Identification of Low-Frequency Oscillation Modes Using PMU Based Data-Driven Dynamic Mode Decomposition Algorithm

Power system inter-area oscillations curtail the power transferring capabilities of transmission lines in a large interconnected system. Accurate identification dominant modes and associated contributing generators is important to avoid failures by taking appropriate remedial measures. This paper proposes multi-channel Improved Dynamic Mode Decomposition (IDMD) algorithm-based modal analysis technique using Synchrophasors measurement. First, reduced-order dynamic model estimated this oscillation modes, corresponding shapes, damping ratio, coherent group generators, participation factors are determined. To improve accuracy data stacking used capture detailed information An optimal hard threshold utilized select most order uncertainties due presence high level measurement noise. The study results show that proposed algorithm gives an accurate robust solution even systems having noise data. performance tested on simulated from two-area four-machine wNAPS 41-bus 16-generator with PMU measurements corrupted different levels further strengthen viewpoint, method validated real-time ISO New England validate work.