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European startups and data-centre projects are addressing energy demand in four ways: optimizing cooling, moving heat away from servers with liquid systems, shifting when facilities draw power, and reusing server heat. These interventions do not all reduce a data centre’s total electricity consumption. A cooling-energy saving, a lower energy bill, flexible grid capacity, and heat supplied to a nearby building are different outcomes—and should not be treated as interchangeable.
Why data-centre energy demand is a concern
Ember, as reported by Euronews in 2026, projects that electricity consumption by European data centres overall will rise from 96 terawatt-hours (TWh) in 2024 to 236 TWh by 2035. That is a forecast for all data centres in Europe, not an estimate of AI-only consumption.
Cooling is one place operators can intervene, but it is only part of a facility’s electricity use. Other measures can make demand more flexible or put heat to use outside the data centre without reducing the facility’s total electricity consumption. The distinctions matter when assessing what a project actually achieves.
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What the reported figures measure
| Project or system | Intervention | Reported outcome and evidence |
|---|---|---|
| EkkoSense at Virgin Media O2 sites | Wireless monitoring and cooling optimization | Virgin Media O2 reported an average 15% reduction in cooling energy, more than £1 million in annual savings, and 760 tonnes of location-based CO2 equivalent across 20 sites in 2024, as reported by Euronews. |
| EkkoSense with Telefónica Germany | Sensors, analytics, and a real-time digital twin | Telefónica estimated an initial 15–20% reduction in cooling-system energy consumption for its project. |
| etalytics at NTT’s Bonn data centre | Software simulation and optimization of cooling infrastructure | Euronews reported a 19.1% reduction in chiller electricity use during the first months of the trial; NTT expected savings of up to 25% over a full year. |
| OctaiPipe ACE at an Italian data centre | AI-based cooling control integrated with existing systems | Italtel reported cooling-energy costs fell by up to 30% and total site infrastructure energy efficiency improved by more than 10% at a 2 MW carrier-neutral facility. |
| Submer liquid cooling | Servers immersed in non-conductive liquid | Submer’s client Telefónica claimed energy-efficiency improvements of up to 50%; the claim is not a general, independently established saving rate. |
| GridBeyond at two Dublin data centres | Software-coordinated battery charging and discharging | Euronews reported a combined 8 MW of flexible capacity at two Keppel DC REIT facilities. This is a grid-flexibility measure, not a reduction in total electricity use. |
| Deep Green southwest England trial | Server heat transferred to a swimming pool | The pool was expected to cut gas use by 62%, save more than £20,000 annually, and reduce annual emissions by 25.8 tonnes. These are reported trial expectations, not data-centre electricity savings. |
| European Commission HEATWISE pilots | Hybrid cooling, digital-twin data management, building energy management, and heat recovery | Project modelling reported cooling-load reductions up to 53.2% and heat-recovery improvements up to 17.1% in specific scenarios. |
| Scaleway Paris DC5 | Adiabatic cooling | A vendor case study reported 30–40% lower electricity consumption and 9–10 times lower water use versus traditional data centres. The figures concern the facility, not an isolated AI workload. |
The figures above have different boundaries and evidence types. They cannot be added together or ranked as if they measured the same thing.
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How cooling optimization works
Sensors and digital twins
EkkoSense uses wireless sensors to monitor room temperature, airflow, power, and cooling capacity. Its software turns those readings into a three-dimensional view of a facility, helping operators find areas that are over-cooled or under-cooled. The Telefónica Germany project also uses a real-time digital twin to map thermal and load risks, make recommendations, and work with existing site capacity.
Software control and simulation
etalytics models cooling equipment such as chillers, pumps, and heat exchangers, then calculates operating options within temperature limits. OctaiPipe’s AI for Cooling Efficiency (ACE) creates a digital twin and uses collaborative AI agents to monitor and optimize cooling parameters. According to Italtel, ACE integrates with existing building management systems (BMS) and data centre infrastructure management (DCIM) systems without requiring additional sensors.
These approaches focus on making installed infrastructure operate more effectively. Their practical fit depends on the equipment, controls, sensor data, and integration options at each site. Results reported for one operator or facility are not a performance guarantee for another.
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How liquid cooling and immersion remove heat
Air-cooled systems move heat through the room and cooling plant. Liquid systems can carry heat away closer to the source. Submer’s approach immerses servers in non-conductive liquid, reducing reliance on fans and air conditioning. It is facility-scale infrastructure, not a consumer computer accessory.
Liquid cooling can also create a useful stream of recoverable heat. The Bitten AI supercomputer, developed by the University of Southern Denmark with Danfoss and HPE, uses liquid cooling with full heat recovery and connects that heat to the local energy system. It demonstrates a project configuration; it does not establish a general savings percentage for other facilities.
How batteries make data-centre demand more flexible
Data centres commonly keep batteries for backup power. GridBeyond’s software coordinates battery charging and discharging in response to grid conditions, allowing a facility to shift some of its electricity draw. That can provide flexibility to the electricity system, but moving consumption to a different time does not necessarily reduce the amount of electricity the data centre uses overall.
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How recovered heat can serve nearby users
Deep Green locates computing facilities near potential heat users, such as swimming pools or district-heating networks, and transfers server heat using warmed liquid. In the reported southwest England trial, the expected reductions concerned the pool’s gas use and emissions—not the data centre’s electricity demand.
The European Commission’s HEATWISE project examines hybrid cooling, digital-twin data management, building energy management, and heat recovery across pilots in Denmark, Poland, Switzerland, Sweden, and Türkiye. Its reported outcomes are modelled for particular pilot scenarios. They should be read as scenario-specific project findings, not as results already observed at every data centre.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to judge an energy-saving claim
Before comparing projects, identify exactly what was measured and where. A percentage about cooling equipment cannot be compared directly with a whole-site energy-efficiency measure, a lower utility bill, or heat supplied to a nearby building.
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- Outcome: Is the claim about cooling energy, total facility electricity, cost, peak or grid draw, water, emissions, or recovered heat?
- Boundary: Does it cover a cooling plant, a data-centre room, the whole facility, or an adjacent heat user?
- Evidence: Is the result measured in a deployment, estimated at the outset, reported by a customer or vendor, simulated, or forecast?
- Operating conditions: What facility size, climate, computing load, cooling design, and baseline operation does it reflect?
- Implementation: Can the approach work with existing infrastructure, or does it require sensors, new cooling hardware, control-system integration, or changes that affect uptime?
For example, a cooling-cost result does not establish the same percentage reduction in total facility electricity, and a flexible-capacity figure is not an energy-saving percentage. Keep each metric attached to its measurement boundary and evidence status.
What these projects do—and do not—show
The examples show several practical routes to more efficient cooling, more flexible electricity use, and useful heat recovery. They do not establish one verified percentage reduction in total AI data-centre electricity demand across Europe. The Europe-wide demand projection covers all data centres, while individual project results describe particular sites, measures, and evidence types.
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