Forecasting space weather risks on power grids
Physics and place: The system combines Auroral Electrojet (AE) and Disturbance Storm Time (Dst) forecasts with local latitude, geology, and ground conductivity. Advance warning: The pipeline detected nearly 80% of major space-weather events during the evaluation period and can warn grid operators 30 to 60 minutes before a specific risk appears. Forecasting a threat to critical infrastructure During the May 2024 geomagnetic storm, utilities across North America prepared for possible impacts as auroras extended far beyond their usual range.
- ▪Physics and place: The system combines Auroral Electrojet (AE) and Disturbance Storm Time (Dst) forecasts with local latitude, geology, and ground conductivity.
- ▪Advance warning: The pipeline detected nearly 80% of major space-weather events during the evaluation period and can warn grid operators 30 to 60 minutes before a specific risk appears.
- ▪Forecasting a threat to critical infrastructure During the May 2024 geomagnetic storm, utilities across North America prepared for possible impacts as auroras extended far beyond their usual range.
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| Original publisher | Microsoft Research |
| Canonical URL | https://www.microsoft.com/en-us/research/blog/forecasting-space-weather-risks-on-power-grids/ |
| Publication time | Wed, 30 Sep 2026 16:00:00 +0000 |
| Retrieval time | 2026-09-30T16:02:02.160Z |
| Last seen | 2026-09-30T16:02:02.160Z |
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Forecasting space weather risks on power grids Published September 30, 2026 By Rohan Kannan , Intern Share this page Share on Facebook Share on X Share on LinkedIn Share on Reddit Subscribe to our RSS feed At a glance End-to-end forecasting: A machine learning pipeline uses forecast-time solar-wind information to generate location-specific risk estimates for 66,935 substations in the continental United States. Physics and place: The system combines Auroral Electrojet (AE) and Disturbance Storm Time (Dst) forecasts with local latitude, geology, and ground conductivity. Advance warning: The pipeline detected nearly 80% of major space-weather events during the evaluation period and can warn grid operators 30 to 60 minutes before a specific risk appears.
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