With the continuous advancement of China’s new-type power system construction, wide-range-frequency oscillation accidents in the power grid have become frequent, characterized by multiple modal components and a wide frequency range. Due to the nonlinearity and coupled time-varying characteristic of wide-range-frequency oscillations, it is difficult to accurately identify parameters. Therefore, this paper proposes an improved particle swarm optimization (PSO)–variational mode decomposition (VMD) method for identifying wide-range-frequency oscillations. First, through improved PSO, the number of modal and secondary penalty factors of the VMD are self-optimized. Energy loss is used as the fitness function, and optimum is achieved through dynamic adjustment of the inertial factor of the particle swarm algorithm. Second, the wide-range-frequency oscillation signal undergoes VMD based on the number of obtained modals and the secondary penalty factor. The effective and noisy modal components are separated using the correlation coefficient approach, and signal reconstruction is utilized to reduce noise. Finally, simulation examples were used to verify the feasibility and effectiveness of the method proposed in this paper. Simulation results demonstrate that the proposed method can capture all wide-band-frequency oscillation information of the signal with an identification error below 2%. It provides a theoretical basis and technical support for wide-band-frequency oscillation traceability and mitigation.