By Alina Tugend
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While utilities have software available to help plan for daily and future operations, they are not as “smart” and dynamic as are needed.
Enter the Grid Resilience & Intelligence Platform project, known as GRIP. Its goal is to apply machine learning to the power grid by using large amounts of satellite imagery, weather data, smart meter data and other information about utility operations to find and fix problems, such as trees’ growing over power lines, that could cause trouble in storms.
The idea is to “anticipate, absorb and recover from events that cause grid outages, such as extreme weather or a cyberattack,” said Ashley Pilipiszyn, GRIP project lead and a Ph.D. student at Stanford University.
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One Concern, a company based in Menlo Park, Calif., uses artificial intelligence to model and forecast the impact of hazards. It started up in 2015 and has two products on the market: software platforms focused on earthquakes and flooding that are tailored to specific geographic areas to predict hyperlocal damage.
One Concern’s flooding platform, released last year, allows customers — which include cities and the private sector — to predict the depth and flow of flooding on a block-by-block basis up to five days before a potential flood.
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