EnerTEF: The future of energy through AI testing and experimentation

The European energy system is transforming at an unprecedented pace. Driven by the goals of decarbonisation, decentralisation and digitalisation, the sector is increasingly reliant on data and automation. AI is emerging as a key enabler of this transformation, offering the ability to predict, optimise and control complex energy networks. However, deploying AI safely and effectively in critical infrastructure requires more than algorithms and models; it requires trusted facilities for testing, validation, and certification.

EnerTEF responds directly to this need. Coordinated by the National Technical University of Athens and funded by the European Climate, Infrastructure and Environment Executive Agency (CINEA), the project brings together 25 partners from ten European countries. Over the course of three years, from November 2024 to October 2027, EnerTEF will create a federated network of testing and experimentation facilities dedicated to the energy sector.

Through this initiative, Europe will gain a structured, secure, and interoperable ecosystem for AI innovation.

EnerTEF methodology

EnerTEF’s methodology is based on the creation of a common federated infrastructure that integrates five primary testing nodes and three satellite sites across Europe. Each node specialises in a different aspect of the energy system, ranging from grid management and renewable integration to data governance and end-user applications. Together they provide a full-scale environment for testing and validating AI technologies in realistic operating conditions.

The project operates through four main thematic components. 

• First is the development of AI living labs, which are interactive spaces where researchers, developers, energy operators and policymakers collaborate on real world AI applications. 
• Second the focus is on bridging centralised access, ensuring that all testing and data sharing activities respect European regulations on privacy, ethics and security.
• Third, seamless federated integration deals with the harmonisation of AI systems and datasets across national and technological boundaries. 
• The final component is the creation of a long-term sustainability and go-to-market strategy that ensures AI innovations validated within EnerTEF can progress toward commercial deployment.

This multi-layered structure combines technical excellence with policy alignment. It also ensures that the EnerTEF framework remains flexible and adaptive, capable of accommodating future technological developments and new use cases.

Energy transition challenges

The EnerTEF project directly addresses several of the most pressing challenges in the European energy transition. One of its key objectives is to build trust in AI through transparent, secure and explainable testing processes. 

Every AI application validated within the EnerTEF framework must comply with the ethical and legal standards of the forthcoming EU AI Act. This approach not only strengthens accountability but also enhances public and industry confidence in digital energy technologies. 

Forty AI services have been developed, designed from our end-users to the SMEs/startups.

Another major contribution lies in the promotion of interoperability. By connecting facilities, datasets and stakeholders through a federated digital architecture, EnerTEF allows innovators to test solutions in multiple countries under harmonised technical and regulatory conditions. This eliminates duplication of effort and accelerates innovation cycles. It also supports smaller enterprises and startups, which often lack access to large-scale testing environments, by providing shared facilities that replicate real operating conditions.

In practical terms, EnerTEF will enable the validation of AI applications such as predictive maintenance, grid forecasting, renewable integration, demand side management, energy storage optimisation and more. The project’s integration with the common European energy data space and the AI-on-demand platform further enhances its ability to manage and process data securely while preserving sovereignty and confidentiality.

In terms of dissemination and communication, EnerTEF’s website has already 2,000 unique users, more than 450 followers in all platforms and more than 40 mentions from other projects or external parties.

Consortium and governance

EnerTEF is implemented by a consortium that brings together research institutions, industrial leaders, utilities, municipalities and technology providers.

This diverse partnership reflects the interdisciplinary nature of AI in energy. It ensures that scientific research, industrial application and policy development advance together, aligning technological innovation with the broader goals of European energy resilience and digital sovereignty.

Impact and future outlook

By 2027, EnerTEF aims to deliver a fully operational federated testing and experimentation platform open to external users. This infrastructure will provide harmonised evaluation procedures, common data interfaces and certification pathways for AI tools developed for the energy sector. It will also establish a European reference point for AI validation, complementing the work of other digital and energy initiatives under Horizon Europe.

Beyond its technical achievements, EnerTEF represents a major step toward a more collaborative, transparent and innovation-friendly European energy ecosystem. It will help reduce fragmentation across national markets, foster cross-border partnerships and support the development of AI technologies that contribute to the European Green Deal and the Digital Europe programme. 

For innovators, it will provide the necessary confidence that their solutions meet the highest standards of safety and reliability. For policymakers, it offers a model for integrating ethics, governance and performance within the same framework.

In conclusion, EnerTEF embodies Europe’s vision for trustworthy and sustainable digital transformation in energy. By creating a federated, interoperable, and ethically grounded environment for AI experimentation, it not only accelerates technological progress but also safeguards the principles of transparency, accountability and inclusiveness that define European innovation. 

The project will help ensure that AI becomes a driver of resilience and efficiency in the continent’s energy systems rather than a source of uncertainty.

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