PMU Tracker: A Visualization Platform for Epicentric Event Propagation Analysis in the Power Grid

Area of Science:

• Electrical Engineering
• Computer Science
• Data Visualization

Background:

• The electrical power grid is critical infrastructure, vulnerable to disruptions.
• Smart grid technologies, including phasor measurement units (PMUs), offer real-time monitoring but generate large volumes of noisy data.
• Analyzing grid events like oscillations and load fluctuations is challenging due to data complexity.

Purpose of the Study:

• To address the challenge of analyzing large, noisy datasets from PMUs in smart grids.
• To develop a visual analytics tool for power grid operators to identify and track grid events.
• To introduce a novel visualization technique for analyzing event propagation.

Main Methods:

• Developed PMU Tracker, a visual analytics tool for power grid event analysis.
• Created an epicentric cluster dendrogram visualization technique.
• Validated the tool with a usage scenario and case studies involving power grid operators and real-world data.

Main Results:

• PMU Tracker effectively supports power grid operators in analyzing anomalous grid events.
• The epicentric cluster dendrogram aids in understanding event propagation from a source.
• The visual analytics approach is applicable to other domains with time-varying networks and epicentric events.

Conclusions:

• PMU Tracker enhances the ability to analyze power grid events by providing visual insights.
• The developed visualization technique offers a novel approach to understanding event dynamics.
• The visual analytics framework has broader applicability beyond power grid monitoring.