EnergyGuard

(Large-Scale Testing and Experimentation Facility (TEF) for Assessing, Validating, and Enhancing AI-Powered Next-Generation Energy Solutions)

EnergyGuard aims to develop, launch, and sustain an open, green, and robust Testing and Experimentation Facility (TEF) that operates under real-world conditions to help innovators bring trustworthy and secure AI solutions to the energy market efficiently and cost-effectively. 
 
The project integrates five major European testing and experimentation infrastructures, collectively covering the entire energy value chain, and is supported by Europe’s greenest high-performance computing infrastructure: MeluXina. Together, they provide a powerful and flexible ecosystem for developing, testing, and validating AI-driven innovations in the energy sector.  
 
EnergyGuard’s network of facilities includes: 
-  A digital twin (DT) of the Portuguese Transmission Network (RDN) 
- The CEDER-CIEMAT Microgrid, featuring advanced Distributed Energy Resources (DERs) 
- Hydrogen testing platforms at CEA LITEN, CARTIF, BER, and CIEMAT  
- A high-fidelity DT of Riga’s multi-apartment residential buildings 
- The Antrodoco Renewable Energy Community 
 
These facilities represent a comprehensive set of testing environments, from renewable generation (wind, solar, hydropower) to energy conversion and storage (hydrogen systems, fuel cells, batteries) and smart mobility (EV charging and electric buses), addressing the diverse needs of AI testing and validation across the sector. 
 
EnergyGuard will offer access through Digital Twins and curated AI assets, including data, models, APIs, and applications, all integrated within a user-friendly AI testing and development environment. It will also enable seamless interoperability with the broader European AI ecosystem, including AI-on-Demand (AIoD), Data Spaces, Digital Innovation Hubs (DIHs), and other TEFs. 
 
To ensure trustworthy and secure deployment, the project introduces an Acceptance Environment and a shared AI Risk Database, supporting cybersecurity, reliability, and regulatory compliance. These capabilities will back national AI regulatory sandboxes and demonstrate real-world impact through five pilot cases in both public and private sectors.