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

Danlei Zhu; Bo Wang; Hengrui Ma; Hongxia Wang

doi:10.17775/CSEEJPES.2019.00440

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

Regular Papers | 更新时间：2025-12-18

- Evaluating the vulnerability of integrated electricity-heat-gas systems based on the high-dimensional random matrix theory
- Evaluating the vulnerability of integrated electricity-heat-gas systems based on the high-dimensional random matrix theory
- 中国电机工程学会电力与能源系统学报(英文) 2020年6卷第4期页码：878-889
- 作者机构：
  
  1. Department of Electrical Engineering, Wuhan University,Wuhan,China
  2. Department of Electrical Engineering, Qinghai University,Xining,China
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2019.00440
  中图分类号：
- 纸质出版：2020
- 稿件说明：
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Danlei Zhu, Bo Wang, Hengrui Ma, 等. Evaluating the vulnerability of integrated electricity-heat-gas systems based on the high-dimensional random matrix theory[J]. 中国电机工程学会电力与能源系统学报(英文), 2020,6(4):878-889.

Danlei Zhu, Bo Wang, Hengrui Ma, et al. Evaluating the vulnerability of integrated electricity-heat-gas systems based on the high-dimensional random matrix theory[J]. CSEE Journal of Power and Energy Systems, 2020, 6(4): 878-889.
Danlei Zhu, Bo Wang, Hengrui Ma, 等. Evaluating the vulnerability of integrated electricity-heat-gas systems based on the high-dimensional random matrix theory[J]. 中国电机工程学会电力与能源系统学报(英文), 2020,6(4):878-889. DOI： 10.17775/CSEEJPES.2019.00440.

Danlei Zhu, Bo Wang, Hengrui Ma, et al. Evaluating the vulnerability of integrated electricity-heat-gas systems based on the high-dimensional random matrix theory[J]. CSEE Journal of Power and Energy Systems, 2020, 6(4): 878-889. DOI： 10.17775/CSEEJPES.2019.00440.

摘要

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.

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