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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| Format: | Article |
| Language: | English |
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China electric power research institute
2024-01-01
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| Series: | CSEE Journal of Power and Energy Systems |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10058874/ |
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| _version_ | 1849768397979516928 |
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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. |
| format | Article |
| 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/ |
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