Quantifying the Risk of Wildfire Ignition by Power Lines Under Extreme Weather Conditions

Utilities in California conduct public safety power shut-offs (PSPSs) to eliminate the elevated chances of wildfire ignitions caused by lines during extreme weather conditions. We propose risk aware operation planning problem (WRAP), which enables system operators pinpoint segments network that should be de-energized. Sustained wind and gust can lead conductor clashing, could ignite surrounding vegetation. The 3-D nonlinear vibration equations are employed generate a dataset considers physical, structural, meteorological parameters. With help machine learning techniques, surrogate model is obtained quantifies ignition individual under cases illustrate superior performance WRAP conditions mitigating serving customers compared naive PSPS approach another method literature. Cases also designated sensitivity analysis critical load-serving control parameters different Finally, discussion provided explore our monetization its implications for decisions.