2022
DOI: 10.1088/1748-9326/ac8d18
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Predicting electricity infrastructure induced wildfire risk in California

Abstract: This paper examines the use of risk models to predict the timing and location of wildfires caused by electricity infrastructure. Our data include historical ignition and wire-down points triggered by grid infrastructure collected between 2015 to 2019 in Pacific Gas & Electricity territory along with various weather, vegetation, and very high resolution data on grid infrastructure including location, age, materials. With these data we explore a range of machine learning methods and strategies to manage tra… Show more

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Cited by 7 publications
(1 citation statement)
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“…Resilience through battery installations or under-grounding of lines is studied in [32]- [35], resilience through microgrid operations in [36], [37], and load shifting through energy storage to reduce power outages in [38]. Other OPS research considers extensions necessary for distribution grids [39], concurrent planning of PSPS and grid restoration [40], considerations of fairness for load outages [41], improved forecasting of wildfire ignition risk [31], [42], and dynamic line rating to reduce current rather than fully de-energize lines [43].…”
Section: A Related Workmentioning
confidence: 99%
“…Resilience through battery installations or under-grounding of lines is studied in [32]- [35], resilience through microgrid operations in [36], [37], and load shifting through energy storage to reduce power outages in [38]. Other OPS research considers extensions necessary for distribution grids [39], concurrent planning of PSPS and grid restoration [40], considerations of fairness for load outages [41], improved forecasting of wildfire ignition risk [31], [42], and dynamic line rating to reduce current rather than fully de-energize lines [43].…”
Section: A Related Workmentioning
confidence: 99%