Data sharing to support the training and development of AI foundation models in the energy sector
Overview
The grant opportunity titled "Data sharing to support the training and development of AI foundation models in the energy sector" (HORIZON-CL5-2026-11-D3-23) falls under the Horizon Europe program. This is an Innovation Action grant, with a total budget of €30 million, expected to fund around three projects with each grant amounting to €10 million. The call opens on August 4, 2026, and the submission deadline is December 1, 2026.
Eligible applicants include a diverse group of stakeholders in the energy sector such as energy utilities, grid operators, asset owners, application developers (startups, SMEs), model deployers (industry participants, equipment manufacturers), research institutions, and digital infrastructure providers. A consortium approach is strongly encouraged to foster collaboration, though it is not explicitly mandatory.
The geographic eligibility extends to all EU member states and associated countries, with specific provisions for non-EU countries potentially under certain conditions. Projects should aim to develop, validate, and demonstrate AI foundation models targeting various applications in the energy sector, including grid operations, demand-side energy efficiency, and renewable energy integration.
Successful proposals are expected to focus on innovative methods for gathering, sharing, and utilizing large datasets while ensuring data privacy and security. The projects should also aim to develop advanced, open-source AI foundation models for various energy applications, ensuring interoperability and cooperative governance among different actors in the energy ecosystem.
In-depth testing and validation of AI models are required through lab demonstrators and real-life pilots, leveraging previously funded testing facilities. Projects must demonstrate access to substantial energy datasets at proposal submission and consider ethical principles including transparency and accountability in AI development.
The evaluation process for submissions will occur in a single-stage with specific criteria outlined in the Horizon Europe Work Programme. Historical success rates are not disclosed, but the competitive nature of funding suggests a potential success rate in the range of 10-39%. Although a co-funding requirement is not explicitly stated, co-funding through in-kind contributions or partnerships is common in such calls.
Overall, this opportunity represents a strategic funding initiative aimed at enhancing AI capabilities in the energy sector, aligning with the EU's digitalization and environmental goals. It invites large, well-coordinated consortia that can effectively leverage diverse datasets and collaborative partnerships to drive innovation in energy technology.
Eligible applicants include a diverse group of stakeholders in the energy sector such as energy utilities, grid operators, asset owners, application developers (startups, SMEs), model deployers (industry participants, equipment manufacturers), research institutions, and digital infrastructure providers. A consortium approach is strongly encouraged to foster collaboration, though it is not explicitly mandatory.
The geographic eligibility extends to all EU member states and associated countries, with specific provisions for non-EU countries potentially under certain conditions. Projects should aim to develop, validate, and demonstrate AI foundation models targeting various applications in the energy sector, including grid operations, demand-side energy efficiency, and renewable energy integration.
Successful proposals are expected to focus on innovative methods for gathering, sharing, and utilizing large datasets while ensuring data privacy and security. The projects should also aim to develop advanced, open-source AI foundation models for various energy applications, ensuring interoperability and cooperative governance among different actors in the energy ecosystem.
In-depth testing and validation of AI models are required through lab demonstrators and real-life pilots, leveraging previously funded testing facilities. Projects must demonstrate access to substantial energy datasets at proposal submission and consider ethical principles including transparency and accountability in AI development.
The evaluation process for submissions will occur in a single-stage with specific criteria outlined in the Horizon Europe Work Programme. Historical success rates are not disclosed, but the competitive nature of funding suggests a potential success rate in the range of 10-39%. Although a co-funding requirement is not explicitly stated, co-funding through in-kind contributions or partnerships is common in such calls.
Overall, this opportunity represents a strategic funding initiative aimed at enhancing AI capabilities in the energy sector, aligning with the EU's digitalization and environmental goals. It invites large, well-coordinated consortia that can effectively leverage diverse datasets and collaborative partnerships to drive innovation in energy technology.
Detail
This is a description of the EU funding opportunity HORIZON-CL5-2026-11-D3-23, titled "Data sharing to support the training and development of AI foundation models in the energy sector". This opportunity falls under the Horizon Europe (HORIZON) program, specifically the ENERGY (HORIZON-CL5-2026-11) call. It is a HORIZON Innovation Action (HORIZON-IA) with a HORIZON Action Grant Budget-Based [HORIZON-AG] Model Grant Agreement (MGA). The deadline model is single-stage. The planned opening date is 04 August 2026, and the deadline is 01 December 2026 at 17:00:00 Brussels time. The budget for this topic is 30,000,000 EUR in 2026, and the indicative number of grants is around 3, with an estimated contribution of 10,000,000 EUR per grant.
