Data sharing to support the training and development of AI foundation models in the energy sector
Horizon Europe · Grant topic
Summary
A Polish company can use this call for R&D.
Funds international consortia with existing dataset access developing energy foundation models, secure data-sharing methods, laboratory demonstrators and real-life pilots.
- Who can apply
- Companies can lead: SME, large company, research org, university.
- Amount
- €30,000,000Indicative budget
- Deadline
- 01 Dec 2026 01:00 CETin 38 days
- Status
- Openopened 4 Aug 2026
Machine-classified from the call text; check eligibility at the source.
Description
Expected Outcome:
Projects are expected to contribute to all the following expected outcomes:
• Effective and innovative methods for gathering, sharing and using large data sets in energy applications for the purpose of training AI models while ensuring privacy and security.
• Advanced and - wherever possible - open-source AI foundation models to support the digitalisation of the energy system, through improved grid observability, forecasting of supply and demand, advanced storage and renewables integration, demand side flexibility and energy efficiency.
• Enhanced cooperation, knowledge sharing and interoperability among energy system actors for secure and seamless data exchange.
• Advanced methodologies for AI model development ensuring that the results are FAIR (Findable, Accessible, Interoperable, Reusable) beyond the project ending, open source and accommodating for technology evolution.
Scope:
The quality of AI models depends strongly on the amount, quality, and representativeness of the data used for their training. Projects are expected to focus on developing, training and testing AI foundation models, using extensive data sets to accelerate the energy transition in key focus areas of the energy sector. Projects are expected to:
• Building on the results of previously funded projects on the Common European energy data space[1] as well as the ongoing work within the Data 4 Energy expert group, projects are expected to demonstrate innovative methods and data governance strategies for sharing data among various energy actors. Projects are expected to demonstrate that they have access to large relevant datasets at the time of submitting the proposal.
• Projects are expected to develop innovative strategies for sharing data in an effective, secure and transparent way to support the development of AI foundation models. An indicative non exhaustive list of strategies that can be explored is the use of data space connectors or federated training of models to allow the integration of confidential data; the creation of synthetic data as an intermediate step to fill data gaps or improve the quality of the data could also be explored. Projects could also explore other innovative data sharing strategies, such as an ‘AI gym’. The data governance strategies that will be developed in the project should be designed in a way to be scalable and operational even after the end of the project.
• Projects are expected to develop foundation models tailored for the energy sector, addressing at least one -or more- of the following use cases: planning and operation of electricity grids (including static power flow modelling and dynamic EMT modelling), forecasting, congestion management, anomaly detection, fault diagnosis, predictive maintenance, flexibility management, demand-side energy efficiency, smart and bidirectional charging of EVs or other use cases that contribute to the objective of digitalisation of the energy system.
• Projects are expected to perform in-depth testing and validation of developed foundation models in lab demonstrators and real-life pilots, building on the results and using the facilities of previously funded projects on “AI testing and experimentation facilities (TEFs)”[2]. Regulatory sandboxes could also be considered for real-life pilot implementations.
• Projects are expected to bring together a wide group of stakeholders including data owners (for example energy utilities, grid operators, asset owners), application developers (for example startups, SMEs, hyperscalers) and model deployers (for example industry, grid operators, equipment manufacturers) providing a space of cooperation and collaborative data exchange.
• To scale up the training and development of the models, projects can benefit from the computing capacity of the AI factories that were recently announced by the European Commission[3], in particular the three AI factories that aim to develop AI applications for the energy sector.
• AI models are expected to respect ethical, safety and security principles; furthermore, transparency, explainability, and accountability should be embedded by design in the model development. Open-source development practices should be pursued wherever feasible. Efforts should be made to avoid biases, ensuring that the data produced is representative of diverse populations.
Selected projects are expected to contribute to the BRIDGE initiative[4] and actively participate in its activities.
Technology Readiness Level - Technology readiness level expected from completed projects
Activities are expected to achieve TRL 7-8 by the end of the project – see General Annex B. Activities may start at any TRL.
[1] Establish the grounds for a common European energy data space
[2] AI Testing and Experimentation Facility (TEF) for the energy sector – bringing technology to the market
[3] AI Factories
[4] https://bridge-smart-grid-storage-systems-digital-projects.ec.europa.eu/
Who can apply, in detail
- Applicant types
- SME, Large company, Research org, University
- Purpose
- Research and innovation
- R&D relevance
- 3 of 3
- Poland eligible
- Yes
- Country limit
- Consortium must include entities from at least three countries, including at least one EU Member State.
