Randomized Dynamic Mode Decomposition for Oscillation Modal Analysis

Alassaf, Abdullah; Fan, Lingling

doi:10.1109/tpwrs.2020.3012419

Randomized Dynamic Mode Decomposition for Oscillation Modal Analysis

Journal Article · Tue Jul 28 00:00:00 EDT 2020 · IEEE Transactions on Power Systems

DOI:https://doi.org/10.1109/tpwrs.2020.3012419· OSTI ID:2202807

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University of Hail (Saudi Arabia); University of South Florida, Tampa, FL (United States); University of South Florida
University of South Florida, Tampa, FL (United States)

The objective of this research is to identify oscillation modes from real-world measurement data captured by phasor measurement units (PMUs) and make distinction of their characteristics. To this end, dynamic mode decomposition (DMD) is applied. This paper improves DMD performance by data stacking. This enables DMD to accurately identify system eigenvalues and reconstruct signals in the time-evolving format. While data stacking raises the computation cost, we further implement a randomization technique for DMD to radically reduce the size of the data matrix. The randomized DMD (rDMD) is shown to achieve both efficiency in computing and accuracy in mode identification. Furthermore, PMU data from three real-world oscillation events are used for demonstration.

View Accepted Manuscript (DOE)

Research Organization:: University of South Florida, Tampa, FL (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: EE0008771

OSTI ID:: 2202807

Alternate ID(s):: OSTI ID: 1848881

Journal Information:: IEEE Transactions on Power Systems, Journal Name: IEEE Transactions on Power Systems Journal Issue: 2 Vol. 36; ISSN 0885-8950

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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42 ENGINEERING
Power system oscillations
dynamic mode decomposition
randomized technique
real-world event
system identification

Randomized Dynamic Mode Decomposition for Oscillation Modal Analysis

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