Wideband oscillation poses a major challenge to the safe and stable operation of power systems with a high proportion of renewable energy. On the one hand

the “black-box” nature of control models of renewable energy power electronic equipment makes it difficult to accurately predict the oscillation characteristics of actual systems. On the other hand

the randomness of renewable energy unit outputs and the complexity of numerous operating conditions pose significant challenges for traditional stability analysis methods

leading to issues such as model mismatch and insufficient coverage of operating scenarios. As a result

it is neither possible to analyze potential oscillation modes through precise modeling nor to comprehensively explore oscillation risk scenarios with limited offline operating conditions

leaving renewable energy power systems exposed to high risks of wideband oscillation. To address these challenges

a methodology of online oscillatory stability assessment and weak point localization is proposed in this paper for large-scale renewable energy power systems. The methodology is based on a combined data and knowledge-driven approach

built upon the online identification of impedance or admittance of renewable energy units and stations. The access points of highly electrified power systems

such as renewable energy stations/clusters

energy storage stations

and flexible DC converter stations

are designated as potential oscillation risk nodes. At the potential oscillation risk nodes

the renewable energy power system is divided into renewable energy subsystems and a remaining subsystem. By calculating the real-time wideband impedance or admittance of these two subsystems

an online assessment of potential oscillation frequencies and stability margins is conducted for each potential oscillation risk node. When the system’s stability margin falls below the predefined threshold

the weak points are identified based on the online impedance identification data

thereby determining the vulnerable stations. Taking a local renewable energy power system in China as an example

the proposed method is utilized for conducting online evaluations of stability under various operating conditions

thereby verifying the accuracy of the proposed method.