Small-signal stability assessment of renewable energy systems: an automatic linearization framework based on user-defined models

With the increasing penetration of renewable energy sources into power systems, their impact on system stability has become increasingly prominent, leading to the emergence of new oscillation modes and substantial changes in small-signal stability characteristics. However, the diversity of renewable energy equipment manufacturers and their control strategies poses significant challenges in accurately simulating the dynamic characteristics through conventional simulation models, thereby limiting precise oscillation mode analysis. This paper presents an automatic linearization method for dynamic simulation models based on a User-Defined Model (UDM), enabling efficient linearization of customized dynamic models independent of traditional generic simulation models. Additionally, an automatic stitching algorithm for the dynamic model linearization matrix and the admittance matrix of the system network is proposed, coupled with implicit restart Arnoldi method, to precisely determine critical oscillation modes in power systems. A UDM-based wind turbine model is developed to validate the proposed approach, and a detailed small-signal stability analysis is performed, successfully identifying wind turbine-associated oscillation modes. The results demonstrate that the proposed method effectively captures oscillatory characteristics induced by renewable energy integration. This approach provides technical guidance for oscillation mode analysis, control system design, and parameter optimization in power systems with high renewable energy penetration.