Evaluating the vulnerability of integrated electricity-heat-gas systems based on the high-dimensional random matrix theory

Abstract

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.