Trends in Data Centers and Energy Management

Liquid cooling is redefining data center efficiency... Delivering a powerful combination of sustainability and cost savings. As computing demands increase, traditional air cooling is falling behind. Data centers are turning to liquid cooling to reduce energy use, cut costs, and support high-performance workloads. Operators are considering direct-to-chip cooling, which circulates liquid over heat-generating components, and immersion cooling, where servers are fully submerged in a dielectric fluid for maximum efficiency. Developed markets, like the U.S. and Europe, are adopting liquid cooling to support AI-driven workloads and reduce carbon footprints in large-scale facilities. Meanwhile, emerging markets in Southeast Asia and Latin America are leveraging liquid cooling to manage high-density computing in regions with hotter climates and less reliable power grids, ensuring operational stability and efficiency. Greater Energy Efficiency Liquid cooling reduces total data center power consumption by 10.2%, with facility-wide savings up to 18.1%. It also uses 90% less energy than air conditioning, improving heat transfer and maintaining stable operating temperatures. Sustainability Gains Lower PUE (Power Usage Effectiveness) means less wasted energy, while reduced electricity use cuts carbon emissions. Closed-loop systems also minimize water consumption, making liquid cooling a more sustainable option. Cost and Performance Advantages Efficient temperature management prevents thermal throttling, optimizing CPU and GPU performance. Higher-density computing lowers construction costs by 15-30%, while cooling energy savings of up to 50% reduce long-term operational expenses. The Future of Cooling As #AI and cloud workloads grow, liquid cooling is becoming a competitive advantage. Early adopters will benefit from lower costs, improved efficiency, and a more sustainable infrastructure. #datacenters

