Network Embedding Algorithm for Vulnerability Assessment of Power Transmission Lines Using Integrated Structure and Attribute Information

In power systems, failures of vulnerable lines can trigger large-scale cascading failures, and vulnerability assessment is dedicated to locating these lines and reducing the risks of such failures. Based on a structure and attribute network embedding (SANE) algorithm, a novel quantitative vulnerabil...

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Main Authors: Xianglong Lian, Tong Qian, Zepeng Li, Xingyu Chen, Wenhu Tang, Q. H. Wu
Format: Article
Language:English
Published: China electric power research institute 2024-01-01
Series:CSEE Journal of Power and Energy Systems
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10058874/
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author Xianglong Lian
Tong Qian
Zepeng Li
Xingyu Chen
Wenhu Tang
Q. H. Wu
author_facet Xianglong Lian
Tong Qian
Zepeng Li
Xingyu Chen
Wenhu Tang
Q. H. Wu
author_sort Xianglong Lian
collection DOAJ
description In power systems, failures of vulnerable lines can trigger large-scale cascading failures, and vulnerability assessment is dedicated to locating these lines and reducing the risks of such failures. Based on a structure and attribute network embedding (SANE) algorithm, a novel quantitative vulnerability analysis method is proposed to identify vulnerable lines in this research. First, a two-layered random walk network with topological and electrical properties of transmission lines is established. Subsequently, based on the weighted degree of nodes in the two-layered network, the inter-layer and intra-layer walking transition probabilities are developed to obtain walk sequences. Then, a Word2Vec algorithm is applied to obtain low-dimension vectors representing transmission lines, according to obtained walk sequences for calculating the vulnerability index of transmissions lines. Finally, the proposed method is compared with three widely used methods in two test systems. Results show the network embedding based method is superior to those comparison methods and can provide guidance for identifying vulnerable lines.
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id doaj-art-3b1c685eb7884c77abc7c8e04afac048
institution DOAJ
issn 2096-0042
language English
publishDate 2024-01-01
publisher China electric power research institute
record_format Article
series CSEE Journal of Power and Energy Systems
spelling doaj-art-3b1c685eb7884c77abc7c8e04afac0482025-08-20T03:03:49ZengChina electric power research instituteCSEE Journal of Power and Energy Systems2096-00422024-01-0110135136010.17775/CSEEJPES.2021.0963010058874Network Embedding Algorithm for Vulnerability Assessment of Power Transmission Lines Using Integrated Structure and Attribute InformationXianglong Lian0Tong Qian1Zepeng Li2Xingyu Chen3Wenhu Tang4https://orcid.org/0000-0003-1823-2355Q. H. Wu5School of Electric Power Engineering, South China University of Technology,Guangzhou,China,510640School of Electric Power Engineering, South China University of Technology,Guangzhou,China,510640School of Electric Power Engineering, South China University of Technology,Guangzhou,China,510640School of Electric Power Engineering, South China University of Technology,Guangzhou,China,510640School of Electric Power Engineering, South China University of Technology,Guangzhou,China,510640School of Electric Power Engineering, South China University of Technology,Guangzhou,China,510640In power systems, failures of vulnerable lines can trigger large-scale cascading failures, and vulnerability assessment is dedicated to locating these lines and reducing the risks of such failures. Based on a structure and attribute network embedding (SANE) algorithm, a novel quantitative vulnerability analysis method is proposed to identify vulnerable lines in this research. First, a two-layered random walk network with topological and electrical properties of transmission lines is established. Subsequently, based on the weighted degree of nodes in the two-layered network, the inter-layer and intra-layer walking transition probabilities are developed to obtain walk sequences. Then, a Word2Vec algorithm is applied to obtain low-dimension vectors representing transmission lines, according to obtained walk sequences for calculating the vulnerability index of transmissions lines. Finally, the proposed method is compared with three widely used methods in two test systems. Results show the network embedding based method is superior to those comparison methods and can provide guidance for identifying vulnerable lines.https://ieeexplore.ieee.org/document/10058874/Network embeddingrandom walktransmission linesvulnerability assessment
spellingShingle Xianglong Lian
Tong Qian
Zepeng Li
Xingyu Chen
Wenhu Tang
Q. H. Wu
Network Embedding Algorithm for Vulnerability Assessment of Power Transmission Lines Using Integrated Structure and Attribute Information
CSEE Journal of Power and Energy Systems
Network embedding
random walk
transmission lines
vulnerability assessment
title Network Embedding Algorithm for Vulnerability Assessment of Power Transmission Lines Using Integrated Structure and Attribute Information
title_full Network Embedding Algorithm for Vulnerability Assessment of Power Transmission Lines Using Integrated Structure and Attribute Information
title_fullStr Network Embedding Algorithm for Vulnerability Assessment of Power Transmission Lines Using Integrated Structure and Attribute Information
title_full_unstemmed Network Embedding Algorithm for Vulnerability Assessment of Power Transmission Lines Using Integrated Structure and Attribute Information
title_short Network Embedding Algorithm for Vulnerability Assessment of Power Transmission Lines Using Integrated Structure and Attribute Information
title_sort network embedding algorithm for vulnerability assessment of power transmission lines using integrated structure and attribute information
topic Network embedding
random walk
transmission lines
vulnerability assessment
url https://ieeexplore.ieee.org/document/10058874/
work_keys_str_mv AT xianglonglian networkembeddingalgorithmforvulnerabilityassessmentofpowertransmissionlinesusingintegratedstructureandattributeinformation
AT tongqian networkembeddingalgorithmforvulnerabilityassessmentofpowertransmissionlinesusingintegratedstructureandattributeinformation
AT zepengli networkembeddingalgorithmforvulnerabilityassessmentofpowertransmissionlinesusingintegratedstructureandattributeinformation
AT xingyuchen networkembeddingalgorithmforvulnerabilityassessmentofpowertransmissionlinesusingintegratedstructureandattributeinformation
AT wenhutang networkembeddingalgorithmforvulnerabilityassessmentofpowertransmissionlinesusingintegratedstructureandattributeinformation
AT qhwu networkembeddingalgorithmforvulnerabilityassessmentofpowertransmissionlinesusingintegratedstructureandattributeinformation