AI and the World's Hard Problems · Earth & climate science · Microsoft Research · 2026-09-30
Forecasting space weather risks on power grids
Extreme space-weather events can induce currents in transmission networks that damage equipment, and grid operators need to know when and where the effects will be most severe with enough warning. Microsoft Research built a machine learning pipeline that combines solar-wind data, AE and Dst forecasts, local latitude, geology, and ground conductivity to produce risk estimates for 66,935 substations in the continental United States. During the evaluation period it detected nearly 80% of major space-weather events and can warn operators 30 to 60 minutes before a specific risk appears.