Coherence-based Oscillation Detection

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Presentation transcript:

Coherence-based Oscillation Detection Frank Tuffner, Jim Follum Electricity Infrastructure Group WECC JSIS Meeting – Salt Lake City, Utah September 10, 2014 PNNL-SA-105200

Spectral Coherence Analysis Primarily developed to detect sustained low signal-to-noise ratio oscillations in PMU data Periodogram-based analysis algorithm Useful to find: Periodic oscillations Forced responses Ringdown events Probing tests

Spectral Coherence Analysis Tool April 2013 Probing Test Brake Insertion Interesting Osc at 13 Hz Pseudo-random Probing

Current Research Basic MATLAB-based tool Detect events and flag the data Generate simplified report of interesting data intervals Data Integrity Situational Awareness Tool (DISAT) integration Statistical evaluations of coherence results with other metrics Detect abnormal conditions

Data Integrity Situational Awareness Tool Three main functions Read in & Clean Data Capture Features Identify Patterns and Unusual Events READS IN & STORES DATA: Raw PMU Data .dst or .pdat to .Rdata files GAS SCORE/ ATYPICALITY Use Cluster and Baseline to identify Atypical Events CALCULATE DATA SIGNATURES Capture mean and variability APPLY DATA QUALITY FILTER: Cleans & Removes Bad Data CLUSTER MEMBERSHIP Cluster data into 36 clusters based on StDev and Mean April 11, 2019

Future Work Examine DISAT Integration Expand to multichannel implementations April 11, 2019

Questions/Further Information For further information, please feel free to contact: Frank Tuffner francis.tuffner@pnnl.gov 206-528-3124 For information regarding DISAT, please contact Brett Amidan b.amidan@pnnl.gov 509-375-3692