About AEGIS
AEGIS — Adaptive Grid-Interactive Edge Datacenter Fleets — is a European research and training network. It is funded by the EU through a Marie Skłodowska-Curie Doctoral Network, runs from 2026 to 2030, and trains 15 Doctoral Candidates (PhD students).
The problem
Europe plans to install about 10,000 climate-neutral edge nodes by 2030. Edge datacenters — small computing sites placed close to where data is produced — are spreading fast, driven by AI. But this growth runs into a tired power grid. Large electricity users now wait years for a new grid connection, and some regions have paused new datacenter connections. At the same time, Europe wastes clean energy: in 2023 Germany alone threw away 10.5 TWh of renewable power — enough for over three million homes for a year — because supply, demand, and grid limits did not match.
The opportunity
The same datacenters that strain the grid could help fix it. A modern datacenter has three kinds of flexibility that match what the grid needs at different speeds: batteries that react in milliseconds, cooling systems that move their power use over minutes, and computing work that can be delayed, moved between sites, or scaled to follow clean energy. Today this flexibility is locked away. Datacenters act as passive loads, blind to the grid, because the computing world — built for probabilistic service targets — and the grid world — built for hard, safety-critical guarantees — do not speak the same language.
What AEGIS builds
AEGIS develops software-defined flexibility technologies that turn edge datacenters from passive electrical loads into active, carbon-efficient, grid-interactive resources. The platform has three layers:
- A programmable infrastructure layer gives safe, runtime-verified control of a site’s power electronics, cooling, and AI hardware.
- An intelligence layer reads real-time grid signals and turns a request such as “reduce power by 20%” into the detailed actions that hardware and facilities must take, without breaking service.
- A fleet orchestration layer coordinates many sites, even when they have different owners, using trusted and privacy-preserving methods, so the whole fleet can act as one Virtual Power Plant.
AEGIS tests the platform in two real settings: a telecom edge fleet that mixes network and AI work, and carbon-aware multi-tenant edge datacenters.
Why this matters
Even modest flexibility is valuable: a 25% power reduction for 200 hours can free up 100 GW of grid capacity, while cutting wasted renewable energy and delaying expensive grid upgrades. AEGIS aims for a double win — a steadier grid that can take in more renewable energy, and the extra grid capacity needed for Europe’s growing edge and AI computing.
Why a Doctoral Network
The problem crosses many fields: energy systems, control theory, machine learning, operations research, and cybersecurity. Few people can bridge them today, which slows progress. AEGIS trains 15 Doctoral Candidates to become the experts who can. A Doctoral Network is the right tool, because it brings universities and companies together across countries and sectors. The consortium has 7 universities and 3 companies as beneficiaries, plus 9 associated partners. The team builds on experience coordinating the FORA MSCA network (2017–2021).
Coordinator: Prof. Paul Pop, DTU Compute — aegis@compute.dtu.dk.