Energy characteristic extraction and influencing factors identification of subsynchronouas oscillations based on WOA-VMD and principal component analysis

The new type power system includes generators with varying operation modes, control strategies and cluster combination methods, leading to distinct subsynchronous oscillation characteristics. Therefore, the extraction of energy characteristics of oscillation and the identification of influencing factors in various scenarios are key to solving subsynchronous oscillations in practical engineering. In this paper, a data-driven method based on improved Variational Mode Decomposition (VMD) and the principal component analysis combined with stepwise regression method for extracting energy characteristics is proposed. First, the optimal number of decomposition modes and penalty factors are determined based on the Whale Optimization Algorithm (WOA)-VMD method to address the modal confusion problem in the modal decomposition of operation data and extract the accurate subsynchronous modal signal; Next, the port-based expression of the energy function for subsynchronous oscillations is derived. Then, the principal component method is employed to solve the multi-collinearity problem between the influencing factors. Finally, the effectiveness of the proposed method is verified based on the Power Systems Computer Aided Design / Electromagnetic Transients including DC (PSCAD/EMTDC) simulation.