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.
- Situation awareness
- Power quality
- Geographic information system
- Getis statistics
- Random matrix theory
- Entity matching
Xiao, F., Lu, T., Ai, Q., Wang, X., Chen, X., Fang, S., & Wu, Q. (Accepted/In press). Design and Implementation of a Data-Driven Approach to Visualizing Power Quality. I E E E Transactions on Smart Grid. https://doi.org/10.1109/TSG.2020.2985767