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EnerTEF
The Future of Energy through AI Testing and Experimentation
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Our Vision
01
Reference Architecture
Establish a Reference Architecture (RA) for an Open Interoperable Common Federated European-scale Energy AI TEF accessible to all the players of the energy ecosystem.
02
Compliance Framework
Establish a regulatory/legal/ethical compliance framework contributing to the effective implementation of the EU Artificial Intelligence Act (EU AI Act) in the development lifecycle of trustworthy AI-powered services.
03
Energy Hub
Leverage local node-level energy infrastructures availability, energy stakeholders’ know-how and ENERSHARE Data Space Building Blocks to instrument an open, standardisable and Energy Data Space compliant interoperability and trust infrastructure for the adaptation and upscale of data-driven trustworthy AI-powered services and Apps.
04
EnerTEF Integration
Integrate, deploy, operate and maintain the Federated Common European-scale Energy AI Testing and Experimentation Facility (EnerTEF), facilitating regulatory sandboxes for supervised testing and experimentation in real environments.
Testing Our Innovations in Action
10
countries
Germany, Italy, France, Greece, Netherlands, Luxemburg, Slovenia, Portugal, Spain, Sweden
5
nodes
TEF DSO Node, TEF EV Node, TEF BUILD Node, TEF RES Node, TEF TSO Node
3
satellites
TEF H2 Satellite, TEF IND Satellite, TEF DHN Satellite
--> Select a country to discover detailed information about ongoing pilot projects there.
Germany
Roadmap
August 2025
Testing services catalogue for AI solutions
November 2025
First wave of EnerTEF solutions
July 2026
Second wave of EnerTEF solutions versions
November 2026
Successful demonstration of solution in the nodes and satellites
February 2027
Final wave of EnerTEF solutions with full functional implementation
August 2027
Demonstration of EnerTEF solutions in facilities outside the consortium
October 2027
Attraction of funding schemes funding schemes & Design of Go-to-Market business plans
Services Catalogue
EnerTEF provides a detailed catalogue of testing and experimentation services for AI tools across different fields in the energy sector.
Energy Efficiency Scoring
City of Athens
This AI service assigns a quantitative efficiency score to each municipal building by comparing its actual energy performance to similar buildings in the city. The score reflects how efficiently a building uses energy relative to its size, use, and category.
- Monitoring & Anomaly Detection
- Predictive & Prescriptive Analytics
Building PV Self-Consumption Optimization
City of Athens
The PV Self-Consumption Optimization service uses AI to maximize the use of locally generated solar energy within municipal buildings. By analyzing real-time consumption, historical PV production and energy consumption data, it identifies optimal load-shifting strategies to increase solar self-consumption and reduce reliance on grid electricity. The service recommends adjustments in building operations and controllable loads to align energy usage with PV generation peaks. This helps municipalities lower energy costs, improve sustainability performance, and enhance building energy autonomy.
- Monitoring & Anomaly Detection
- Predictive & Prescriptive Analytics
- Optimization & Decision Support
Building Energy Consumption Forecasting
City of Athens
Building Energy Consumption Forecasting service uses historical energy bills, building characteristics, real-time data from smart meters and seasonal patterns to forecast electricity consumption for municipal buildings. Leveraging machine learning models, it provides accurate short-term and mid-term forecasts. This service helps municipalities anticipate energy needs, optimize procurement, and identify potential inefficiencies before they escalate, supporting smarter and more sustainable energy management across the building portfolio.
- Predictive & Prescriptive Analytics
- Optimization & Decision Support
Real-Time Power Management for TSO-DSO Coordination
ELGO, ELES
Currently the DSOs have multiple requests for 5-20 MW battery energy storage system (BESS) on the 20kV feeder in the primary transformer station. There exists a potential of activating multiple disturbing elements at once, which in turn can affect the TSO network frequency and voltage. Flexibility management between TSO and DSO networks can be achieved by modelling the DSO network and simulate the effects of distributed energy resources (DER) and BESS on the DSO network and in turn on the TSO network. This data can be used in a system that notifies TSO operators about the potentially disturbing events or even the system itself actively controls the deployed BESSs.
- Optimization & Decision Support
- Automation & Control Systems
News & Events
EnerTEF at EUSEW 2026: Advancing AI-powered grids for Europe’s energy future
EnerTEF will take part in the European Sustainable Energy Week 2026, joining key discussions and activities dedicated to the future of smart, secure, and digital energy systems in Europe.
This year’s EUSEW, taking place from 9–11 June 2026 in Brussels and online, will bring together policymakers, researchers, industry representatives, and energy stakeholders to explore solutions for accelerating Europe’s clean energy transition.
