Event Driven Model for Dynamic Deduction of Transmission Line Safety Under Wildfire Disasters Based on Multi-Source Data
With the intensification of global climate change, wildfires pose a serious threat to the safety of transmission lines. A dynamic deduction method for the safety status of transmission lines under wildfire disasters based on event driven models is proposed in this paper, aiming to evaluate and predi...
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IEEE
2024-01-01
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Online Access: | https://ieeexplore.ieee.org/document/10792913/ |
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author | Zhipeng Li Shuo Shen Rui Dong Chenfeng Qi Yahan Zhang Yanhong Wang |
author_facet | Zhipeng Li Shuo Shen Rui Dong Chenfeng Qi Yahan Zhang Yanhong Wang |
author_sort | Zhipeng Li |
collection | DOAJ |
description | With the intensification of global climate change, wildfires pose a serious threat to the safety of transmission lines. A dynamic deduction method for the safety status of transmission lines under wildfire disasters based on event driven models is proposed in this paper, aiming to evaluate and predict the safety status of transmission lines in real-time in wildfire environments. This method first constructs an event driven model that includes meteorological factors, terrain features, and wildfire propagation characteristics. By analyzing historical data, key events that affect the safety of transmission lines are identified. Secondly, using dynamic deduction technology, real-time monitoring and prediction of the safety form of transmission lines are carried out to ensure timely response to potential risks. Finally, the effectiveness and practicality of the method are verified through simulation. Under two levels of carbon balance disruption, IDCs operators reduced their computing power load on IDCs5 and IDCs6 by 20% and 80% respectively in the remaining months of this year. Similarly, the power grid will increase the penetration rate of wind and solar power to 32% and 58% respectively in the remaining months of this year. The results showed that the dynamic deduction method based on event driven model can significantly improve the safety management capability of transmission lines in wildfire disasters. |
format | Article |
id | doaj-art-8c3cb9efa6604e4995932a2f1e3df488 |
institution | Kabale University |
issn | 2169-3536 |
language | English |
publishDate | 2024-01-01 |
publisher | IEEE |
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series | IEEE Access |
spelling | doaj-art-8c3cb9efa6604e4995932a2f1e3df4882025-01-16T00:02:03ZengIEEEIEEE Access2169-35362024-01-011219286019287310.1109/ACCESS.2024.351548210792913Event Driven Model for Dynamic Deduction of Transmission Line Safety Under Wildfire Disasters Based on Multi-Source DataZhipeng Li0Shuo Shen1Rui Dong2Chenfeng Qi3Yahan Zhang4https://orcid.org/0009-0004-4682-7406Yanhong Wang5Digitalization Department, State Grid Gansu Electric Power Company, Gansu, ChinaDigitalization Department, State Grid Gansu Electric Power Company, Gansu, ChinaDigitalization Department, State Grid Gansu Electric Power Company, Gansu, ChinaDigital Communication Department, Longnan Power Supply Company of State Grid Gansu Electric Power Company, Gansu, ChinaDigital Communication Department, Longnan Power Supply Company of State Grid Gansu Electric Power Company, Gansu, ChinaDigital Communication Department, Longnan Power Supply Company of State Grid Gansu Electric Power Company, Gansu, ChinaWith the intensification of global climate change, wildfires pose a serious threat to the safety of transmission lines. A dynamic deduction method for the safety status of transmission lines under wildfire disasters based on event driven models is proposed in this paper, aiming to evaluate and predict the safety status of transmission lines in real-time in wildfire environments. This method first constructs an event driven model that includes meteorological factors, terrain features, and wildfire propagation characteristics. By analyzing historical data, key events that affect the safety of transmission lines are identified. Secondly, using dynamic deduction technology, real-time monitoring and prediction of the safety form of transmission lines are carried out to ensure timely response to potential risks. Finally, the effectiveness and practicality of the method are verified through simulation. Under two levels of carbon balance disruption, IDCs operators reduced their computing power load on IDCs5 and IDCs6 by 20% and 80% respectively in the remaining months of this year. Similarly, the power grid will increase the penetration rate of wind and solar power to 32% and 58% respectively in the remaining months of this year. The results showed that the dynamic deduction method based on event driven model can significantly improve the safety management capability of transmission lines in wildfire disasters.https://ieeexplore.ieee.org/document/10792913/Event driven modelwildfire disasterstransmission linesafe formdynamic deductionrisk assessment |
spellingShingle | Zhipeng Li Shuo Shen Rui Dong Chenfeng Qi Yahan Zhang Yanhong Wang Event Driven Model for Dynamic Deduction of Transmission Line Safety Under Wildfire Disasters Based on Multi-Source Data IEEE Access Event driven model wildfire disasters transmission line safe form dynamic deduction risk assessment |
title | Event Driven Model for Dynamic Deduction of Transmission Line Safety Under Wildfire Disasters Based on Multi-Source Data |
title_full | Event Driven Model for Dynamic Deduction of Transmission Line Safety Under Wildfire Disasters Based on Multi-Source Data |
title_fullStr | Event Driven Model for Dynamic Deduction of Transmission Line Safety Under Wildfire Disasters Based on Multi-Source Data |
title_full_unstemmed | Event Driven Model for Dynamic Deduction of Transmission Line Safety Under Wildfire Disasters Based on Multi-Source Data |
title_short | Event Driven Model for Dynamic Deduction of Transmission Line Safety Under Wildfire Disasters Based on Multi-Source Data |
title_sort | event driven model for dynamic deduction of transmission line safety under wildfire disasters based on multi source data |
topic | Event driven model wildfire disasters transmission line safe form dynamic deduction risk assessment |
url | https://ieeexplore.ieee.org/document/10792913/ |
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