The expected outcomes of projects funded under this topic include:
Effective and innovative methods for gathering, sharing, and using large datasets in energy applications for 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.
The scope of this funding opportunity focuses on developing, training, and testing AI foundation models using extensive datasets to accelerate the energy transition in key focus areas of the energy sector. Projects are expected to:
Build on the results of previously funded projects on the Common European energy data space and the ongoing work within the Data 4 Energy expert group, demonstrating 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.
Develop innovative strategies for sharing data in an effective, secure, and transparent way to support the development of AI foundation models. Strategies may include data space connectors, federated training of models, creation of synthetic data, or an ‘AI gym’. The data governance strategies should be scalable and operational even after the project ends.
Develop foundation models tailored for the energy sector, addressing use cases such as: 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.
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)”. Regulatory sandboxes could also be considered for real-life pilot implementations.
Bring together a wide group of stakeholders including data owners (e.g., energy utilities, grid operators, asset owners), application developers (e.g., startups, SMEs, hyperscalers), and model deployers (e.g., industry, grid operators, equipment manufacturers), providing a space of cooperation and collaborative data exchange.
Benefit from the computing capacity of the AI factories announced by the European Commission, particularly the three AI factories that aim to develop AI applications for the energy sector, to scale up the training and development of the models.
Ensure that AI models respect ethical, safety, and security principles, with transparency, explainability, and accountability embedded by design. 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.
Contribute to the BRIDGE initiative and actively participate in its activities.
The general conditions for this funding opportunity include:
Admissibility Conditions: Proposal page limit and layout described in Annex A and Annex E of the Horizon Europe Work Programme General Annexes and Part B of the Application Form available in the Submission System.
Eligible Countries: Described in Annex B of the Work Programme General Annexes. Specific provisions may exist for non-EU/non-Associated Countries; refer to the Horizon Europe Programme Guide.
Other Eligible Conditions: If projects use satellite-based earth observation, positioning, navigation and/or related timing data and services, beneficiaries must make use of Copernicus and/or Galileo/EGNOS.
Financial and operational capacity and exclusion: Described in Annex C of the Work Programme General Annexes.
Evaluation and award: Award criteria, scoring and thresholds are described in Annex D of the Work Programme General Annexes. Submission and evaluation processes are described in Annex F of the Work Programme General Annexes and the Online Manual. The indicative timeline for evaluation and grant agreement is described in Annex F of the Work Programme General Annexes.
Legal and financial set-up of the grants: The granting authority may object to a transfer of ownership or to the exclusive licensing of results up to 4 years after the end of the action, as set out in Annex G of the Work Programme General Annexes and the specific provision of Annex 5.
Specific conditions are described in the specific topic of the Work Programme. Application and evaluation forms and the Model Grant Agreement (MGA) are available in the Submission System. Standard application forms (HE RIA, IA) and evaluation forms will be used with necessary adaptations.
Additional documents include:
HE Main Work Programme 2026-2027 – 1. General Introduction
HE Main Work Programme 2026-2027 – 8. Climate, Energy and Mobility
HE Main Work Programme 2026-2027 – 15. General Annexes
HE Programme Guide
HE Framework Programme 2021/695
HE Specific Programme Decision 2021/764
EU Financial Regulation 2024/2509
Decision authorising the use of lump sum contributions under the Horizon Europe Programme
Rules for Legal Entity Validation, LEAR Appointment and Financial Capacity Assessment
EU Grants AGA — Annotated Model Grant Agreement
Funding & Tenders Portal Online Manual
Funding & Tenders Portal Terms and Conditions
Funding & Tenders Portal Privacy Statement
Partner search announcements are available for collaboration on this topic. LEARs, Account Administrators, or self-registrants can publish partner requests for open and forthcoming topics after logging into the Portal.
The submission system is planned to be opened on the date stated on the topic header.
Applicants are encouraged to read all provisions carefully before preparing their application. The Online Manual serves as a guide on procedures from proposal submission to grant management. The Horizon Europe Programme Guide contains detailed guidance on the structure, budget, and political priorities of Horizon Europe. The Funding & Tenders Portal FAQ provides answers to frequently asked questions on proposal submission, evaluation, and grant management.
