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Optimizing Data Center Cooling with AI

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We Don't Have Time

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How AI can tackle data centers’ most energy-intensive component

For which energy user: Digital infrastructure
As energy efficiency is booming, a global data center provider in Singapore partnered with technology experts to develop artificial intelligence and machine learning models to optimize their entire cooling plant.
By using sensors placed throughout upstream chillers and distribution systems, they track and analyze data to facilitate dynamic cooling optimization. Because cooling is the most energy-intensive component of a data center, optimizing it yields massive relative gains.
The pilot project targets a 10% energy savings directly within the cooling system, driving the company toward its goal of becoming net carbon neutral by 2030 while supporting predictive maintenance.
Additional benefits:
  • Global scale potential: With more than 130 data centers across Asia and Europe, even modest efficiency improvements could translate into massive energy and emissions savings across the company’s global operations.
  • AI beyond cooling: The same AI infrastructure could later support capacity planning, operational risk management, and predictive maintenance, expanding the value far beyond energy optimization.
  • Data-first implementation: The project begins by analyzing historical operational data before deploying live AI controls, reducing risk and helping identify the most effective optimization opportunities before full-scale rollout.
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https://app.wedonthavetime.org/frontpage/energyefficiencyaction




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