Forecasting space weather risks on power grids
Microsoft 2 weeks ago 18
A Microsoft Research intern built a physics-grounded machine learning pipeline that forecasts geomagnetically induced current risk for power-grid substations using solar-wind forecasts plus local geology and grid data. It estimated risk for 66,935 U.S. substations and generated outputs in about 333 milliseconds while detecting nearly 80% of major space-weather events in the evaluation period. The approach changes grid warning from broad alerts to location-specific, 30–60 minute risk estimates that utilities can use to prioritize analysis and potential protective actions.