Join the session: AI-powered grids: securing the future of European energy
EnerTEF will be represented in the session “AI-powered grids: securing the future of European energy”, which will explore the challenges and opportunities linked to the development, deployment, and mastery of sovereign European AI solutions for electricity grids.
The session will focus on how AI can support the energy transition by enabling smarter, more resilient, and more secure grid operations.
Session details
Date: Wednesday, 10 June 2026
Time: 15:30–17:00
Venue: NH Berlaymont – Jean Rey, Brussels
The discussion will address key themes including the EU and global decarbonisation framework, grids, and digitalisation.
Speakers include:
Elissaios Sarmas, Senior Research Associate, National Technical University of Athens (EPU-NTUA)
Nathalie Samovich, Steering Board Member, Alliance for AI, IoT and Edge Continuum Innovation (AIOTI)
Antonello Monti, Professor, Fraunhofer FIT
Marie-Sophie Debry, Power System Stability R&D Director, Réseau de Transport d'Electricité (RTE)
Michael Metzger, Distinguished Engineer on Sustainable Energy and Infrastructure, Siemens Energy
Gianluca Lipari, Project Manager, EPRI Europe
Meet EnerTEF at the Smart Energy Cluster stand
EnerTEF will also hold a full 3 - day stand under #SmartEnergyCluster!
The Smart Energy Cluster is an initiative currently managed by IEECP and NTUA under the Business2Act project. For this occasion, our stand will bring together 19 EU-funded initiatives working across smart grids, building decarbonisation, energy efficiency, and digital innovation. Visitors will have the unique opportunity to interact with experts and explore deliverables from a powerhouse of projects: BUILDON, BUILD-OSS, BUSINESS2ACT, EnerTEF, Enpower, ESCALATE, EU-TRACE, EVELIXIA, GiDomus, GINNGER, Hycool_IT, LEG-UP, LiveBetter, PVSmile, ReLIFE, REN+HOMES, Reschool, WILSON, and WeForming.
Whether you are walking the exhibition floor in Brussels or tracking the updates online, make sure the Smart Energy Cluster is on your agenda. Participation is free of charge, but registration is mandatory.
👉 Secure your EUSEW 2026 pass and bookmark the Smart Energy Cluster Stand here!
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AI-EFFECT Podcast with EnerTEF & Energy Guard Projects - Recorded by EPRI
EnerTEF is featured in a new episode of EPRI Current, EPRI’s flagship podcast exploring major innovations, challenges, and opportunities in the global energy sector. In this episode, host Samantha Gilman speaks with Elissaios Sarmas, Project Coordinator of EnerTEF and Senior Researcher at NTUA, and Sotiris Pelekis from ICCS, representing the EnergyGuard project.
The discussion focuses on what utilities can gain from shared AI infrastructure, with particular attention to the role of Testing and Experimentation Facilities in supporting interoperability, trust, scalability, and cost-efficient development across the energy ecosystem.
The episode also highlights the complementarity between EnerTEF, EnergyGuard, and AI-EFFECT, and reflects on how these initiatives contribute to a stronger and more reliable framework for AI adoption in the energy sector.
We also thank EPRI for recording the episode and the AI-EFFECT project for organising this collaboration.
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EnerTEF at BRIDGE General Assembly 2026
Europe’s energy transition is no longer only a technical challenge. It has become a strategic priority closely linked to resilience, security, and sovereignty.
At the BRIDGE General Assembly 2026 in Brussels, key representatives from policy, research, and innovation gathered to discuss the future of Europe’s energy systems, with a focus on digitalisation, interoperability, flexibility, and risk management in an increasingly complex energy landscape.
We are pleased to announce that EnerTEF Project Coordinator, Elissaios Sarmas, participated as a speaker in the high-level panel discussion on “The Role of AI in the Energy Grids”, held on 23–24 March 2026 at The Skyline, Brussels.
During the session, he contributed to the dialogue on how artificial intelligence can support the transformation of power systems, making them smarter, more adaptive, and more secure.
As part of his intervention, he presented practical applications and insights from the EnerTEF project, including:
- The Athens Energy Portal, which enables advanced monitoring and supports decision-making for urban energy systems
- The EnerTEF Portal, which supports the testing, validation, and deployment of AI-driven solutions for energy infrastructure
EnerTEF’s participation in the BRIDGE General Assembly 2026 highlights the project’s commitment to advancing trustworthy AI solutions that strengthen Europe’s energy infrastructure and support the transition to a more resilient and intelligent energy system.
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