Improved Oscillation Detection for Alarming and Daily Summary Reports

PI:

Project Status:

Completed

This project is enhancing a spectral coherence algorithm to improve the detection of persistent oscillations in the power system in a manner that will provide better information on the characteristics of these oscillations to the end user. This phase of work will refine the approach by investigating new algorithms for the oscillation detection within the DISAT framework, as well as further investigating the use of the statistical quantities to aid in alarming.

Related Publications

Follum, Jim, and Francis K Tuffner. Forced Oscillation Detection and Analysis with the DISAT Application. Pacific Northwest National Laboratory, 2016.

Related Files

PDF (2.03 MB)

Zhou, Ning, and Jeffery E Dagle. "Initial Results in Using a Self-Coherence Method for Detecting Sustained Oscillations." IEEE Transactions on Power Systems 30.1 (2015) 522 - 530.

Follum, Jim, Francis K Tuffner, and Brett G Amidan. Integration of a Self-Coherence Algorithm into DISAT for Forced Oscillation Detection. Pacific Northwest National Laboratory, 2015.