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Europe faces urgent challenges in energy and AI autonomy due to geopolitical tensions and market volatility, a new study from the European Commission’s DG CONNECT reports.
Commissioned by DG CONNECT to explore the role of AI across all the layers of the energy system, the report points to these pressures necessitating resilient, flexible and sustainable energy systems, with AI, including generative AI (GenAI), central to managing their complexity.
In particular, the study finds that the development of AI factories – of which at least 15 are expected to become operational in the coming months and gigafactories to come – digital twins including the ‘digital spine’ of the energy system and the emerging European energy data space are the key enablers of a real time data-driven energy management system.
“The integration of AI technologies within the European energy sector aligns seamlessly with
the EU’s broader goals for competitiveness and innovation, including through simplification,” the study states.
“By structurally applying AI to manage and optimise interactions within and between energy
systems, the EU can potentially enhance its competitive edge in the global market.”
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Moreover, it adds: “This approach supports the Competitiveness Compass, which emphasises closing the innovation gap and fostering a friendly environment for companies to adopt new technologies such as AI and robotics.”
The study entitled ‘Novel AI applications in the energy sector’ authored by Martin Brynskov, Scientific Director, AI and Digital at the University of Copenhagen and independent researcher to the European Commission, identifies example use cases of AI in each of the three domains – the supply side, the demand side and GenAI powered digital spine.
These are:
- Supply side – in (semi-)autonomous control for renewable energy, for digital twins of the energy production assets and in power plant and infrastructure management.
- Demand side – in demand forecasting, for citizens and energy communities and for energy efficient transportation.
- GenAI powered digital spine – for digital twins of the entire EU electrical grid, in (semi-)automated grid operation, control and management and in transition to renewables and a weather-based energy system.
From these, one in each domain was selected for analysis. On the supply side, AI-supported decentralised distribution, on the demand side, consumer-facing apps were identified as a new focus, and for the GenAI-powered digital spine, resilient and flexible decentralised balancing.
These were found to present a comprehensive approach to enhancing the resilience, efficiency and sustainability of the energy grid.
Combined strengths include enhanced monitoring and control, support for resilience and flexibility, optimisation and efficiency and data integration.
However, there are also weaknesses, including the high computational need, integration complexity and need for data accuracy.
Nevertheless, opportunities presented are the opportunity for regulatory alignment, technological advancements, support for sustainability goals and enhanced market participation.
Combined threats include cybersecurity risks, high system complexity, potential market misalignment and exposure to market volatility.
In conclusion, the study highlights the need for the EU to invest in AI factories and complementary model development networks enabling low latency, scalable inference across distributed nodes as foundational infrastructure.
These investments should be accompanied by efforts to standardise trusted data and model transactions, ensure cybersecurity and foster collaboration between research institutions, industry, and policymakers.
Together, these measures will enable the EU to build a more intelligent, flexible, and sustainable energy future, the study concludes.
Originally published on Enlit World.