Additional support resources include the Research Enquiry Service, National Contact Points (NCPs), Enterprise Europe Network, IT Helpdesk, European IPR Helpdesk, CEN-CENELEC Research Helpdesk and ETSI Research Helpdesk, the European Charter for Researchers and the Code of Conduct for their recruitment, and Partner Search.
In summary, this Horizon Europe funding opportunity aims to foster the development and deployment of AI foundation models in the energy sector by promoting data sharing, collaboration, and innovation. It seeks to address key challenges in the energy transition through the use of AI, while ensuring ethical and responsible development practices. The call encourages participation from a diverse range of stakeholders, including data owners, application developers, and model deployers, to create a collaborative ecosystem for AI-driven solutions in the energy sector.
The expected outcomes of projects funded under this topic include:
Effective and innovative methods for gathering, sharing, and using large datasets in energy applications for 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.
The scope of this funding opportunity focuses on developing, training, and testing AI foundation models using extensive datasets to accelerate the energy transition in key focus areas of the energy sector. Projects are expected to:
Build on the results of previously funded projects on the Common European energy data space and the ongoing work within the Data 4 Energy expert group, demonstrating 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.
Develop innovative strategies for sharing data in an effective, secure, and transparent way to support the development of AI foundation models. Strategies may include data space connectors, federated training of models, creation of synthetic data, or an ‘AI gym’. The data governance strategies should be scalable and operational even after the project ends.
Develop foundation models tailored for the energy sector, addressing use cases such as: 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.
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)”. Regulatory sandboxes could also be considered for real-life pilot implementations.
Bring together a wide group of stakeholders including data owners (e.g., energy utilities, grid operators, asset owners), application developers (e.g., startups, SMEs, hyperscalers), and model deployers (e.g., industry, grid operators, equipment manufacturers), providing a space of cooperation and collaborative data exchange.
Benefit from the computing capacity of the AI factories announced by the European Commission, particularly the three AI factories that aim to develop AI applications for the energy sector, to scale up the training and development of the models.
Ensure that AI models respect ethical, safety, and security principles, with transparency, explainability, and accountability embedded by design. 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.
Contribute to the BRIDGE initiative and actively participate in its activities.
The general conditions for this funding opportunity include:
Admissibility Conditions: Proposal page limit and layout described in Annex A and Annex E of the Horizon Europe Work Programme General Annexes and Part B of the Application Form available in the Submission System.
Eligible Countries: Described in Annex B of the Work Programme General Annexes. Specific provisions may exist for non-EU/non-Associated Countries; refer to the Horizon Europe Programme Guide.
Other Eligible Conditions: If projects use satellite-based earth observation, positioning, navigation and/or related timing data and services, beneficiaries must make use of Copernicus and/or Galileo/EGNOS.
Financial and operational capacity and exclusion: Described in Annex C of the Work Programme General Annexes.
Evaluation and award: Award criteria, scoring and thresholds are described in Annex D of the Work Programme General Annexes. Submission and evaluation processes are described in Annex F of the Work Programme General Annexes and the Online Manual. The indicative timeline for evaluation and grant agreement is described in Annex F of the Work Programme General Annexes.
Legal and financial set-up of the grants: The granting authority may object to a transfer of ownership or to the exclusive licensing of results up to 4 years after the end of the action, as set out in Annex G of the Work Programme General Annexes and the specific provision of Annex 5.
Specific conditions are described in the specific topic of the Work Programme. Application and evaluation forms and the Model Grant Agreement (MGA) are available in the Submission System. Standard application forms (HE RIA, IA) and evaluation forms will be used with necessary adaptations.
Additional documents include:
HE Main Work Programme 2026-2027 – 1. General Introduction
HE Main Work Programme 2026-2027 – 8. Climate, Energy and Mobility
HE Main Work Programme 2026-2027 – 15. General Annexes
HE Programme Guide
HE Framework Programme 2021/695
HE Specific Programme Decision 2021/764
EU Financial Regulation 2024/2509
Decision authorising the use of lump sum contributions under the Horizon Europe Programme
Rules for Legal Entity Validation, LEAR Appointment and Financial Capacity Assessment
EU Grants AGA — Annotated Model Grant Agreement
Funding & Tenders Portal Online Manual
Funding & Tenders Portal Terms and Conditions
Funding & Tenders Portal Privacy Statement
Partner search announcements are available for collaboration on this topic. LEARs, Account Administrators, or self-registrants can publish partner requests for open and forthcoming topics after logging into the Portal.
