Ambient data-driven participation factors related to oscillation modes based on subspace dynamic mode decomposition

Analyzing the connection between the variables participating in the oscillation and modes in electromechanical oscillation is particularly important for maintaining system stability. This paper proposes an ambient data -driven method based on Subspace Dynamic Mode Decomposition (Sub-DMD) to extract the Participation Factors (PFs) related to system state and algebraic variables in electromechanical oscillation modes. This method uses ambient data to calculate the low -dimensional approximate matrix of the system, and the PFs is extracted by using eigen-decomposition and mode energy. Compare the extracted PFs with the results of power generation dispatch. The effectiveness of the proposed method is demonstrated by using simulation data from IEEE 4 -generator 2 -area test system and IEEE 16 -generator 68 -bus test system.