𝗕𝘆 𝟮𝟬𝟮𝟳, 𝗔𝗜 𝗗𝗮𝘁𝗮 𝗖𝗲𝗻𝘁𝗲𝗿𝘀 𝗪𝗼𝗻’𝘁 𝗝𝘂𝘀𝘁 𝗕𝗲 𝗦𝘁𝗿𝘂𝗴𝗴𝗹𝗶𝗻𝗴 𝗳𝗼𝗿 𝗣𝗼𝘄𝗲𝗿—𝗧𝗵𝗲𝘆’𝗹𝗹 𝗕𝗲 𝗙𝗶𝗴𝗵𝘁𝗶𝗻𝗴 𝗳𝗼𝗿 𝗪𝗮𝘁𝗲𝗿. The AI revolution is fueling unprecedented growth, but beneath the surface lies a critical vulnerability: 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲 𝘀𝗰𝗮𝗿𝗰𝗶𝘁𝘆. Gartner predicts that by 2027, 𝟰𝟬% 𝗼𝗳 𝗔𝗜 𝗱𝗮𝘁𝗮 𝗰𝗲𝗻𝘁𝗲𝗿𝘀 𝘄𝗶𝗹𝗹 𝗳𝗮𝗰𝗲 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗰𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻𝘁𝘀 𝗱𝘂𝗲 𝘁𝗼 𝗽𝗼𝘄𝗲𝗿 𝘀𝗵𝗼𝗿𝘁𝗮𝗴𝗲𝘀. And while power gets the headlines, 𝘄𝗮𝘁𝗲𝗿 𝘀𝗰𝗮𝗿𝗰𝗶𝘁𝘆 is emerging as an equally pressing challenge. Cooling systems—critical for managing the immense heat from AI workloads—rely heavily on water. As demand for power rises, so does the strain on this finite resource. Regions like 𝗖𝗮𝗹𝗶𝗳𝗼𝗿𝗻𝗶𝗮 and parts of 𝗘𝘂𝗿𝗼𝗽𝗲 are already grappling with power shortages, forcing data centers to rethink their strategies. The stakes couldn’t be higher: Without urgent action, these constraints could slow AI innovation and 𝗿𝗮𝗶𝘀𝗲 𝗰𝗼𝘀𝘁𝘀 for businesses and end-users alike. But this isn’t just a crisis—it’s a call to innovate. 𝗛𝗼𝘄 𝗗𝗼 𝗪𝗲 𝗦𝗼𝗹𝘃𝗲 𝗧𝗵𝗶𝘀? The key lies in tackling inefficiency at its source. Start with 𝗣𝗨𝗘 (𝗣𝗼𝘄𝗲𝗿 𝗨𝘀𝗮𝗴𝗲 𝗘𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲𝗻𝗲𝘀𝘀): • A lower PUE (closer to 1.0) means less wasted energy, which directly reduces heat generation—and by extension, cooling demands and water use. • Smarter energy and workload management can shrink the power and water footprint of AI operations. 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝘃𝗲 𝗣𝗮𝘁𝗵𝘀 𝗙𝗼𝗿𝘄𝗮𝗿𝗱: 1. 𝗔𝗜-𝗗𝗿𝗶𝘃𝗲𝗻 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Use AI itself to dynamically manage energy and cooling systems. 2. 𝗪𝗮𝘁𝗲𝗿𝗹𝗲𝘀𝘀 𝗖𝗼𝗼𝗹𝗶𝗻𝗴 𝗦𝘆𝘀𝘁𝗲𝗺𝘀: Embrace liquid immersion and advanced cooling technologies to reduce reliance on water. 3. 𝗥𝗲𝗻𝗲𝘄𝗮𝗯𝗹𝗲𝘀 𝗮𝗻𝗱 𝗖𝗶𝗿𝗰𝘂𝗹𝗮𝗿 𝗦𝘆𝘀𝘁𝗲𝗺𝘀: Pair renewable energy with closed-loop cooling to build long-term resilience. 𝗪𝗵𝘆 𝗧𝗵𝗶𝘀 𝗠𝗮𝘁𝘁𝗲𝗿𝘀: Sustainability isn’t just about compliance—it’s a 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗲𝗱𝗴𝗲 in a world demanding responsible innovation. Organizations that act now will not only future-proof their operations but also enhance their brand and bottom line. 𝗪𝗵𝗮𝘁 𝗦𝗵𝗼𝘂𝗹𝗱 𝗟𝗲𝗮𝗱𝗲𝗿𝘀 𝗗𝗼 𝗧𝗼𝗱𝗮𝘆? Start by assessing your data center’s 𝗣𝗨𝗘 𝗮𝗻𝗱 𝗰𝗼𝗼𝗹𝗶𝗻𝗴 𝘀𝘆𝘀𝘁𝗲𝗺𝘀. Small improvements now can lead to significant cost and resource savings as demand grows. 𝗧𝗵𝗲 𝗕𝗶𝗴𝗴𝗲𝗿 𝗣𝗶𝗰𝘁𝘂𝗿𝗲: AI isn’t just a test of innovation—it’s a test of our ability to 𝗯𝗮𝗹𝗮𝗻𝗰𝗲 𝗽𝗿𝗼𝗴𝗿𝗲𝘀𝘀 𝘄𝗶𝘁𝗵 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆. The future of AI depends not just on its potential—but on how sustainably we can scale it. The time to rethink and innovate is now. 𝗪𝗵𝗮𝘁’𝘀 𝘆𝗼𝘂𝗿 𝗽𝗹𝗮𝗻? #AIInnovation #SustainableTech #DataCenterEfficiency #LeadershipInAI