The submission system is planned to be opened on the date stated on the topic header.
Applicants are encouraged to read all provisions carefully before preparing their application. The Online Manual serves as a guide on procedures from proposal submission to grant management. The Horizon Europe Programme Guide contains detailed guidance on the structure, budget, and political priorities of Horizon Europe. The Funding & Tenders Portal FAQ provides answers to frequently asked questions on proposal submission, evaluation, and grant management.
Additional support resources include the Research Enquiry Service, National Contact Points (NCPs), Enterprise Europe Network, IT Helpdesk, European IPR Helpdesk, CEN-CENELEC Research Helpdesk and ETSI Research Helpdesk, the European Charter for Researchers and the Code of Conduct for their recruitment, and Partner Search.
In summary, this Horizon Europe funding opportunity aims to foster the development and deployment of AI foundation models in the energy sector by promoting data sharing, collaboration, and innovation. It seeks to address key challenges in the energy transition through the use of AI, while ensuring ethical and responsible development practices. The call encourages participation from a diverse range of stakeholders, including data owners, application developers, and model deployers, to create a collaborative ecosystem for AI-driven solutions in the energy sector.
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Breakdown
Eligible Applicant Types: The eligible applicant types are not explicitly stated in the provided text. However, based on the context of Horizon Europe and the types of actions (Innovation Actions, Research and Innovation Actions, Pre-commercial Procurement), eligible applicants could include startups, SMEs, large enterprises, universities, research institutes, and other relevant organizations involved in the energy sector and AI development. The call also mentions data owners (energy utilities, grid operators, asset owners), application developers (startups, SMEs, hyperscalers) and model deployers (industry, grid operators, equipment manufacturers).
Funding Type: The primary financial mechanism is a grant, specifically through Horizon Innovation Actions (IA), Research and Innovation Actions (RIA), and Pre-commercial Procurement (PCP) under the Horizon Europe program. The type of Model Grant Agreement (MGA) is HORIZON Action Grant Budget-Based [HORIZON-AG].
Consortium Requirement: The text does not explicitly state whether a single applicant or a consortium is required. However, the call encourages bringing together a wide group of stakeholders, including data owners, application developers, and model deployers, suggesting that a consortium approach is preferred to foster cooperation and collaborative data exchange.
Beneficiary Scope (Geographic Eligibility): The eligible countries are described in Annex B of the Work Programme General Annexes. A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon Europe projects. See the information in the Horizon Europe Programme Guide. This indicates that the primary geographic eligibility is for EU and associated countries, with possibilities for non-EU countries under specific conditions.
Target Sector: The program targets the energy sector, with a focus on the digitalization of the energy system, AI, and data sharing. Specific areas include grid observability, forecasting of supply and demand, advanced storage and renewables integration, demand side flexibility, energy efficiency, and smart charging of EVs. The program also targets AI and data governance.
Mentioned Countries: The text mentions EU and non-EU/non-Associated Countries.
Project Stage: The project stages targeted include development, testing, and validation of AI foundation models. The call mentions lab demonstrators and real-life pilots, suggesting that the projects should be at least at the validation or demonstration stage.
Funding Amount: The funding amounts vary by topic:
HORIZON-CL5-2026-11-D3-04: EUR 40,000,000
HORIZON-CL5-2026-11-D3-05: EUR 13,500,000
HORIZON-CL5-2026-11-D3-06: EUR 18,000,000
HORIZON-CL5-2026-11-D3-14: EUR 30,000,000
HORIZON-CL5-2026-11-D3-23: EUR 30,000,000
Application Type: The application type is a single-stage call.
Nature of Support: Beneficiaries will receive money through grants.
Application Stages: The application process is a single-stage process.
Success Rates: The success rates are not explicitly mentioned, but the indicative number of grants for each topic is provided, which can be used to estimate the potential success rate based on the number of expected applications.
Co-funding Requirement: The text does not explicitly mention a co-funding requirement.
