Data center cooling: Pros and cons of air, liquid and geothermal systems

AI could also provide recommendations for equipment upgrades or changes in configuration to improve cooling efficiency, Graham says.

Another area where the technology can help is performance analytics. “AI provides valuable insights into the performance of the cooling systems, helping to identify areas for improvement and ensuring that the systems are operating efficiently,” Graham says. By optimizing cooling systems, AI helps in reducing energy consumption, leading to significant cost savings and a reduction in a data center’s carbon footprint, Graham says.

The use of AI for data center cooling is in its infancy, Sharp says. “Today, this technology can be used to assist with the thermal modelling of the facility from a fluid dynamics perspective, to attempt to isolate and prevent hot spots,” he says. “In the future, AI will likely be used in more operational systems which can ingest large amounts of operational data from equipment in the data center in order to optimize cooling across a range of rack densities in a single site.”

AI is driving an increasing average rack density in the data center, which itself creates the need for more liquid cooling, Sharp says. “Innovations in this area including non-electrically conductive coolants, industry standard backplane connectors to easily connect customer equipment to the facility’s liquid loop, and intelligent flow control systems are all promising for improving the safety, accessibility, performance and environmental impact of the data center,” he says.

To decrease the energy usage of cooling systems, Equinix is trialing the use of AI/machine learning technology as a superseding control system on top of the existing control systems, van Gennip says. “The initial results look very promising,” he says.

Which technologies are ideal for existing data centers vs. newly constructed facilities? “Ultimately, the right cooling methodology for any data center will depend on a number of factors including its design, the climate, environmental goals, cooling requirements, budget, etc.,” Graham says.

Newer data centers, especially those focused on high-density workloads such as generative AI, are most likely better suited for direct-to-chip or immersion cooling, Graham says.