Project description
Green energy solutions supported by green AI
The EU-funded EnergyGuard project aims to create a disruptive enabler of AI-supported energy sector solutions with a cost-effective, open testing experimentation facility that leverages Europe’s greenest high-performance computing infrastructure, Meluxina. The project will bring together five European large-scale testing and experimentation facilities covering a transmission network, a microgrid with distributed energy resources, hydrogen testing platforms, a digital twin of a city’s apartment buildings and a renewable energy community. It will enable AI testing of diverse renewable energy systems, energy storage systems electrolysers, fuel cells and electric mobility via advanced digital twins along with assessment of cybersecurity and regulatory requirements. Finally, the project and its testing experimentation facility will conduct five pilots case studies.
Objective
EnergyGuard aims to develop, kickstart and sustain an open, green and robust Testing Experimentation Facility operating under real-world conditions to empower innovators in bringing trustworthy AI products to the energy market in a cost-effective manner. It will integrate five significant European large-scale testing and experimentation facilities that cover the full energy value chain,supported by European’s greenest HPC infrastructure (Meluxina). This includes a digital twin (DT) of the Portuguese Transmission Network (RDN), the CEDER-CIEMAT Microgrid with its Distributed Energy Resources (DERs), the Hydrogen testing platforms at CEA LITEN, CARTIF, BER and CIEMAT, a high-fidelity local DT of Riga's multi-apartment residential buildings and the Antrodoco Renewable Energy Community. This includes a wide range of elements to cover diverse AI test needs,including wind power, photovoltaic systems, hydropower plant, AEM,PEM and SO eletrolysers, fuel cells, EV charging stations, electric and public buses and battery storage systems. The facilities will be accessible to EnergyGuard end-users through a set of properly configured Digital Twins (DTs) and curated assets, including data, models, inference APIs, services, and applications through a AI development Testing environment. It will enable easy seamless access to assets from the EU ecosystem including AIOD, Data Spaces, DIHs and other TEFs; Moreover, EnergyGuard facilitates users to validate their products with an Acceptance Environment and a common open AI risks database for a wide range of cybersecurity and trustworthy AI assessments. The TEF will serve as full infrastructure to support national AI regulatory sandbox initiatives and deliver 5 pilot cases for the private and public sector. EnergyGuard will build upon a long-term, self-sustainable business model driven by a new entity, incorporating market-ready features early in the design, such as a subscription/plan framework, billing, and professional support
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencescomputer and information sciencesdatabases
- social scienceseconomics and businessbusiness and managementinnovation management
- natural sciencesbiological sciencesecologyecosystems
- engineering and technologyenvironmental engineeringenergy and fuelsrenewable energyhydroelectricity
- natural sciencescomputer and information sciencescomputer security
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Programme(s)
Funding Scheme
HORIZON-IA - HORIZON Innovation ActionsCoordinator
106 82 ATHINA
Greece