LF Energy, a Linux Foundation initiative that brings the energy sector together to develop the digital foundation for energy through open source software, standards, and data, received $2.5 million in funding from Google.org this week to accelerate the development and adoption of open-source tools for Europe's electricity grids.
Europe's electricity grids are being asked to carry more renewable generation, electrified heating and transport and data centre demand than they were built for, and new lines cannot be permitted and built quickly enough to keep pace. In the near term, grid operators must maximise use of the capacity they already have, which depends on technology to observe, model and forecast their networks.
Rather than building new technology from scratch, this funding will help further develop existing open-source AI solutions to address local grid needs and drive adoption across Europe, especially for smaller and lower-resourced operators and regions.
The funding will advance AI-ready grid data, faster power system modelling and more accurate energy forecasting through four LF Energy projects:
OpenSynth: An open data community that gives researchers and grid planners realistic energy data without exposing customer information, so they can study how heat pumps, electric vehicles (EVs) and solar will affect local grids. It includes 10 million AI-generated synthetic household load profiles and real French transmission grid topology published by RTE
PowSyBl: A modular framework for transmission grid analysis that helps operators manage congestion and plan grid reinforcements and new renewable connections. RTE in France and TenneT in the Netherlands use it in production, and TenneT built a PowSyBl-based solution in five months that improved calculation performance tenfold.
Power Grid Model: A high-performance calculation engine for distribution grids that runs thousands of scenarios at once, so operators can see where growth in EVs, heat pumps and solar will overload local networks and plan ahead. It has passed 10 million downloads and is used and developed by Dutch distribution operators Alliander, Enexis and Stedin.
OpenSTEF: A machine learning framework that forecasts electricity load and generation from minutes to days ahead, giving operators time to head off congestion and put spare grid capacity to use for flexible loads, such as EV charging. Alliander uses it to forecast grid congestion and Sigholm uses it to plan district heating production.
"AI will only be as useful to grid operators as the data and models it is built on," said Alex Thornton, executive director of LF Energy.
"This grant from Google.org via INCO invests in that foundation: open data, grid models and forecasting tools that operators across Europe can build on. Because the work is open source, its benefits reach every operator, not only those with the resources to develop these capabilities themselves."
“Supporting a reliable, resilient power grid requires not just new physical infrastructure, but open digital tools that help operators get more out of the grid capacity we already have. Through this $2.5 million in Google.org funding to Linux Foundation Europe, we’re proud to support LF Energy in scaling open source data, modelling and AI forecasting tools—helping grid operators of every size across Europe modernise grid planning and unlock more affordable, reliable, and clean energy for everyone,” said Adam Elman, Director of Sustainability, EMEA at Google.
Beyond technical development, the funding will support technical guides and implementation resources, training courses, workshops co-located with LF Energy Summit Europe and translations into various EU languages.
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