One of the biggest roadblocks to clean energy in the U.S. isn’t a lack of wind or solar power — it’s an outdated grid that can’t keep up.

Gridraven, an Estonian startup, is tackling that problem with AI-powered weather modeling, and it just secured €4 million to bring its tech to the U.S., reported CleanTechnica.

The U.S. grid wasn’t built to handle the surge of renewable energy, leading to frequent bottlenecks and curtailments — when clean electricity goes unused because transmission lines are at capacity.

“The current U.S. transmission system will need to be upgraded and expanded to make it possible to carry larger amounts of clean energy across longer distances,” the U.S. Department of Energy’s National Renewable Energy Laboratory (NREL) warned in May.

Right now, power lines operate with built-in safety margins, meaning they don’t always carry as much electricity as they could. Utilities typically use seasonal estimates to decide capacity, but this approach leaves a lot of potential power untapped.

Some companies are trying to fix that by installing physical sensors on transmission lines — a process called dynamic line rating (DLR) — to adjust capacity in real time. But adding hardware to thousands of miles of power lines is expensive and slow.

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Gridraven offers an alternative: ditch the sensors and use AI instead. By predicting real-time weather conditions, its technology continuously adjusts transmission capacity on the fly. That means more electricity can move through existing lines — up to 30% more on average, and sometimes even 50% when winds are strong.

This is a game changer for renewable energy. One of the biggest hurdles in transitioning to clean power isn’t generating it — it’s getting it where it needs to go. Instead of waiting years for costly new infrastructure, Gridraven’s software makes better use of what’s already in place.

While AI-driven transmission tech is still new in the U.S., Gridraven has already tested its system abroad. In Estonia, where dense forests make conventional forecasting unreliable, the company ran a pilot project on a live transmission line. Gridraven’s AI improved forecast accuracy by 60% over existing methods, increasing line capacity by 30%.

“Our solution increases the capacity of overhead lines by up to 30% annually — sometimes as much as 50% during windy periods — without requiring new infrastructure,” said Gridraven CTO and co-founder Dr. Henri Manninen.

With fresh investment from European venture capital firms like 42CAP and Icebreaker, the company is setting up operations in Austin, Texas — a smart choice given the state’s leadership in wind and solar power.

The Department of Energy has identified dynamic line rating as a crucial tool for making renewable energy more reliable and reducing costly curtailments. During extreme weather events, when traditional power plants struggle to keep up, AI-driven solutions like Gridraven’s could help ensure that more clean electricity reaches homes and businesses.

“In a situation like this, dynamic line ratings could allow grid operators to increase line ratings that were determined during a typical, warm day to match the reality during periods of extreme cold weather,” elaborated NREL senior research fellow Paul Denholm. “This simple change could provide much-needed power to people that might not otherwise have it.”

Utilities are starting to take notice. Companies in Nevada and Georgia are exploring dynamic line rating technology, and in New York, National Grid has already implemented sensor-based DLR to boost renewable energy transmission.

With AI-powered solutions like Gridraven’s entering the mix, the transition to a more flexible and resilient grid could happen even faster.

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