EnerTEF
The Future of Energy through AI Testing and Experimentation
Scroll for more
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.
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.
AI-Based Hydrogen Leak Detection and Localization
UTBM
The service is intended to be evaluated using historical datasets containing both normal operation and leak scenarios. The evaluation framework would separate training and testing data to ensure a robust assessment of detection and localization performance. Performance is expected to be measured using standard classification metrics, including accuracy, precision, recall, F1-score, and false alarm rate for leak detection, along with localization accuracy for identifying the leak position. Visual analysis of sensor signals and detected events would further support validation of the model’s ability to capture abnormal behaviour.
- Monitoring & Anomaly Detection
AI-Based Multi-Energy Demand Forecasting (Electricity and Hydrogen)
UTBM
The Multi-Energy Demand Forecasting service delivers AI-driven forecasts of electricity and hydrogen demand using time-series data from integrated energy systems. Based on advanced deep learning architectures (LSTM, TCN, Transformers), the service models interdependencies between electricity and hydrogen demand across coupled systems such as microgrids, industrial facilities, and energy hubs, supporting operational planning and resource allocation.
- Predictive & Prescriptive Analytics
Operational Scheduling for DHN
Veolia
The Operational Scheduling for DHN service generates optimal operational schedules for the district heating network by translating demand forecasts and real-time data into actionable control strategies. Using forecast-driven optimisation combined with rule-based and data-driven techniques, the service recommends supply temperature setpoints, load distribution plans, and operation timelines to maximise energy efficiency and minimise operational costs.
- Predictive & Prescriptive Analytics
- Optimization & Decision Support
Anomaly Detection and Fault Diagnosis in DHN
Veolia
The Anomaly Detection and Fault Diagnosis service detects abnormal patterns in the Torrelago district heating network using AI-based techniques applied to real-time and historical data. By establishing expected behavioural baselines from historical patterns and continuously comparing real-time data against these baselines, the service provides early warnings of inefficiencies, faults, and unexpected operational conditions.
- Monitoring & Anomaly Detection
News & Events
EnerTEF Joins the Smart City Expo Congress 2026!
EnerTEF will be at the Smart City Expo World Congress 2026 (Barcelona, 3–5 November) as part of the Smart Energy Cluster, a group of more than 40 EU-funded projects working together to speed up Europe’s clean energy transition.
On 5 November, 15:10-15:55, the cluster hosts “The Climate & Energy Quiz: Testing Knowledge & Unlocking Solutions for Cities”. Instead of a classic panel, this is a fast-paced, gamified session. Participants answer live multiple-choice questions on their smartphones by scanning a QR code, with no app needed. Each question opens the door to a European project and a practical solution that cities can use right away.
Vangelis Marinakis (NTUA) will represent EnerTEF and show two things:
- From testbeds to EU policy: how evidence from EnerTEF’s real-world AI testing has fed into the EU Strategic Roadmap for Digitalisation and AI in the Energy Sector, the AI.grids initiative and the SET Plan.
- The EnerTEF Portal: one entry point to Europe’s AI testing facilities for energy. Data owners such as cities offer data, digital twins and test sites, while AI developers find them, run experiments and buy services. A live example is the Athens Energy Portal, where smart-meter data from 90 municipal buildings now supports AI forecasts of energy use in the city’s schools.
EnerTEF will be joined by Smart Energy Cluster projects, ReLIFE, BlueBird, BUSINESS2ACT, EU-DREAM, with the session moderated by IEECP.
Explore the EnerTEF Portal: https://portal.enertef.eu/
Watch the walkthrough: https://www.youtube.com/watch?v=O9d1G_pFPNk
EnerTEF at Enlit Europe 2026!
EnerTEF will be at Enlit Europe 2026 in Vienna (10–12 November). On Wednesday 11 November, from 12:00 to 13:00, Elissaios Sarmas of DSS Lab, EPU-NTUA will present the project at the TEF Cluster session in EU Projects Hub 3 (EU Projects Zone, Hall C), together with our sister testing facilities for energy, AI-EFFECT and EnergyGuard.
EnerTEF brings five testing nodes and three satellites across Europe into one federated facility for AI in energy. Through the EnerTEF Portal, energy companies, AI developers and SMEs can find partners, ask for and negotiate AI services, and run experiments on shared data and computing resources.
Throughout the event, the EnerTEF team will be at stand C1.EU-S14, shared with EnergyGuard, META BUILD, PVSmile and Crete Valley, and happy to show you the Portal. Registration for the exhibition is free at https://www.enlit.world/enlit-europe/register. More about EnerTEF at enertef.eu.
EnerTEF highlighted in the EU SET Plan Task Force Recommendations on Digitalisation
Under the revised European Strategic Energy Technology (SET) Plan, Task Force 3 on Digitalisation has published 8 recommendations to support the integration of digital technologies and seamless data flows across the European energy sector. The recommendations were developed by representatives of the SET Plan IWGs, ETIPs, EERA and the Clean Energy Transition Partnership, together with independent experts.
EnerTEF features in Recommendation 7, “Develop a European energy data space rollout plan”, in two places.
A reference for a core building block. Among the concrete building blocks of the European Energy Data Space, the report calls for an open, standardisable, Energy Data Space–compliant interoperability and trust infrastructure. Its purpose is to adapt and scale up trustworthy, AI-powered data-driven services and applications, and EnerTEF is cited as the example. The report notes that this requires interoperability building blocks such as standardised interfaces and open APIs based on widely accepted energy ontologies like SAREF.
A Phase 1 pilot and sandbox (2026-2027). The proposed rollout roadmap begins with a Pilot & Sandbox phase that validates the foundational elements of the Energy Data Space: interoperability, trust frameworks and early marketplace functions. EnerTEF is listed among the large-scale pilots and sandboxes that will test these core functions, alongside ENERSHARE, HEDGE IoT, Crete Valley, META BUILD and ENPOWER.
Both references recognise EnerTEF’s role in building a federated, interoperable and trusted European Energy Data Space.
We also acknowledge Vangelis Marinakis, who contributed to Task Force 3 as a Support Expert and helped shape the recommendations.
📄 Download the report: https://lnkd.in/dyHxHDPb
More on the SET Plan Task Forces: https://setis.ec.europa.eu/about-set-plan/task-forces_en
Coming Soon!