Faced with the tight coupling of multi energy sources

the interaction between different energy supply systems makes it difficult for integrated energy systems (IES) to identify weak nodes. Based on the analysis of the data generated by the actual operation of IES

this paper proposes a weak node identification method based on random matrix theory (RMT). First

establish a unified power flow model for IES. Secondly. introduce RMT and the characteristics of weak nodes

without considering the detailed physical model of the system

using historical data and real-time data to construct the random matrix. Thirdly

the two limit spectrum distribution functions (Marchenko-Pastur law and ring law) are used to qualitatively analyze the system's operating status

calculate linear eigenvalue statistics such as mean spectral radius (MSR)

and establish the weak node identification model based on entropy theory. Finally

the simulation of IES verifies the effectiveness of the proposed method and provides a new approach for the identification of weak nodes in IES.