大规模电力系统暂态稳定域估计 第Ⅰ部分：Koopman算子与降阶模型

This paper presents an estimation of transient stability regions for large-scale power systems.In Part Ⅰ,a Koopman operator based model reduction(KOMR)method is proposed to derive a low-order dynamical model with reasonable accuracy for transient stability analysis of large-scale power systems.Unlike traditional reduction methods based on linearized models,the proposed method does not require linearization,but captures dominant modes of the original nonlinear dynamics by employing a Koopman operator defined in an infinite-dimensional observable space.Combined with the Galerkin projection,the obtained dominant Koopman eigenvalues and modes produce a reduced-order nonlinear model.To approximate the Koopman operator with sufficient accuracy,we introduce a Polynomial-based Multi-trajectory Kernel Dynamic Mode Decomposition(PMK-DMD)algorithm,which outperforms traditional DMD in various scenarios.In the end,the proposed method is applied to the IEEE 10-machine-39-bus power system and IEEE 16-machine-68-bus power system,which demonstrates that our method is significantly superior to the modal analysis method in both qualitative and quantitative aspects.