Estonian start-up Gridraven uses machine learning and LiDAR terrain maps to predict exactly how much electricity a power line can safely carry. Now it wants to sell these insights in the US
An Estonian start-up is using machine learning to squeeze more capacity out of existing power lines – and now it wants to dominate the American grid, writes Delfi.
The problem Georg Rute and his colleagues at Gridravenare solving is known as dynamic line rating (DLR): the ability to accurately predict how much electricity a power line can carry at any given moment. The physics are straightforward – when wind blows across a line, it cools it down, allowing more current to pass through safely. The challenge is knowing, two days in advance and at every point along a line’s length, exactly how hard the wind will blow.
Without that precision, grid operators are stuck choosing between underutilising their networks and risking overheated cables. Too much guesswork in the optimistic direction, and the line fails.
A problem decades in the making
Gridraven’s approach combines three data sources: weather forecasts from Norwegian service Yr.no (accurate to within one metre per second for wind), LiDAR-generated terrain maps that capture the wind-slowing effect of trees, buildings, and topography down to one-metre resolution, and a machine learning model that synthesises the two to produce a localised wind forecast for a specific line, at a specific time.
The technology has been a long time coming. Rute, who previously worked at Estonian transmission system operator Elering, recalls the organisation trialling line sensors as far back as 2011 – they broke within four months. A 2018 attempt using weather stations on transmission masts, in collaboration with the University of Tartu, found that standard weather forecasts correlated poorly with actual conditions at the mast. “About 40 per cent of the time the number would have been wrong,” Rute said.
Gridraven was founded in 2023 to take another run at the problem, with machine learning co-founder Markus Lippusjoining on the basis that weather forecast data contained enough signal for a model to learn from.
Fingrid is already seeing results
Finnish grid operator Fingrid has now adopted the technology in live operations. Even with a deliberately conservative approach – Gridraven deliberately avoids over-promising capacity to prevent cable overloads – the system is already delivering a 10% efficiency gain for Fingrid. The company’s website cites figures of up to 30%, though Rute notes that the baseline assumptions used by different grid operators vary widely; some assume zero wind speed as a worst-case starting point, which naturally inflates the improvement figure when a more realistic number is applied.
“What we always try to avoid is saying we can push twice as much electricity through, the grid does it, and we were wrong. That means the cable gets damaged. We are very conservative,” Rute said.
As for competition, Rute names General Electric and Siemens without hesitation – but adds that on paper is where the similarity ends. He claims Gridraven covers more live operational lines than any other provider globally, when pilots and trials are excluded from the count. Two German companies have built their own internal solutions; one US competitor has five lines under management.
Texas first, then the rest of the country
With that position established, Gridraven is now looking at the United States. Grid operators in each country tend to be natural monopolies and typically convene in sector-wide forums – meaning a single high-profile contract can rapidly build credibility across an entire market.
“We’re about to close our first contract in Texas – then the whole of the US will know about us. Our hope is that within the next year, we take over the entire US market,” Rute said.
The company is not currently planning a new fundraising round. It raised approximately €4M at the start of last year and has runway through to the end of 2026.
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