Dynamic Identification Method of Distribution Network Weak Links Considering Disaster Emergency Scheduling
With the deterioration of the global climate, the losses caused by distribution network failures during natural disasters such as typhoons have become increasingly serious. In the whole process of disaster resistance, it is very important to effectively identify the weak links in distribution networ...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/18/13/3519 |
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| Summary: | With the deterioration of the global climate, the losses caused by distribution network failures during natural disasters such as typhoons have become increasingly serious. In the whole process of disaster resistance, it is very important to effectively identify the weak links in distribution networks during typhoon disasters. In this paper, the weak links in distribution networks during typhoons are identified dynamically from four indexes: real-time failure rate, load loss caused by line disconnection, line degree, and line betweenness. First, the Batts typhoon model is established to simulate the whole process of the typhoon and obtain the real-time failure rate of the distribution network. Secondly, the distribution network is powered by distributed generators when there are line disconnections, and a mixed integer linear programming model is established to solve the problem. Then, the line degrees and the line betweenness are calculated to obtain the structure indexes of the line, both of which are dynamically related to the power flow and the loads of the distribution network. Finally, the four indexes are comprehensively analyzed, and the dynamic identification of the weak links in the distribution network are realized by the analytic hierarchy process (AHP)—entropy weight (EW)—technique for order preference by similarity to an ideal solution (TOPSIS) method. The results of the case study show that the proposed method can effectively identify the weak links in a distribution network during a typhoon and provide a reference to resist extreme disasters. |
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| ISSN: | 1996-1073 |