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GE Vernova: Grid disruption intelligence and wildfire risk management

4 June 2026
    AI‑Enabled Assessment and Management of Wildfire and Extreme‑Event Risks for Utility Grids

    Context

    Utilities operate in service territories exposed to disruption events, including wildfires, across generation, distribution, and transmission activities. The operating environment requires preparedness for disruption impacts on grid assets and customer service continuity.

    Challenge

    Wildfires caused up to 68.4 billion USD in damage in the US between 2018 to 2022. The number of wildfires increased by +30% during the last years. Utilities need capabilities to manage disruptions proactively and reactively to improve grid sustainability, reliability, security, and resiliency.

    AI Solution

    The solution uses Generative AI and Machine Learning to assess wildfire risk, and assess risk from other disruptions such as flooding, for the utility service territory. The system assesses potential impact on utility assets, predicts outages and impacted customers, and supports decisions on proactive actions such as auto-deploying crews. The solution can be delivered as a cloud offering either as SaaS (Software as a Service) or as a managed services offering.

    Impact & evidence

    Impact is measured through short time to resolution in case of a disruption through to pro-active measures, higher customer experience / satisfaction through faster resolutions and pre-active resolution activities and high grid stability & resiliency.

    Implementation / Adoption

    The solution can be deployed with standard integration uses APIs (Application Programming Interface), SDKs (Software Development Kit), and connectors. Replicability requires a grid-aware data foundation and a trusted state for grid topology at all time. Required data quality work includes cleansing. Typical implementation time is less than 6 weeks.

    Data

    Network topology and asset data are used alongside weather forecast, satellites HS, and wildfire data sets. Validation uses predicted number of outages, predicted number of impacted customers, and predicted time to restore, with predictions compared to reality.

    Future enhancements

    Various disruptions, including flooding, storms, wildfire, blizzards, and heavy rain will be supported under future enhancements.

    Additional information

    https://marketplace.microsoft.com/en-us/product/ge_vernova.gridos-disruption-prepare?tab=overview

    https://www.gevernova.com/software/blog/power-grid-disruption-grid-orchestration-software

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