A Framework for Wildfire Risk Assessment to Electric Grid
Wildfires can cause catastrophic damage to the surrounding environment and pose substantial challenges to the reliability and resiliency of the electric grid. Recently, wildfire incidents have increased, and electric utilities are facing numerous challenges in maintaining seamless operation of the p...
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| Format: | Article |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/11053845/ |
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| author | Jubair Yusuf Holly Eagleston Michelle Bester Brian J. Pierre |
| author_facet | Jubair Yusuf Holly Eagleston Michelle Bester Brian J. Pierre |
| author_sort | Jubair Yusuf |
| collection | DOAJ |
| description | Wildfires can cause catastrophic damage to the surrounding environment and pose substantial challenges to the reliability and resiliency of the electric grid. Recently, wildfire incidents have increased, and electric utilities are facing numerous challenges in maintaining seamless operation of the power system. In this paper, a data-driven framework is proposed to assess the spatio-temporal aspects of wildfires on the power system. To illustrate this approach, we utilize data from two existing power networks in the southwestern-US, including corresponding fire risk values for these geographical locations. This methodology aims to establish a correlation between the wildfire risks to the power grid models, leveraging the geographical attributes of transmission lines. Subsequently, power flow is solved using dynamic power grid models in Positive Sequence Load Flow (PSLF) to demonstrate the damages caused by wildfires using probabilities representing wildfire risks and fire arrival times based on single fire growth, respectively. Additionally, grid hardening techniques and component-induced ignition probabilities are incorporated in the analysis to provide a comparative evaluation of the effects on power grids with grid hardening included. The findings demonstrate that both N-k and N-1-1 contingencies evaluations are required, and the reliability of a system in adverse fire-related conditions can be exacerbated without grid-hardening measures, and the cascading failure probabilities can be significantly increased while component failures are incorporated. |
| format | Article |
| id | doaj-art-c7bff8fe9b95465382e856c2d05c5816 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-c7bff8fe9b95465382e856c2d05c58162025-08-20T03:17:32ZengIEEEIEEE Access2169-35362025-01-011311543311544510.1109/ACCESS.2025.358396411053845A Framework for Wildfire Risk Assessment to Electric GridJubair Yusuf0https://orcid.org/0000-0003-1048-0952Holly Eagleston1Michelle Bester2Brian J. Pierre3https://orcid.org/0000-0003-3880-5501Electric Power Systems Research Department, Sandia National Laboratories, Albuquerque, NM, USARemote Sensing Research Department, Sandia National Laboratories, Albuquerque, NM, USAElectric Power Systems Research Department, Sandia National Laboratories, Albuquerque, NM, USAElectric Power Systems Research Department, Sandia National Laboratories, Albuquerque, NM, USAWildfires can cause catastrophic damage to the surrounding environment and pose substantial challenges to the reliability and resiliency of the electric grid. Recently, wildfire incidents have increased, and electric utilities are facing numerous challenges in maintaining seamless operation of the power system. In this paper, a data-driven framework is proposed to assess the spatio-temporal aspects of wildfires on the power system. To illustrate this approach, we utilize data from two existing power networks in the southwestern-US, including corresponding fire risk values for these geographical locations. This methodology aims to establish a correlation between the wildfire risks to the power grid models, leveraging the geographical attributes of transmission lines. Subsequently, power flow is solved using dynamic power grid models in Positive Sequence Load Flow (PSLF) to demonstrate the damages caused by wildfires using probabilities representing wildfire risks and fire arrival times based on single fire growth, respectively. Additionally, grid hardening techniques and component-induced ignition probabilities are incorporated in the analysis to provide a comparative evaluation of the effects on power grids with grid hardening included. The findings demonstrate that both N-k and N-1-1 contingencies evaluations are required, and the reliability of a system in adverse fire-related conditions can be exacerbated without grid-hardening measures, and the cascading failure probabilities can be significantly increased while component failures are incorporated.https://ieeexplore.ieee.org/document/11053845/Burning probabilitydynamic simulationoutagespower systemgrid hardeningwildfire |
| spellingShingle | Jubair Yusuf Holly Eagleston Michelle Bester Brian J. Pierre A Framework for Wildfire Risk Assessment to Electric Grid IEEE Access Burning probability dynamic simulation outages power system grid hardening wildfire |
| title | A Framework for Wildfire Risk Assessment to Electric Grid |
| title_full | A Framework for Wildfire Risk Assessment to Electric Grid |
| title_fullStr | A Framework for Wildfire Risk Assessment to Electric Grid |
| title_full_unstemmed | A Framework for Wildfire Risk Assessment to Electric Grid |
| title_short | A Framework for Wildfire Risk Assessment to Electric Grid |
| title_sort | framework for wildfire risk assessment to electric grid |
| topic | Burning probability dynamic simulation outages power system grid hardening wildfire |
| url | https://ieeexplore.ieee.org/document/11053845/ |
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