Summary:
This Horizon Europe funding opportunity, under the ENERGY (HORIZON-CL5-2026-11) call, aims to foster data sharing and the development of AI foundation models to accelerate the energy transition. The call is structured around several topics, each with a specific focus and budget, ranging from EUR 13.5 million to EUR 40 million. The primary goal is to improve the quality of AI models used in the energy sector by enhancing the amount, quality, and representativeness of the data used for training.
Projects are expected to contribute to effective methods for gathering, sharing, and using large datasets in energy applications, while ensuring privacy and security. They should also develop advanced, open-source AI foundation models to support the digitalization of the energy system, improving grid observability, forecasting, storage, renewables integration, demand side flexibility, and energy efficiency. Enhanced cooperation and interoperability among energy system actors are also key objectives.
The scope includes building on previous projects related to the Common European energy data space and demonstrating innovative data governance strategies. Projects should develop strategies for secure and transparent data sharing, such as using data space connectors, federated training, or creating synthetic data. The AI models developed should address use cases like planning and operation of electricity grids, forecasting, congestion management, anomaly detection, and predictive maintenance.
Applicants are expected to perform in-depth testing and validation of their models in lab demonstrators and real-life pilots, leveraging facilities from previously funded AI testing and experimentation facilities (TEFs). The call encourages bringing together a diverse group of stakeholders, including data owners, application developers, and model deployers, to foster collaboration and data exchange. The computing capacity of AI factories announced by the European Commission can be utilized to scale up model training and development.
Ethical considerations, safety, security, transparency, explainability, and accountability are paramount in AI model development. Open-source development practices are encouraged, and efforts should be made to avoid biases in the data. Selected projects are expected to contribute to the BRIDGE initiative and actively participate in its activities.
The application process is a single-stage submission, with a planned opening date of August 4, 2026, and a deadline of December 1, 2026. The funding is provided through Horizon Innovation Actions (IA), Research and Innovation Actions (RIA), and Pre-commercial Procurement (PCP), with the Model Grant Agreement being a HORIZON Action Grant Budget-Based [HORIZON-AG].
Funding Type: The primary financial mechanism is a grant, specifically through Horizon Innovation Actions (IA), Research and Innovation Actions (RIA), and Pre-commercial Procurement (PCP) under the Horizon Europe program. The type of Model Grant Agreement (MGA) is HORIZON Action Grant Budget-Based [HORIZON-AG].
Consortium Requirement: The text does not explicitly state whether a single applicant or a consortium is required. However, the call encourages bringing together a wide group of stakeholders, including data owners, application developers, and model deployers, suggesting that a consortium approach is preferred to foster cooperation and collaborative data exchange.
Beneficiary Scope (Geographic Eligibility): The eligible countries are described in Annex B of the Work Programme General Annexes. A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon Europe projects. See the information in the Horizon Europe Programme Guide. This indicates that the primary geographic eligibility is for EU and associated countries, with possibilities for non-EU countries under specific conditions.
Target Sector: The program targets the energy sector, with a focus on the digitalization of the energy system, AI, and data sharing. Specific areas include grid observability, forecasting of supply and demand, advanced storage and renewables integration, demand side flexibility, energy efficiency, and smart charging of EVs. The program also targets AI and data governance.
Mentioned Countries: The text mentions EU and non-EU/non-Associated Countries.
Project Stage: The project stages targeted include development, testing, and validation of AI foundation models. The call mentions lab demonstrators and real-life pilots, suggesting that the projects should be at least at the validation or demonstration stage.
Funding Amount: The funding amounts vary by topic:
HORIZON-CL5-2026-11-D3-04: EUR 40,000,000
HORIZON-CL5-2026-11-D3-05: EUR 13,500,000
HORIZON-CL5-2026-11-D3-06: EUR 18,000,000
HORIZON-CL5-2026-11-D3-14: EUR 30,000,000
HORIZON-CL5-2026-11-D3-23: EUR 30,000,000
Application Type: The application type is a single-stage call.
Nature of Support: Beneficiaries will receive money through grants.
Application Stages: The application process is a single-stage process.
Success Rates: The success rates are not explicitly mentioned, but the indicative number of grants for each topic is provided, which can be used to estimate the potential success rate based on the number of expected applications.
Co-funding Requirement: The text does not explicitly mention a co-funding requirement.