- Region
- Any
- Consortium
- Required
- Readiness level (TRL)
- 7-8
- Topics
- Energy foundation models
- Secure data sharing
- Privacy-preserving AI
- Grid forecasting
- Energy system digitalisation
Machine-classified from the call text; check eligibility at the source. 23 Oct 2026
Conditions
Typed facts extracted from the source documents by Scindu's grant-data review. Each value keeps its own conditions. Unknown means unstated, not zero or unlimited.
- Applicant type
- At least three independent beneficiary legal entities established in different countries are required unless topic-specific conditions say otherwise: at least one in an EU Member State and two others in different Member States or Associated Countries.
- Eligible project scope
- Proposals should already have access to large relevant datasets when submitted, develop energy-sector foundation models for at least one use case, test them in lab demonstrators and real-life pilots, and bring together data owners, application developers and model deployers.
- Other condition
- Models are expected to respect ethical, safety and security principles and embed transparency, explainability and accountability by design; open-source is pursued wherever feasible.
- Other condition
- Selected projects are expected to contribute to and actively participate in the BRIDGE initiative.
- Other condition
- HORIZON-CL5-2026-11 ENERGY opens 4 August 2026 and closes 1 December 2026 at 17:00 Brussels local time. The Work Programme permits the Director-General to adjust opening/deadline dates within the stated limits.
- Other condition
- The Commission estimates around EUR 10.00 million in EU contribution per project. This is an estimate, not a fixed project ceiling or floor; the Work Programme says different requested amounts are not precluded.
- Other condition
- The ENERGY call overview lists around EUR 10.00 million expected EU contribution per project and an indicative 3 projects expected to be funded for this topic. These are planning estimates, not guaranteed awards.
- Other condition
- If personnel receive project-based supplementary remuneration, the rate is capped by the beneficiary’s national-project reference and must be based on objective criteria and consistent usual practice; where no valid reference or objective criteria exist, the MGA supplies a fallback reference. This conditional rule is not a topic-specific salary amount.
- Other condition
- Conditional eligibility rule: if the project uses satellite EO/positioning/navigation/timing data or services, beneficiaries must use Copernicus and/or Galileo/EGNOS; additional sources may also be used.
- Other condition
- The reviewed call/topic does not name occupations, degrees, FTE, project hire counts, staff contract lengths, or salary caps. The budget-based MGA permits the conditional personnel categories documented above; project-specific staffing and compensation remain proposal/budget-dependent.
- Technology readiness level at end, maximum
- 8 TRL
Expected range stated by the topic for end-of-action readiness; activities may start at any TRL.
- Technology readiness level at end, minimum
- 7 TRL
Expected range stated by the topic for end-of-action readiness; activities may start at any TRL.
Amounts and costs
- Indicative budget
- €30,000,000
Topic budget as stated in the portal's budget table. Lump-sum and per-project limits are in the call conditions.
- Call allocation
- €132
Overall indicative call budget in the official Work Programme; subject to availability of EU appropriations.
- Eligible cost
- For the budget-based Horizon Europe action grant, personnel costs can include employees/equivalents assigned under an employment contract or appointing act; qualifying direct-contract natural persons and paid secondments under employee-like working conditions (with beneficiary ownership of results unless agreed otherwise); and, as a unit cost, non-salaried SME owners or natural-person beneficiaries. Eligibility remains subject to the MGA general conditions.
- Eligible cost
- For employee/equivalent personnel on actual-cost basis, the daily rate is annual personnel costs divided by 215 and multiplied by action day-equivalents; a person’s annual day-equivalents declared across EU grants may not exceed 215 minus parental-leave time. This is a cost-calculation rule, not a market salary ceiling.
- Topic allocation
- €30,000,000
Indicative topic allocation, not a guaranteed amount to one beneficiary.
Personnel and services
Other role
Staff cost the grant can fund
Generic potential personnel category for a budget-based action only. The topic does not set a headcount, FTE, duration, occupation, or salary amount; project-specific necessity and staffing plans are not stated.
Source documents
Call facts
- Opens
- 4 Aug 2026
- Deadline model
- Single-stage
- Programme
- Horizon Europe · 2021 - 2027
- Call
- HORIZON-CL5-2026-11 · ENERGY
- Types of action
- HORIZON Innovation Actions
- Source
- ec.europa.eu
- Checked
- 24 Oct 2026
- Portal updated
- 3 Aug 2026
- Review status
- Partial review
- Reviewed
- 22 Oct 2026
This is a summary of the source page, not the official text. Eligibility, conditions and the submission system are at the source.