FNETVision: A WAMS Big Data Knowledge Discovery System

Conference · Wed Aug 01 00:00:00 EDT 2018

DOI:https://doi.org/10.1109/PESGM.2018.8586284· OSTI ID:1564166

Wang, Weikang ^[1]; Zhao, Jiecheng ^[2]; Yu, Wenpeng ^[1]; Liu, Yilu ^[3]

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1. The University of Tennessee, Knoxville
2. University of Tennessee (UT)
3. ORNL

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.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1564166
• Country of Publication: United States
• Language: English