AI Could Snuff Out Wildfires One Power Line at a Time - CleanTechnica

The article discusses a new project led by the U.S. National Renewable Energy Laboratory (NREL) aimed at preventing wildfires caused by fallen or degraded power lines through the use of artificial intelligence (AI). Each year, a portion of wildfires in the U.S. are triggered by high-impedance (HiZ) faults—small electrical faults where energized conductors contact the ground, producing sparks that can ignite nearby flammable materials. These faults are difficult to detect due to their low energy output. To address this, NREL, funded by the U.S. Army Construction Engineering Research Laboratory, developed machine learning models based on artificial neural networks (ANNs) to identify these faults early and enable utilities to respond quickly, thereby reducing wildfire risks and power outages. NREL partnered with Eaton, a multinational power management company, to simulate various downed conductor scenarios under different environmental conditions, generating extensive datasets. These datasets were integrated into NREL’s PSCAD grid simulation platform to create a large variety of