AI-powered software could recover 300GW of hidden capacity for the US power grid, enough to power thousands of AI data centers
Hidden power grid capacity could solve America's AI electricity crunch
- AI software claims hidden grid capacity could ease America's growing electricity shortage
- GridCARE says simulations reveal unused transmission capacity across existing power infrastructure
- Existing transmission lines may hold far more capacity than previously estimated
A new software platform claims it can unlock roughly 300 gigawatts of hidden electrical transmission capacity across the existing United States power grid within three to five years.
The technology, developed by GridCARE and led by founder and CEO Amit Narayan, relies on advanced grid modelling rather than costly new infrastructure.
Instead of building additional transmission lines or substations, the platform analyzes how the grid actually operates in real time.
Unlocking hidden capacity
The US power grid has traditionally been planned around conservative assumptions that account for multiple simultaneous equipment failures at once.
This approach has left substantial portions of the transmission network underused for most of the calendar year, while electricity demand has resumed growing sharply, and grid upgrades may struggle to keep pace before 2030.
Bank of America data indicates the country could face a 100 GW power shortfall within the next four years.
Analysts project at least 230 GW of new power demand will emerge between 2026 and 2030 alone.
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During the same period, utilities are expected to add only 93 GW of new supply capacity.
That gap between projected demand and available supply has intensified pressure on operators searching for faster solutions.
However, GridCARE claims it could cut years from clean energy interconnection wait times across multiple regions.
Running quadrillions of simulations
The platform reportedly runs quadrillions of simulations to identify where unused transmission capacity remains hidden from conventional planning tools.
By modelling actual grid behaviour rather than worst-case scenarios, utilities gain a more accurate picture of available headroom.
This method allows operators to make better use of infrastructure that already exists across the network.
The technology was recently discussed on the "Energy Empire" podcast, hosted by Jigar Shah, a US entrepreneur and former director of the Department of Energy's Loan Programs Office.
According to Narayan, the 300 GW figure represents capacity that traditional planning methods have consistently overlooked for years.
He claims that recovering even a fraction of that capacity could meaningfully ease constraints facing data center developers and clean energy projects awaiting grid connection.
The claims arrive as pressure mounts on grid operators to accommodate rising demand from artificial intelligence infrastructure and electrification trends nationwide.
However, no independent testing or verification has confirmed the software's claims about the extent of its capabilities.
Utilities have historically been cautious about departing from conservative planning standards that prioritize reliability during equipment failures.
Still, the scale of the projected shortfall — combined with slow transmission buildout timelines — may push operators toward faster, software-based alternatives sooner than expected.
Via PV Magazine
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Efosa has been writing about technology for over 7 years, initially driven by curiosity but now fueled by a strong passion for the field. He holds both a Master's and a PhD in sciences, which provided him with a solid foundation in analytical thinking.
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