A smarter, more efficient energy future starts with the right people. At Gridraven, we bring together experts from different fields, all working toward the goal of helping solve the global energy bottlenecks.
The Raven is our quarterly magazine, delivering insights on DLR, machine learning, and the technology shaping the future of energy. Published in print and online, it brings news, expert takes, and real-world impact—fast, clear, and always ahead of the curve.
Gridraven is now officially registered in the United States, and we’ve secured €4 million in funding from the VC firms 42CAP and Icebreaker.vc to support our expansion.
Gridraven proudly announces its official expansion into the United States with the registration of Gridraven Inc.
Let's delve into the latest topics, trends, and innovations as seen in the media, shaping the energy landscape and highlighting the critical role DLR plays in this evolution.
Gridraven's machine learning model improves wind speed forecast accuracy by 50% in the Golden State compared to the existing large scale numerical weather predictions. These improvements are fully leveraged in our software-based Dynamic Line Rating solution, leading to increased safety and efficiency in grid operations.
Gridraven’s 2024 has been a year of growth, learning, and validating our technology, but most importantly, it has set the stage for scaling up in 2025.
Henri and I attended CEATI's annual transmission and distribution conference in Palm Springs, California, this November. CEATI is one of the main power industry networks where utility engineers produce technical reports and guidance documents. During the event there are engineering working groups, parallel conference-style presentations, as well as an exhibition floor.
By harnessing machine learning and cutting-edge technology, Gridraven is optimizing energy infrastructure, increasing transmission line capacity, and paving the way for a more efficient energy future. Our Co-Founder and CTO's story underscores the importance of interdisciplinary collaboration and innovation in reshaping the global energy landscape.
We brought together experts from Estonia’s energy sector to discuss electricity prices in Estonia and nearby, what drives them, and how they can be reduced.
At Gridraven, I work with a wide range of geospatial data—weather observations, digital elevation models (DEM), and numerical weather prediction (NWP) models. My job is finding, cleaning, and preparing these datasets to train machine learning models. The end goal? Precise wind forecasts that can help optimize the performance of high-voltage power lines.
Markus Lippus and the team at GridRaven are rethinking grid potential through advanced AI solutions, using machine learning to unlock real-time flexibility in power transmission.
Introducing three key members who drive our projects forward: Eneli Toodu, Sten Buldas, and Juri Krainjukov.
Growing the team to pioneer smarter power grids with AI and innovation.
GridRaven has demonstrated a 50% improvement in accuracy for predicting wind speeds in forested areas.
Every line and every span must be accounted with to increase capacity.
Exploring the parameters that affect our wind predictions.
Ambient Adjusted Ratings can lead to a reduction of capacity.
A single span limits the entire line.
Accurate ratings would help reduce congestion in Texas.
Lack of grid capacity is slowing down affordable energy.
Accurate line ratings ensure safety while increasing capacity.
Predicting wind in sheltered areas.
More transmission capacity means lower prices.
Lack of transmission capacity is slowing the energy transition.
Mari joins as Senior Power Systems Expert and Ingvar as Data Scientist.
Using satellite data to improve line ratings.
A year-long cooperation centered on sharing expertise.
The funding will be used to expand GridRaven's technical team in Tallinn.
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