Design and Implementation of a Data-Driven Approach to Visualizing Power Quality

Fei Xiao, Tianguang Lu, Qian Ai, Xiaolong Wang, Xinyu Chen, Sidun Fang, Qiuwei Wu

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Abstract

Numerous underlying causes of power-quality (PQ) disturbances have enhanced the application of situational awareness to power systems. This application provides an optimal overall response for contingencies. With measurement data acquired by a multi-source PQ monitoring system, we propose an interactive visualization tool for PQ disturbance data based on a geographic information system (GIS). This tool demonstrates the spatio–temporal distribution of the PQ disturbance events and the cross-correlation between PQ records and environmental factors, leveraging Getis statistics and random matrix theory. A methodology based on entity matching is also introduced to analyze the underlying causes of PQ disturbance events. Based on real-world data obtained from an actual power system, offline and online PQ data visualization scenarios are provided to verify the effectiveness and robustness of the proposed framework.
Original languageEnglish
JournalI E E E Transactions on Smart Grid
Number of pages14
ISSN1949-3053
DOIs
Publication statusAccepted/In press - 2020

Keywords

  • Situation awareness
  • Power quality
  • Geographic information system
  • Getis statistics
  • Random matrix theory
  • Entity matching

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