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

2. 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

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

4. 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

5. 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
January 12, 2019

6. Future Work Examine DISAT Integration
Expand to multichannel implementations
January 12, 2019

7. Questions/Further Information
For further information, please feel free to contact:
Frank Tuffner
For information regarding DISAT, please contact
Brett Amidan