AI reshapes data centre energy, cooling & sustainability strategies

The rapid expansion of artificial intelligence is driving significant changes in how data centres manage rising power and cooling demands worldwide.

Farokh Ghadially, Vice President of IT & Data Centres at Schneider Electric, has outlined the substantial challenges and emerging strategies for the data centre sector in the wake of exponential AI growth.

Ghadially states, "As AI continues to push the boundaries of what's possible its growing influence is pressuring enterprises, colocation providers, and tech giants to rethink data centre strategy. With that, how can the data centre industry navigate rapid transformation while simultaneously shifting gears at full speed?"

He notes the dramatic escalation in energy use, saying, "Readily accepted as an essential tool for streamlining significant swaths of tech-driven tasks, it was the volume and velocity of AI enquiries that came as a surprise. Even more surprising has been the immense energy tradeoff."

Pointing to research from the Electric Power Research Institute, Ghadially highlights that "a typical AI query consumes ten times the electricity of a traditional internet search, while generating original music, photos, and videos demands magnitudes more power."

With 5.45 billion internet users globally, the fast uptake of AI is "driving power consumption to unprecedented levels. In fact, AI's computing capacity is expected to double approximately every 100 days, driving a 26% to 36% annual rise in global energy consumption linked to AI in the years ahead."

This mounting demand has prompted industry leaders to reevaluate operational approaches to maintain data centre efficiency and reliability. Ghadially explains, "The best among them are pursuing innovative design to develop out-of-the-box strategies accommodating growth while maintaining reliability."

Engineering solutions are at the forefront of this transformation. Ghadially identifies four main areas: rack configuration, cooling solutions, software management, and power optimisation technologies.

AI workloads require new considerations for space efficiency. "AI workloads require thoughtful space planning to accommodate advanced cooling systems and the increased infrastructure footprint, driving increasing need for more compact and efficient designs. This is reshaping how space is used within data centres, with a heightened focus on optimising rack density and airflow to enhance overall performance."

He notes, "Large AI training models – systems that teach computers to recognise data patterns – are driving a shift toward higher rack power densities. High-density racks are designed to accommodate more servers in a smaller area allowing for higher computing power without increasing space requirements."

For scalability, "modular rack systems enable easy upgrades and scalability for data centres, allowing them to quickly adapt to changing AI power requirements without costly, extensive overhauls. However, as computing demands continue to rise, traditional cooling methods will struggle to maintain optimal temperatures."

This leads to greater adoption of liquid cooling. "AI hardware is generating heat beyond the limits of traditional air-cooling, making liquid cooling essential for data centres to maintain peak performance. Liquid cooling not only manages higher thermal loads more effectively, it also helps extend equipment lifespan. As a result, data centres are increasingly installing liquid cooling to future-proof their facilities."

"In addition, many are adopting hybrid cooling solutions that combine both air and liquid cooling to optimise performance and flexibility. This approach not only enhances cooling efficiency but also allows data centres to scale their operations in response to evolving workloads, ensuring they remain competitive in an increasingly demanding landscape."

"To enhance cooling efficiency and ensure AI workloads are effectively managed, data centre operators are exploring new airflow design strategies. Proper airflow management is crucial in preventing literal hotspots and allowing equipment to remain within optimal temperature ranges, especially as AI-driven workloads generate significantly more heat."

He elaborates, "For hybrid cooling setups, where both air and liquid cooling solutions are used, precise airflow control becomes even more essential. This often involves strategic placement of hot and cold aisles, containment systems, and optimised server arrangements to prevent air mixing and maximise cooling efficiency."

Reference designs and proven architectures are also being deployed to improve system performance while controlling costs and energy use.

Regarding power needs, "Higher-density workloads necessitate more robust power distribution systems. Data centres are seeking out more advanced uninterruptible power supplies (UPS) and scalable power solutions for reliable energy delivery. They are also equipping racks with advanced power distribution units (PDUs) that can handle higher wattages and allow for dynamic power allocation to support varying AI workloads."

"What's more, data centres are collaborating more closely with utility companies to optimise energy sourcing and management. By working together, they can implement demand response programs and leverage renewable energy options, pursuing a more sustainable and resilient power infrastructure."

The wider community is also benefiting from the sector's focus on sustainability. "Waste heat is primarily used to heat nearby buildings, like homes, offices, and even public spaces like swimming pools. By capturing the excess heat generated by servers and transferring it through a system of pipes, warmth is provided to surrounding areas. This illustrates how AI is driving community collaboration and contributing to energy conservation while supporting local heating needs."

Ghadially adds, "Data centres are continuously developing more creative ways to capture and repurpose excess heat, enabling smarter, more precise management of energy resources." Examples include Google's operation in Hamina, Finland, where excess heat from a data centre is used by a nearby paper mill, and Equinix directing waste heat from its Paris data centre to warm local Olympic swimming pools. Other centres are channeling waste heat to indoor agriculture to support crop growth.

The use of AI within data centres is aiding operations. "By channeling AI's problem-solving abilities, data centres operate more effectively with predictive analytics and intelligent systems that can monitor operations and streamline complex or time-consuming processes."

"AI offers countless opportunities to enhance energy efficiency. AI can analyse real-time data to optimise cooling systems and drive peak performance while minimising energy use. Predictive analytics can forecast energy demands, allowing for more streamlined power distribution and waste reduction."

Ghadially provides the example, "Google has implemented AI-driven predictive maintenance for its data centres, using machine learning algorithms to analyse sensor data from equipment like cooling systems, servers, and power units. This work enables Google to identify patterns that may indicate potential equipment failures, allowing for preemptive maintenance that reduces downtime and enhances reliability."

He adds, "Additionally, Schneider Electric's AI-based technology provides real-time predictive maintenance insights by analysing the performance and condition of data centre equipment. Schneider's platform has the ability to prewarn of battery failures in UPS systems and optimises cooling system performance, prompting proactive repairs and improving data center energy efficiency."

Security is also a consideration, with AI tools increasingly used to detect and address potential threats before they escalate.

Ghadially concludes, "As AI adoption accelerates, data centres must be adaptive and nimble in stepping up to the plate. They need to implement strategic changes across all aspects of operations, from reimagining facility design and infrastructure to optimising power efficiency, cooling systems, and management practices. Investing in scalable, future-proof solutions is equally important for the infrastructure to evolve with advancing technology."

"As AI revolutionises every facet of modern life, its transformative impact is felt deeply across the data centre industry. However, it also presents an extraordinary opportunity for data centres to take the lead in innovation and set new industry standards in sustainability and performance during one of the most exciting eras of digital transformation."