Schneider Electric: Can AI Data Centres Run Water-Free?

Data centres built for gen AI workloads do not require water consumption to operate.

The cooling systems needed for high-density AI infrastructure can function through closed-loop liquid cooling that eliminates external water draw.

Tuan Hoang, Head of Cooling Technology and Product Development at Schneider Electric, addressed this topic during the Schneider Electric & TeraWulf Global Press Event in Buffalo, New York.

"We do not need to consume water to operate data centres," Tuan says to a room full of journalists.

His remarks respond to investigative reports that examined the water footprints of gen AI data centres.

These reports raised concerns about localised water scarcity in communities near large-scale AI facilities.

Geographical factors influence water decisions

Water consumption patterns differ from cooling requirements. "Zero water is needed to cool AI data centres," Tuan says. "Liquid cooling is required but it's for the load and radiators."

The decision to consume water depends on location-specific variables. "Water consumption for data centres is a choice – a geographical choice dependent on power, land and what is required," Tuan says.

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Liquid cooling for a rack of 400kW is mandatory for AI workloads. Water consumption is optional.

The distinction could reshape how the sector approaches resource planning.

Schneider Electric presented two theoretical case studies comparing air-cooled and liquid-cooled facilities.

The projections examined data centres in Dallas, Texas and Paris, France.

According to Schneider Electric, transitioning to liquid cooling can reduce annual water consumption by roughly half.

The projected water usage for the Dallas data centre fell from 382,000 cubic metres per year with air cooling to 197,000 cubic metres with liquid cooling.

Case studies show consumption cuts

This represents a 48% reduction in water use. The Paris facility dropped from 108,000 cubic metres to 51,000 cubic metres, a 53% decrease.

"It's a choice to how you reject the heat and the myth that all data centres with liquid cooling are using lots of water, isn't true," Tuan says. "We focus on high-efficiency chilling."

The Uniflair XCA line by Schneider Electric is a series of pre-engineered air-cooled chillers designed for data centre environments.

The system "does not use water, just radiates heat out," Tuan notes.

These systems provide continuous cooling up to 2.4MW per unit. They include fast restart capabilities and dual-feed power redundancy.

Closed-loop engineering eliminates evaporation

The technology relies on closed-loop engineering rather than external water consumption. The system uses a dedicated, factory-sealed volume of high-quality cooling fluid.

Schneider Electric tests the specific formulation in its Motivair factories. This ensures the fluid remains trapped safely within the system throughout its operational life.

The design eliminates evaporation or discharge. The fluid supply is built to endure the entire operational life of the data centre without replenishment.

Liquid cooling has existed since the 1980s but its status has changed. "Now it isn't an option, it's mandatory," according to Rich Whitmore, CEO of Motivair by Schneider Electric.

Motivair has been developing liquid cooling systems for 400kW racks for over 10 years. "People don't have a choice – if you want advanced AI systems going in, you have to cool them," Rich says.

The thermal requirements of AI infrastructure could redefine the resource equation. Implementing closed-loop liquid cooling reduces a data centre's reliance on external water supplies.

The shift from air cooling to liquid cooling changes the environmental profile of AI data centres. According to Schneider Electric's projections, water consumption could fall by approximately half when facilities transition to liquid cooling systems.

This transition addresses concerns raised in recent reports about water use. The closed-loop approach could offer a pathway for data centre operators to reduce environmental impact while meeting the cooling demands of AI workloads.