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EPRI EUROPE DAC

How EPRI EUROPE DAC appears in the EU Horizon funding graph: the research projects it has won money for, the consortia it joined, the EuroSciVoc topics it works in, and the organisations it co-funds projects with.

1 Horizon project, EUR 0 total EC contribution, last active 2030.

Organisation

Country
IE (IE061)
Organisation type
REC
VAT number
IE3606212VH
CORDIS match
high confidence

Horizon projects

EU Horizon research projects EPRI EUROPE DAC participated in, with its role and the EC contribution recorded for this organisation. Figures cover EU Horizon grants only, not total EU spend.

Adaptive Grid-Interactive Edge Datacenter Fleets (AEGIS)

associatedpartner

Europe’s Digital Decade will deploy large fleets of Edge Datacenters (EDCs) by 2030, just as Europe’s electricity grid struggles to integrate variable renewables. The fundamental disconnect is that EDCs operate as passive loads: physically connected to the grid but blind to its real-time needs. This is due to two barriers: a lack of internal controls to safely coordinate fragmented subsystems (IT, cooling, batteries) to provide the verifiable performance the grid requires; and a lack of fleet coordination mechanisms, as energy markets require minimum bids that smaller EDCs cannot meet, with no trusted way to aggregate them into a unified resource. The main scientific objective of AEGIS is to transform EDCs from passive liabilities into grid-interactive assets by developing a Software-Defined Platform for EDC Flexibility. This platform is architected in three layers. The foundational cyber-physical layer provides runtime-verified control to unlock safe, quantifiable flexibility. The intelligence layer uses carbon-aware forecasting and control, enabling AI workloads to dynamically adapt their behavior and resource consumption in response to real-time grid signals. The orchestration layer enables trusted, fleet-scale operations using privacy-preserving mechanisms to create a unified grid resource. Our ambitious objectives require researchers with a unique combination of interdisciplinary and intersectoral skills. AEGIS’s 15 Doctoral Candidates will receive integrated training across key areas (computer science, power systems, control engineering, machine learning, and distributed systems) necessary to realize the potential of these technologies, moving between academic and industrial environments to bridge the gap between the energy and computing domains. AEGIS will provide a new generation of experts capable of driving future developments in sustainable, grid-interactive edge datacenters across Europe.

EC contribution:
EUR 0
Start:
2026-10-01
End:
2030-09-30
Status:
SIGNED
Scheme:
HORIZON-TMA-MSCA-DN
Call:
HORIZON-MSCA-2025-DN-01
machine learningcontrol engineering

View on CORDIS (DOI 10.3030/101311399)

Co-funding partners

Organisations that EPRI EUROPE DAC has shared one or more EU Horizon projects with, ranked by the number of shared projects. 1 of these are Irish organisations with their own profile.

WienIT GmbH
1 shared project
Corintis SA
1 shared project
TDC NET A/S
1 shared project
CELLNEX TELECOM SA
1 shared project
CENTER DANMARK DRIFT APS
1 shared project
ELISA OYJ
1 shared project
EC Group
1 shared project
AALTO KORKEAKOULUSAATIO SR
1 shared project
SHELL GLOBAL SOLUTIONS INTERNATIONAL BV
1 shared project
LUNDS UNIVERSITET
1 shared project
DEUTSCHE TELEKOM AG
1 shared project
OY L M ERICSSON AB
1 shared project
ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
1 shared project
TECHNISCHE UNIVERSITAET WIEN
1 shared project
TECHNISCHE UNIVERSITAT BERLIN
1 shared project
DANMARKS TEKNISKE UNIVERSITET
1 shared project
IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE
1 shared project

Research topics

control engineeringmachine learning

About this data

This profile is built from the European Commission CORDIS open dataset of EU Horizon research projects, covering the digital and AI research vertical. It records EU Horizon grant participation only and does not represent an organisation's total EU funding. Verify figures against the official record before relying on them.

Source: CORDIS (CC-BY-4.0), snapshot 2026-09-04.cordis.europa.eu

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