Large-Scale piloting of next-generation AI-driven digital platforms for a more affordable, secure and sustainable European energy system (IA) - Apply AI

From the Commission's own budget table for this call. Confirm against the topic page before you plan around it: these move when a work programme is amended.

Expected Outcome: Projects are expected to contribute to the following outcomes: Strengthened Europe’s technological leadership and sovereignty in the energy sector. Market-ready AI-driven digital platforms and solutions with quantifiable minimal environmental impact, that enhance grid operation, renewable energy integration and utilisation rates, energy storage integration, grid integration of data centres and other energy intensive critical infrastructures, non-fossil, balancing solutions, electrification and energy efficiency, derived from existing and ongoing AI and IoT research. Successfully integrate applied research results in real-world pilot programmes involving energy operators, technology providers, public authorities, and end users. Secure, interoperable, and cross-border data exchange mechanisms and digital services reducing fragmentation. Accelerated scaling of digital solutions leveraging European data spaces, AI factories [1] , digital twins, and cloud-to-edge infrastructures. Credible pathway from innovation to large-scale piloting, ensuring long-term sustainability and scale up. Quantifiable improvements in terms of reduction in greenhouse gas emissions, energy savings, electricity cost reduction and grid flexibility. Scope: This topic will support one large-scale cross-border pilot project demonstrating the operational use of next-generation AI-driven Digital Platforms (DPs) for the European energy system, to optimize electricity system operation and flexibility management cross multiple European energy systems. This pilot forms a core implementation layer of the AI-enabled digital backbone flagship identified in the Apply AI Strategy and contributes to the Strategic Roadmap for Digitalisation and AI in Energy. The project should implement and validate these capabilities through operational pilots in at least six Member States or Associated Countries (ensuring geographic variability and coverage), involving real infrastructure, energy operators and users. The pilot should run for a sufficient duration to demonstrate operational performance under real system conditions (e.g. seasonal variability, renewable generation variability and EV charging patterns). The objective of the pilot is to demonstrate that AI-enabled digital platforms can enable real-time coordination of distributed energy resources and cross-border flexibility services improving grid utilisation, increasing renewable energy integration and reducing system costs and emissions. Proposals should: Develop and pilot at scale next-generation AI-driven digital platforms, critic…