Risk-Averse Resilient Operation of Electricity Grid Under the Risk of Wildfire

[2408.15774] Risk-Averse Resilient Operation of Electricity Grid Under the Risk of Wildfire Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Electrical Engineering and Systems Science > Systems and Control arXiv:2408.15774 (eess) [Submitted on 28 Aug 2024 ( v1 ), last revised 10 Apr 2026 (this version, v4)] Title: Risk-Averse Resilient Operation of Electricity Grid Under the Risk of Wildfire Authors: Muhammad Waseem , Arash F. Soofi , Saeed D. Manshadi View a PDF of the paper titled Risk-Averse Resilient Operation of Electricity Grid Under the Risk of Wildfire, by Muhammad Waseem and 2 other authors View PDF HTML (experimental) Abstract: Wildfires and other extreme weather conditions due to climate change are stressing the aging electrical infrastructure. Power utilities have implemented public safety power shutoffs as a method to mitigate the risk of wildfire by proactively de-energizing some power lines, which leaves customers without power. System operators have to make a compromise between de-energizing of power lines to avoid the wildfire risk and energizing those lines to serve the demand. In this work, with a quantified wildfire ignition risk of each line, a resilient operation problem is presented in power systems with a high penetration level of renewable generation resources. A two-stage robust optimization problem is formulated and solved using column-and-constraint generation algorithm to find improved balance between the de-energization of power lines and the customers served. Different penetration levels of renewable generation to mitigate the impact of extreme fire hazard situations on the energization of customers is assessed. The validity of the presented robust optimization algorithm is demonstrated on various test cases. Subjects: Systems and Control (eess.SY) Cite as: arXiv:2408.15774 [eess.SY] (or arXiv:2408.15774v4 [eess.SY] for this version) https://doi.org/10.48550/arXiv.2408.15774 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Muhammad Waseem [ view email ] [v1] Wed, 28 Aug 2024 13:12:28 UTC (342 KB) [v2] Sat, 31 Aug 2024 05:37:47 UTC (342 KB) [v3] Mon, 9 Sep 2024 19:29:10 UTC (342 KB) [v4] Fri, 10 Apr 2026 10:04:17 UTC (340 KB) Full-text links: Access Paper: View a PDF of the paper titled Risk-Averse Resilient Operation of Electricity Grid Under the Risk of Wildfire, by Muhammad Waseem and 2 other authors View PDF HTML (experimental) TeX Source view license Current browse context: eess.SY < prev | next > new | recent | 2024-08 Change to browse by: cs cs.SY eess References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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