šŸ“Œ EIC Transition OpenĀ 

FutureGrid Intelligence Transition

šŸ’° Budget:Ā  (minimum: €500K, maximum: €3M) | ā³ Duration:Ā  (minimum: 24, maximum: 36) | šŸ“… Deadline: 17/09/2025

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Short Idea:Ā 

FutureGrid Intelligence Transition aims to evolve Adaion’s high‐fidelity digital twin and AI-powered diagnostics from laboratory proof-of-concept to a fully validated demonstrator (TRL 5-6) in real grid environments. By integrating advanced GIS/AMI data fusion, scenario simulation and iterative user-testing, the project will deliver a robust, market-ready tool for smarter grid operations and efficient investment decisions.

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Abstract

FutureGrid Intelligence Transition is an ambitious project focused on taking Adaion’s established digital twin platform and associated AI-driven diagnostic tools beyond the laboratory, toward full operational deployment within actual grid environments. The proposal seeks to mature the technology from TRL 4 to TRL 5-6 through a series of iterative and user-centric development cycles. In recent years, grid operators have faced increasing challenges due to the rising complexity of energy infrastructures. Adaion’s integrated approach—merging detailed GIS and AMI data with real-time digital simulation—has already proven its potential to deliver critical insights for grid management. Now, through FutureGrid, we will enhance these capabilities by implementing advanced scenario-based simulations, refined diagnostics, and robust validation testing in realistic operational contexts.

The project is organized into a comprehensive series of work packages combining technology and market development. Initially, our consortium will focus on strengthening project management, ensuring close collaboration between technical teams and end-users. This is followed by focused activities to upgrade the digital twin platform, incorporating enhanced AI algorithms and real-world diagnostics that provide actionable insights for timely decision-making in grid operations. Concurrent with technology enhancement, iterative cycles of user feedback and field testing will drive improvements. Validation experiments in actual grid settings will be executed in collaboration with utilities, ensuring that the technology meets both technical requirements and market demands.

Market and business model development is integrated into the project to create a sustainable path to commercialization. This will include developing strategic partnerships, aligning regulatory compliance, and establishing clear market pathways. Finally, rigorous impact assessment and effective dissemination strategies will amplify the project’s results, ensuring widespread adoption of an optimized, future-ready grid management solution. Overall, FutureGrid Intelligence Transition will not only yield a demonstrator platform that significantly reduces grid downtime and boosts operational productivity but also paves the way for a resilient, smart energy future informed by data-driven decision-making.

Who’s Behind?

Key Partners

Country: [Country of Adaion, e.g., Denmark]

Organization Scope: Company

Role in the Project: Project Coordinator and WP Leader for Project Management

Country: Germany

Organization Scope: Research Center

Role in the Project: Technology Partner and WP Leader for Data Integration and Validation

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Country: France

Organization Scope: Company

Role in the Project: Technical Expert supporting Digital Twin enhancement and AI diagnostics

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Country: United Kingdom

Organization Scope: University

Role in the Project: User Testing and Simulation Leader (WP Leader for Advanced Scenario Simulation and User Testing)

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