FNETVision: A WAMS Big Data Knowledge Discovery System

被引:0
|
作者
Wang, Weikang [1 ]
Zhao, Jiecheng [1 ]
Yu, Wenpeng [1 ]
Liu, Yilu [1 ,2 ]
机构
[1] Univ Tennessee, Dept Elect Engn & Comp Sci, Knoxville, TN 37996 USA
[2] Oak Ridge Natl Lab, Oak Ridge, TN USA
来源
2018 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM) | 2018年
基金
美国国家科学基金会;
关键词
Frequency Disturbance Recorder (FDR); Big Data; Knowledge Discovery; Frequency Monitoring Network (FNET); Visualization;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
With the growing awareness of the power system stability, wide area measurement system (WAMS) has been widely studied and deployed. In WAMS, a phasor data concentrator (PDC) collects and persists the GPS-time-synchronized phasor data from hundreds of phasor measurement units (PMU). Due to the size and complexity of the modern power systems, the number of deployed PMUs has been increasing and their data size becomes increasingly large. The large data volume challenges the analysis, and the knowledge discovery of the measurement data. This paper takes the pioneering distribution level WAMS-the frequency monitoring network FNET/GridEye as an example. It develops an adaptive visualization system-FNETVision to visualize the large-volume WAMS data by interconnection. The case studies suggest, based on the FNETVision system, the system administrator can quickly dig out issues of the FNET system and accordingly pinpoint the cause of these issues.
引用
收藏
页数:5
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