LAPSE:2023.8519
Published Article

LAPSE:2023.8519
Coupled Model and Node Importance Evaluation of Electric Power Cyber-Physical Systems Considering Carbon Power Flow
February 24, 2023
Abstract
To improve the distributed carbon emission optimization control capability of the smart distribution network system, thereby reducing the carbon emissions in the distribution process, it is a very important issue to comprehensively analyze the importance of the node carbon emission flow of the smart distribution network. This paper transforms the power grid into a carbon emission flow network through power flow calculations: Based on the complex network theory, it determines the coupling scale of the two networks by means of the correlation coefficient method and the correlation matrix method, and establishes a coupling network model based on the carbon emission flow network; Combining the different business characteristics of carbon emission flow and information flow, an evaluation index system considering the dual-network coupling scale is established, and a multi-indicator comprehensive evaluation method that combines the Topsis and grey relational analysis method, that can objectively evaluate indicators that contain subjective components was proposed; The obtained node importance values can be used to determine the relative key line, greater sum node importance values represent a greater carbon emission impact of the line, providing a sequential basis for the carbon reduction and restructuring of the distribution network; Taking the 3-machine 9-node system as an example, the carbon flow distribution in the corresponding network is calculated, and the comprehensive importance value of the coupling node is calculated to analyze the rationality of this method.
To improve the distributed carbon emission optimization control capability of the smart distribution network system, thereby reducing the carbon emissions in the distribution process, it is a very important issue to comprehensively analyze the importance of the node carbon emission flow of the smart distribution network. This paper transforms the power grid into a carbon emission flow network through power flow calculations: Based on the complex network theory, it determines the coupling scale of the two networks by means of the correlation coefficient method and the correlation matrix method, and establishes a coupling network model based on the carbon emission flow network; Combining the different business characteristics of carbon emission flow and information flow, an evaluation index system considering the dual-network coupling scale is established, and a multi-indicator comprehensive evaluation method that combines the Topsis and grey relational analysis method, that can objectively evaluate indicators that contain subjective components was proposed; The obtained node importance values can be used to determine the relative key line, greater sum node importance values represent a greater carbon emission impact of the line, providing a sequential basis for the carbon reduction and restructuring of the distribution network; Taking the 3-machine 9-node system as an example, the carbon flow distribution in the corresponding network is calculated, and the comprehensive importance value of the coupling node is calculated to analyze the rationality of this method.
Record ID
Keywords
carbon emission flow network, coupling scale, distribution network, dual-network coupling model, key line, node importance value evaluation, objective empowerment method
Subject
Suggested Citation
Yang C, Sun H, Li T, Xie H, Lei Z, Song J, Cai H, Yang J, Gong G, Ren S. Coupled Model and Node Importance Evaluation of Electric Power Cyber-Physical Systems Considering Carbon Power Flow. (2023). LAPSE:2023.8519
Author Affiliations
Yang C: Information and Communication Company, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, China
Sun H: Research Institute, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110000, China
Li T: Research Institute, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110000, China
Xie H: Beijing Energy and Power Information Security Engineering Technology Research Center, North China Electric Power University, Changping District, Beijing 102206, China
Lei Z: Information and Communication Company, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, China
Song J: Research Institute, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110000, China
Cai H: Beijing Energy and Power Information Security Engineering Technology Research Center, North China Electric Power University, Changping District, Beijing 102206, China
Yang J: Beijing Energy and Power Information Security Engineering Technology Research Center, North China Electric Power University, Changping District, Beijing 102206, China
Gong G: Beijing Energy and Power Information Security Engineering Technology Research Center, North China Electric Power University, Changping District, Beijing 102206, China
Ren S: Research Institute, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110000, China
Sun H: Research Institute, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110000, China
Li T: Research Institute, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110000, China
Xie H: Beijing Energy and Power Information Security Engineering Technology Research Center, North China Electric Power University, Changping District, Beijing 102206, China
Lei Z: Information and Communication Company, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, China
Song J: Research Institute, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110000, China
Cai H: Beijing Energy and Power Information Security Engineering Technology Research Center, North China Electric Power University, Changping District, Beijing 102206, China
Yang J: Beijing Energy and Power Information Security Engineering Technology Research Center, North China Electric Power University, Changping District, Beijing 102206, China
Gong G: Beijing Energy and Power Information Security Engineering Technology Research Center, North China Electric Power University, Changping District, Beijing 102206, China
Ren S: Research Institute, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110000, China
Journal Name
Energies
Volume
15
Issue
21
First Page
8223
Year
2022
Publication Date
2022-11-03
ISSN
1996-1073
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Original Submission
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PII: en15218223, Publication Type: Journal Article
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LAPSE:2023.8519
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https://doi.org/10.3390/en15218223
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Feb 24, 2023
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