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Completed TRL 4 (started at 2, targeting 4)
The reliability and resilience of the national electrical grid is a matter of both national security and quality of life. However, the grid is highly vulnerable to damage and outages due to extreme weather; a problem that is expected to worsen in the face of climate change. Storm restoration is a major expense for utility companies, with U.S. power companies alone spending on average $55 billion annually on storm response and restoration of infrastructure, a number that could be decreased significantly with better information on the threat of vegetation near vulnerable infrastructure. StormImpact Inc. will use NASA Earth Science data to build machine learning (ML) vegetation growth and vegetation risk models that will allow electrical utilities to proactively prepare for storms and improve the resilience of the electrical infrastructure to climate change. In addition, the NASA remote sensing data and vegetation ML model outputs will be ingested into our current suite of storm outage ML models. We anticipate cost savings of 10% to 20% for our utility customers due to improved vegetation management efficiency and greater power system reliability based on improved damage and outage predictions in advance of storms.
NASA benefits: This Phase I R/R&D project is responsive to the SBIR Ignite solicitation request for "Technologies Using NASA Data to Foster Climate Resilience." The vegetation growth and vegetation risk products that we are developing have applications for assessing infrastructure damage and wildfire risk. Non-NASA benefits: Vegetation management products will address a gap in the market by providing electrical utilities with accurate and cost-effective guidance so that they can identify when and where there are vegetation management issues. In addition, there are markets and applications for these products such as wildfire risk management, insurance, and forestry.
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