Summary:
This Horizon Europe funding opportunity, under the ENERGY (HORIZON-CL5-2026-11) call, aims to foster data sharing and the development of AI foundation models to accelerate the energy transition. The call is structured around several topics, each with a specific focus and budget, ranging from EUR 13.5 million to EUR 40 million. The primary goal is to improve the quality of AI models used in the energy sector by enhancing the amount, quality, and representativeness of the data used for training.
Projects are expected to contribute to effective methods for gathering, sharing, and using large datasets in energy applications, while ensuring privacy and security. They should also develop advanced, open-source AI foundation models to support the digitalization of the energy system, improving grid observability, forecasting, storage, renewables integration, demand side flexibility, and energy efficiency. Enhanced cooperation and interoperability among energy system actors are also key objectives.
The scope includes building on previous projects related to the Common European energy data space and demonstrating innovative data governance strategies. Projects should develop strategies for secure and transparent data sharing, such as using data space connectors, federated training, or creating synthetic data. The AI models developed should address use cases like planning and operation of electricity grids, forecasting, congestion management, anomaly detection, and predictive maintenance.
Applicants are expected to perform in-depth testing and validation of their models in lab demonstrators and real-life pilots, leveraging facilities from previously funded AI testing and experimentation facilities (TEFs). The call encourages bringing together a diverse group of stakeholders, including data owners, application developers, and model deployers, to foster collaboration and data exchange. The computing capacity of AI factories announced by the European Commission can be utilized to scale up model training and development.
Ethical considerations, safety, security, transparency, explainability, and accountability are paramount in AI model development. Open-source development practices are encouraged, and efforts should be made to avoid biases in the data. Selected projects are expected to contribute to the BRIDGE initiative and actively participate in its activities.
The application process is a single-stage submission, with a planned opening date of August 4, 2026, and a deadline of December 1, 2026. The funding is provided through Horizon Innovation Actions (IA), Research and Innovation Actions (RIA), and Pre-commercial Procurement (PCP), with the Model Grant Agreement being a HORIZON Action Grant Budget-Based [HORIZON-AG].
Short Summary
Impact This funding aims to foster data sharing and the development of AI foundation models to accelerate the energy transition, improving grid observability, forecasting, and energy efficiency. | Impact | This funding aims to foster data sharing and the development of AI foundation models to accelerate the energy transition, improving grid observability, forecasting, and energy efficiency. |
Applicant Applicants should possess expertise in AI development, data management, and energy systems, including stakeholders like energy utilities, application developers, and research institutions. | Applicant | Applicants should possess expertise in AI development, data management, and energy systems, including stakeholders like energy utilities, application developers, and research institutions. |
Developments The funding will support projects focused on AI foundation models in the energy sector, specifically targeting data sharing, grid operations, and predictive maintenance. | Developments | The funding will support projects focused on AI foundation models in the energy sector, specifically targeting data sharing, grid operations, and predictive maintenance. |
Applicant Type This funding is designed for a diverse consortium of stakeholders in the energy sector, including energy utilities, startups, SMEs, research institutions, and model deployers. | Applicant Type | This funding is designed for a diverse consortium of stakeholders in the energy sector, including energy utilities, startups, SMEs, research institutions, and model deployers. |
Consortium A consortium approach is preferred, emphasizing collaboration among various stakeholders in the energy sector. | Consortium | A consortium approach is preferred, emphasizing collaboration among various stakeholders in the energy sector. |
Funding Amount €10,000,000 per project, with a total budget of €30,000,000 for three expected grants. | Funding Amount | €10,000,000 per project, with a total budget of €30,000,000 for three expected grants. |
Countries The funding is relevant for EU member states and associated countries, emphasizing cross-border collaboration. | Countries | The funding is relevant for EU member states and associated countries, emphasizing cross-border collaboration. |
Industry The funding targets the energy sector, focusing on digitalization and AI applications within the context of Horizon Europe. | Industry | The funding targets the energy sector, focusing on digitalization and AI applications within the context of Horizon Europe. |
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Novel solutions for off-grid storage of renewable energy for critical infrastructures
Call for ProposalForthcoming
The grant opportunity HORIZON-CL5-2026-03-D3-21 focuses on developing innovative off-grid energy storage solutions for renewable energy, particularly for critical infrastructures such as hospitals...
March 31st, 2026