AI's impact on data center cooling is unprecedented. In 2025, data centers are anticipated to experience a 33% annual increase in demand for AI-ready capacity, with AI workloads driving energy consumption growth at a compound annual rate of 44.7%, reaching 146.2 terawatt-hours by 2027. As reported by Forbes and Futurcio. This surge underscores the critical need for efficient and reliable cooling solutions to manage escalating heat loads and energy demands. For those designing chilled water plants for data centers, Armstrong Fluid Technology’s comprehensive Data Center Water Cooled Chiller Plant Design Guide is an invaluable resource. This guide focuses on Tier II installations, a cost-effective solution providing reliable cooling through CRAC units. It dives into critical design considerations, including: • N+1 redundancy for system reliability • Understanding Tier II Uptime standards • Balancing cost with infrastructure availability But beyond the guide—let’s talk trends! 👉 How are AI workloads influencing your approach to chilled water system design? 👉 Are you seeing shifts toward liquid cooling, higher temperature chilled water, or innovative redundancy strategies? We’d love to hear your thoughts. Share your insights in the comments and let’s discuss where data center cooling is headed.

This white paper analyzes the energy implications of artificial intelligence (AI) and data centers, highlighting their rapid expansion and projected increase in energy demands. My key take aways: 1. Rising Data Center Energy Demand: • Data centers, particularly those operated by companies like Meta, Amazon, Microsoft, and Google, more than doubled their electricity use between 2017 and 2021. • AI models, including generative AI such as ChatGPT, are highly energy-intensive. Each ChatGPT request uses about 2.9 watt-hours, which is at least ten times the electricity of a standard Google query. 2. Projected Energy Scenarios: • Four scenarios project U.S. data center electricity consumption growth from 2023 to 2030: low (3.7% annual growth), moderate (5%), high (10%), and higher (15%). By 2030, data centers could represent 4.6% to 9.1% of U.S. electricity demand. • This growth is geographically concentrated, with 80% of the national data center load in 15 states. Virginia’s data center demand could reach nearly 50% of the state’s electricity use by 2030 under the high-growth scenario. 3. Challenges and Strategies for Sustainable Expansion: • Efficiency Improvements: Data centers must increase operational efficiency, including adopting energy-efficient hardware and cooling technologies. • Enhanced Collaboration: Effective partnerships between electric companies and data center developers are needed for efficient power sourcing and grid stability. • Advanced Forecasting and Modeling: Improved forecasting tools are essential to plan infrastructure investments and manage the demand surges from AI-driven applications. Thanks Julien Pestourie for sharing ! At SE Ventures we are committed to support a sustainable AI path with new investments and venture building. Luc Meysenc Stephan Prueger sébastien Cruz-Mermy Amit Peri Deepak Bhandary Amit Narayan , point #3 is particularly important

Data Centers and service providers led the global corporate energy procurement push, accounting for 26% of the 68 GW in announced deals. As shown in the S&P Global Commodity Insights data, this sector outpaced all others—including manufacturing (13%) and materials (8%)—in its pursuit of alterative power. The energy-intensive nature of Data Centers, combined with growing pressure to decarbonize digital infrastructure, is making them a key driver in the corporate transition to alterative energy.

I thought I’d would dust off my data center hat to dive into this great PwC article on the future of data centers, as the insights in this piece really struck a chord: - AI and Emerging Tech: Demand for compute is skyrocketing, pushing data centers to explore new configurations and innovate on cooling, power, and scalability. - Supply Chain and Location: As global infrastructure and market demands shift, data center operators must juggle site selection, supply constraints, and regional regulations. - Sustainability and ESG: Energy efficiency remains a major consideration, not just for operational costs but also to meet evolving environmental standards. From my own experience, one angle to consider further is the cost vs. benefit of chasing an ultra-low PUE (Power Usage Effectiveness). It’s often a substantial capital investment, and the ROI doesn’t always pencil out if tenants and customers aren’t willing to pay a premium for those added efficiencies. Striking the right balance between sustainability goals and financial viability is key. This is a challenging area to understand and one that PwC can provide guidance on as you look to make data center design and capital outlay decisions. PwC is at the forefront of navigating these complexities—from AI-driven design to ESG alignment. Check out the article, and I’d be happy to hear your thoughts on how data centers can best balance performance, cost, and sustainability in today’s landscape. https://lnkd.in/gn7W4n_J #PwC #TMT