The multivariate coupling and symmetry characteristic of a synchronous condenser and its excitation system (SCES) poses a challenge for parameter identification. This paper proposes a parameter identification approach for the SCES considering multivariate coupling and symmetry characteristics. The key parameters of the synchronous condenser under different time scales are selected. Then, the sensitivity analysis method is utilized to classify the parameters and establish the sets of coupling variables. In addition, the response mechanism and characteristics of the SCES under steady-state, sub-transient, and transient conditions are analyzed, based on which the parameter identification models are established separately. Moreover, the measurement data noise is processed by the wavelet threshold denoising method. According to the coupling variable sets, an improved snake optimization method based on Tent chaotic mapping is adopted for a solution. A case study is conducted to validate the effectiveness of the proposed approach. The results show that the proposed approach is able to improve the identification precisely and reduce the mode response error.