Vulnerable node identification method for distribution networks based on complex networks and improved TOPSIS theory
Abstract A method for identifying vulnerable nodes in distribution networks is proposed, which is based on complex networks and optimized TOPSIS. This method aims to address the issues of one‐sided evaluation indicators and inaccurate indicator weights that are present in existing methods for identi...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-11-01
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| Series: | IET Generation, Transmission & Distribution |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/gtd2.13011 |
| _version_ | 1797615864499929088 |
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| author | Enyu Jiang Wentao Zhang Ang Xue Shunfu Lin Yang Mi Dongdong Li |
| author_facet | Enyu Jiang Wentao Zhang Ang Xue Shunfu Lin Yang Mi Dongdong Li |
| author_sort | Enyu Jiang |
| collection | DOAJ |
| description | Abstract A method for identifying vulnerable nodes in distribution networks is proposed, which is based on complex networks and optimized TOPSIS. This method aims to address the issues of one‐sided evaluation indicators and inaccurate indicator weights that are present in existing methods for identifying vulnerable nodes in distribution networks. Based on the theory of complex networks, a comprehensive set of vulnerability indicators for distribution network nodes is constructed by considering both the topology structure and system operation status of the distribution network. The TOPSIS comprehensive evaluation model for optimization is proposed to enhance the selection process of optimal and worst indicator values. The advantages and disadvantages of each indicator are characterized using Mahalanobis distance. The calculation of proximity is optimized by establishing a virtual negative ideal solution, which makes the identification of vulnerable nodes more reasonable. The simulation results demonstrate that this method is more effective in identifying vulnerable nodes in the power grid compared to traditional methods, and has significant practical applications. |
| first_indexed | 2024-03-11T07:33:01Z |
| format | Article |
| id | doaj.art-823582d1cbe2443385f3df79d30593d2 |
| institution | Directory Open Access Journal |
| issn | 1751-8687 1751-8695 |
| language | English |
| last_indexed | 2024-03-11T07:33:01Z |
| publishDate | 2023-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Generation, Transmission & Distribution |
| spelling | doaj.art-823582d1cbe2443385f3df79d30593d22023-11-17T06:51:33ZengWileyIET Generation, Transmission & Distribution1751-86871751-86952023-11-0117224991500210.1049/gtd2.13011Vulnerable node identification method for distribution networks based on complex networks and improved TOPSIS theoryEnyu Jiang0Wentao Zhang1Ang Xue2Shunfu Lin3Yang Mi4Dongdong Li5Shanghai University of Electric Power Shanghai ChinaShanghai University of Electric Power Shanghai ChinaShanghai University of Electric Power Shanghai ChinaShanghai University of Electric Power Shanghai ChinaShanghai University of Electric Power Shanghai ChinaShanghai University of Electric Power Shanghai ChinaAbstract A method for identifying vulnerable nodes in distribution networks is proposed, which is based on complex networks and optimized TOPSIS. This method aims to address the issues of one‐sided evaluation indicators and inaccurate indicator weights that are present in existing methods for identifying vulnerable nodes in distribution networks. Based on the theory of complex networks, a comprehensive set of vulnerability indicators for distribution network nodes is constructed by considering both the topology structure and system operation status of the distribution network. The TOPSIS comprehensive evaluation model for optimization is proposed to enhance the selection process of optimal and worst indicator values. The advantages and disadvantages of each indicator are characterized using Mahalanobis distance. The calculation of proximity is optimized by establishing a virtual negative ideal solution, which makes the identification of vulnerable nodes more reasonable. The simulation results demonstrate that this method is more effective in identifying vulnerable nodes in the power grid compared to traditional methods, and has significant practical applications.https://doi.org/10.1049/gtd2.13011complex network theoryimproved TOPSISoperational statuspower systemvulnerable node |
| spellingShingle | Enyu Jiang Wentao Zhang Ang Xue Shunfu Lin Yang Mi Dongdong Li Vulnerable node identification method for distribution networks based on complex networks and improved TOPSIS theory IET Generation, Transmission & Distribution complex network theory improved TOPSIS operational status power system vulnerable node |
| title | Vulnerable node identification method for distribution networks based on complex networks and improved TOPSIS theory |
| title_full | Vulnerable node identification method for distribution networks based on complex networks and improved TOPSIS theory |
| title_fullStr | Vulnerable node identification method for distribution networks based on complex networks and improved TOPSIS theory |
| title_full_unstemmed | Vulnerable node identification method for distribution networks based on complex networks and improved TOPSIS theory |
| title_short | Vulnerable node identification method for distribution networks based on complex networks and improved TOPSIS theory |
| title_sort | vulnerable node identification method for distribution networks based on complex networks and improved topsis theory |
| topic | complex network theory improved TOPSIS operational status power system vulnerable node |
| url | https://doi.org/10.1049/gtd2.13011 |
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