Tender Match
EU · in EnglishHORIZON-CL5-2027-02-D3-24

Large scale operational validation and upscaling of state-of-the-art (Generative) AI tools and models powering a next generation digital energy system

Expected Outcome: Project results are expected to contribute to all the following expected outcomes: Advanced, secure frugal (energy-, resource-, data- and cost-efficient, sustainable) AI tools for real-time grid operations (including protection), market operations (if relevant) and consumer empowerment in distributed energy systems. A demonstrated AI development environment integrated with the up

The official English text of the call comes from the European Commission's Funding & Tenders portal.

Deadline

31 March 2027 Opens 3 December 2026

Grant per project

10 million EURTotal budget: 20 million EUR · about 2 funded projects

Region

International (EU)

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Eligibility criteria

EU direct call: eligibility depends mainly on the consortium, the participants' countries and their types of organisation. We cannot check these from your company details, so we do not tell you whether you are eligible. The criteria are in the official call.

Official call

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What is this call about?

Ez az uniós pályázat mesterséges intelligencia alapú eszközök fejlesztésére és tesztelésére irányul az energiarendszer digitalizációjában, különösen a hálózati működés, piaci folyamatok és fogyasztói alkalmazások terén. A támogatás olyan nyílt forráskódú AI-megoldások létrehozására használható, amelyek energiahatékonyak, költségkímélők és helyi szinten telepíthetők. A projekt konzorciumok számára nyitott, és olyan fejlesztésekhez illik, amelyek az európai energiarendszer intelligens, biztonságos és fenntartható átalakítását támogatják.

Official description

Expected outcome and scope

Expected Outcome: Project results are expected to contribute to all the following expected outcomes: Advanced, secure frugal (energy-, resource-, data- and cost-efficient, sustainable) AI tools for real-time grid operations (including protection), market operations (if relevant) and consumer empowerment in distributed energy systems. A demonstrated AI development environment integrated with the upgraded digital spine of the energy system and energy-saving consumer applications. Scaled-up capabilities for learning at edge nodes and federated systems using agent-based architectures.

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