Vulnerability analysis on random matrix theory for power grid with flexible impact loads
Abstract The stochastic volatility of the rail transit load brings greater uncertainty to the vulnerability of the power grid. To solve the problem of the inaccurate results caused by the incomplete time-domain simulation model of the power system with rail transit load integration, this paper propo...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-01-01
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| Series: | Energy Informatics |
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| Online Access: | https://doi.org/10.1186/s42162-024-00458-5 |
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| _version_ | 1832571247241723904 |
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| author | Chuan Long Shengyong Ye Xinying Zhu Minghai Xu Xinting Yang Yuqi Han Liyang Liu |
| author_facet | Chuan Long Shengyong Ye Xinying Zhu Minghai Xu Xinting Yang Yuqi Han Liyang Liu |
| author_sort | Chuan Long |
| collection | DOAJ |
| description | Abstract The stochastic volatility of the rail transit load brings greater uncertainty to the vulnerability of the power grid. To solve the problem of the inaccurate results caused by the incomplete time-domain simulation model of the power system with rail transit load integration, this paper proposes a vulnerability analysis method for the power system with rail transit load integration based on the random matrix theory. In this paper, we first constructed a rail transit load model based on Deep Convolutional Generative Adversarial Networks (DCGAN) to simulate the situation that massive rail transit load merged into the Grid Scenario. Then, we generate a high-dimensional random matrix based on the power flow of the grid-connected system under different rail transit loads. Then, we construct a vulnerability analysis model combining the random matrix theory and the real-time separation window. Finally, we take the IEEE-39 bus system and a regional power grid in China as examples to evaluate the vulnerability of the grid-connected system. The results show that our method quantifies not only the impact of the rail transit load volatility on the system vulnerability, but the system endurance under different capacities of the rail transit load connected to grid. Moreover, it also provides a new way for system planning and safety monitoring in the power system with rail transit load integration. |
| format | Article |
| id | doaj-art-852b7d105ae04df5925d1aae262ea71a |
| institution | Kabale University |
| issn | 2520-8942 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Energy Informatics |
| spelling | doaj-art-852b7d105ae04df5925d1aae262ea71a2025-02-02T12:44:43ZengSpringerOpenEnergy Informatics2520-89422025-01-018111810.1186/s42162-024-00458-5Vulnerability analysis on random matrix theory for power grid with flexible impact loadsChuan Long0Shengyong Ye1Xinying Zhu2Minghai Xu3Xinting Yang4Yuqi Han5Liyang Liu6State Grid Sichuan Economic Research InstituteState Grid Sichuan Economic Research InstituteSchool of Electrical Engineering, Southwest Jiaotong UniversitySchool of Electrical Engineering, Southwest Jiaotong UniversityState Grid Sichuan Economic Research InstituteState Grid Sichuan Economic Research InstituteState Grid Sichuan Economic Research InstituteAbstract The stochastic volatility of the rail transit load brings greater uncertainty to the vulnerability of the power grid. To solve the problem of the inaccurate results caused by the incomplete time-domain simulation model of the power system with rail transit load integration, this paper proposes a vulnerability analysis method for the power system with rail transit load integration based on the random matrix theory. In this paper, we first constructed a rail transit load model based on Deep Convolutional Generative Adversarial Networks (DCGAN) to simulate the situation that massive rail transit load merged into the Grid Scenario. Then, we generate a high-dimensional random matrix based on the power flow of the grid-connected system under different rail transit loads. Then, we construct a vulnerability analysis model combining the random matrix theory and the real-time separation window. Finally, we take the IEEE-39 bus system and a regional power grid in China as examples to evaluate the vulnerability of the grid-connected system. The results show that our method quantifies not only the impact of the rail transit load volatility on the system vulnerability, but the system endurance under different capacities of the rail transit load connected to grid. Moreover, it also provides a new way for system planning and safety monitoring in the power system with rail transit load integration.https://doi.org/10.1186/s42162-024-00458-5Power system vulnerabilityRandom matrix theoryRail transit loadDCGAN |
| spellingShingle | Chuan Long Shengyong Ye Xinying Zhu Minghai Xu Xinting Yang Yuqi Han Liyang Liu Vulnerability analysis on random matrix theory for power grid with flexible impact loads Energy Informatics Power system vulnerability Random matrix theory Rail transit load DCGAN |
| title | Vulnerability analysis on random matrix theory for power grid with flexible impact loads |
| title_full | Vulnerability analysis on random matrix theory for power grid with flexible impact loads |
| title_fullStr | Vulnerability analysis on random matrix theory for power grid with flexible impact loads |
| title_full_unstemmed | Vulnerability analysis on random matrix theory for power grid with flexible impact loads |
| title_short | Vulnerability analysis on random matrix theory for power grid with flexible impact loads |
| title_sort | vulnerability analysis on random matrix theory for power grid with flexible impact loads |
| topic | Power system vulnerability Random matrix theory Rail transit load DCGAN |
| url | https://doi.org/10.1186/s42162-024-00458-5 |
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