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Official call identifier: HORIZON-CL5-2026-11-D3-23
Objective of the call
This call aims to enable large-scale, secure and interoperable data sharing to support the development and training of AI foundation models for the energy sector.
It seeks to accelerate the digitalisation of the energy system by improving grid observability, forecasting, storage and renewables integration, flexibility management and energy efficiency.
Projects are expected to develop scalable data governance strategies and open-source AI models aligned with FAIR principles.
Scope of activities
Proposals must address all of the following:
- Develop and test AI foundation models for the energy sector, using extensive and representative datasets
- Demonstrate access to large and relevant datasets at the time of proposal submission
- Build on results from previously funded projects on the Common European Energy Data Space and the Data 4 Energy expert group
- Develop secure, transparent and scalable data governance strategies, including approaches such as data space connectors, federated model training, synthetic data generation or other innovative mechanisms (e.g. AI gym environments)
- Ensure that data governance solutions remain operational and scalable beyond the project duration
AI foundation models must address at least one of the following use cases:
- Planning and operation of electricity grids (including static power flow and dynamic EMT modelling)
- Supply and demand forecasting
- Congestion management
- Anomaly detection and fault diagnosis
- Predictive maintenance
- Flexibility management
- Demand-side energy efficiency
- Smart and bidirectional EV charging
- Other use cases contributing to energy system digitalisation
Projects must validate models through laboratory demonstrators and real-life pilots, potentially using AI Testing and Experimentation Facilities (TEFs) and regulatory sandboxes.
Consortia must bring together data owners (e.g. utilities, grid operators), application developers (e.g. SMEs, start-ups, hyperscalers) and model deployers (e.g. industry, equipment manufacturers).
AI development must embed transparency, explainability, accountability, privacy and security by design. Open-source development practices should be pursued where feasible. Bias mitigation and representativeness of data must be ensured.
Selected projects are expected to contribute to the BRIDGE initiative.
Eligible applicants
- Innovative SMEs, startups and enterprises aiming to scale and strengthen competitiveness
- Public-sector organisations driving transformation and societal impact
- Research and academic institutions commercialising knowledge
- Non-profit organisations delivering purpose-driven innovation
- Organisations based in EU Member States, EFTA/EEA, or Associated Countries (described in General Annex A, General Annex B, General Annex C)
- Minimum 3 independent partners from 3 eligible countries
Specific consortium we are looking for:
- Energy utilities and grid operators
- Energy asset owners
- AI developers and digital solution providers
- SMEs and start-ups active in AI and energy technologies
- Equipment manufacturers
- Research and technology organisations
- Data infrastructure and platform providers
Applicants must form consortia covering the full data-to-deployment value chain.
Eligible costs
Eligible costs follow standard Horizon Europe Innovation Action (IA) rules and may include:
- AI model development and training
- Data acquisition, preparation and governance implementation
- Federated learning or secure data-sharing infrastructure
- Laboratory testing and real-life pilot validation
- Integration with AI factories or testing facilities
- Dissemination, interoperability and standardisation activities
Funding conditions
Type of action:
Innovation Action (IA)
Funding rate:
70% of eligible costs (except for non-profit legal entities, where a rate of up to 100% applies)
EU contribution per project:
Around EUR 10 million
Number of funded projects:
3 projects
Project duration:
Typically 36 months
Technology Readiness Level (TRL):
Activities are expected to achieve TRL 7-8
*Technology Readiness Levels (TRL) describe the maturity of a technology, from basic research (TRL 1) to fully deployed, market-ready solutions (TRL 9).
Deadline for submission
1 December 2026