Romvær, som solstormer, kan indusere strømmer (GICs) i kraftnett, rørledninger og undersjøiske kabler. Slike strømmer kan skade transformatorer, forstyrre strømforsyningen og true kritisk infrastruktur. Dagens globale varselindekser, som Kp, gir kun grove varsler og fanger ikke opp lokale sårbarheter, noe som gjør at operatører mangler handlingsrelevant informasjon. Vårt prosjekt har utviklet en dyplæringsbasert prognosemodell som kombinerer solvinddata, magnetometermålinger og historiske GIC-hendelser for å gi sannsynlighetsbaserte, stedsspesifikke varsler. Tester på tidligere stormer viser at modellen overgår eksisterende verktøy. Systemet kan utstede nivåene “watch” og “warning”, slik at operatører kan iverksette tiltak som lastfordeling eller midlertidig frakobling av utsatt utstyr. Selv om fokuset i første omgang er det norske kraftnettet, kan tilnærmingen tilpasses andre infrastrukturer, som rørledninger, jernbane og kommunikasjonskabler, og vekker interesse i sektorer som forsikring og romfart. Ved å styrke beredskap og robusthet bidrar teknologien til å tette gapet mellom bevissthet om romvær og evnen til å håndtere konsekvensene, og støtter overgangen til et mer bærekraftig, pålitelig og elektrifisert samfunn.
The qualification project has delivered both technical and commercial advances towards a novel forecasting tool for geomagnetically induced currents (GICs). On the technical side, we have moved from a deterministic proof of concept to a deep learning–based probabilistic model that ingests real-time solar wind and geomagnetic measurements to provide location-specific forecasts. Tests on past storm events confirm that the model can reliably capture short-term fluctuations and provide useful guidance several hours in advance, outperforming existing global indices. This demonstrates that the concept is feasible and raises the technology readiness level to TRL4. The model’s ability to issue probabilistic “watch” and “warning” thresholds offers operators actionable lead times to mitigate risks by redistributing loads or temporarily disconnecting vulnerable equipment.
On the commercial side, the project has clarified the potential market fit of such a tool. Outreach to more than 60 companies across multiple sectors highlighted both challenges and opportunities. The broader societal impact lies in improving resilience to space weather at a time of accelerating electrification. By reducing the probability of blackouts and costly equipment failures, the tool supports critical infrastructure reliability and energy security. It also aligns with several UN Sustainable Development Goals, including affordable and clean energy, resilient infrastructure, and sustainable cities. Economically, even modest improvements in preparedness can prevent multimillion-dollar damages and contribute to long-term grid stability, thus reducing systemic risks for utilities, insurers, and society at large.
The potential impacts extend internationally. As global solar activity increases towards the 2025 maximum, demand for forecasting solutions is expected to grow, and the project positions Norway at the forefront of this emerging market. With further development and testing, the technology could become a key element of critical infrastructure protection, contributing both to national preparedness and to a wider international market for space weather resilience.
