物：《IEEE TRANSACTIONS ON POWER DELIVERY》 (IEEE Trans Power Delivery)

年 卷 期：2022年第37卷第6期

页      面：5190-5202页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 

基　　金：NSF Cyber-Physical Systems (CPS) Program Engineering Research Center Program of the National Science Foundation Department of Energy under NSF [EEC-1041877] CURENT Industry Partnership Program 

主　　题：Event location estimation wave arrival time convolutional neural network (CNN) oscillation intensity triangulation synchrophasor measurement FNET/GridEye frequency disturbance recorder (FDR) 

摘      要：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.