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Power Usage Effectiveness (PUE)
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“冷却”之于数据中心为何如此重要?
高工锂电· 2026-01-27 11:21
如何理解?如果 PUE 为 1.3 ,即数据中心每消耗 1.5 度电,其中只有 1 度电真正用于芯片计算,其余 0.5 度用于制冷、配电、照明等基础设 施。 摘要 高效冷却是降低数据中心PUE的有效抓手。 数据中心的能耗与冷却息息相关。 拆解来看,数据中心靠稳定的电力维系芯片的高效运算,而电力消耗离不开热的产生,若热量得不到有效消散,温度过高会导致芯片性能下降、运算 速度变慢 。 因此,温控设备、冷却手段成为建设数据中心的关键一环。然而,温控系统也需要消耗电力, 一个决定数据中心是否高效运行重要指标在于,电能 的消耗占比。 而 PUE(Power Usage Effectiveness , 电能使用效率 ) 是 决定数据中心运行效率的关键指标,即数据中心总能耗 /IT 设备能耗, 数字越小则代 表用于芯片计算的电量使用效率越高 ,目前已普遍要求 PUE < 1.3 ,甚至逼近 1.2 。 而冷却,往往是数据中心的耗电大户。 也有观点认为,数据中心发展初期, PUE > 2 可以说是常态,其中的冷却环节是造成 PUE 走高的主要原因。 降低 PUE 的路径有两条: 一是充分利用外部冷却资源;二是数据中心内部的高 ...
The AI Boom Is Pushing Data Centers Past the Thermal Wall
Yahoo Finance· 2025-12-14 18:00
Core Insights - The demand for advanced cooling technologies in data centers is surging due to the thermal limits of traditional infrastructure being tested by hyperscale operators [1] Market Overview - The global data center cooling market was valued at $14.21 billion in 2024 and is projected to reach $34.12 billion by 2033, representing a compound annual growth rate (CAGR) of 10.3% [2] Technical Evolution - The industry is evolving technically, moving from conventional air-cooling methods to liquid and hybrid architectures due to the rapid adoption of high-performance computing (HPC) and AI workloads [3] - Current rack densities in hyperscale facilities are exceeding 20 to 30 kilowatts (kW) per rack, with some AI clusters surpassing 100 kW, making air cooling inefficient [5] Cooling Technologies - The report identifies the rapid expansion of hyperscale facilities as a primary catalyst for the demand for direct-to-chip and immersion cooling technologies [5] - New data center builds are increasingly designed with liquid-first infrastructure, while legacy facilities face challenges in retrofitting [6] Energy Consumption - Data centers are projected to consume over 1,000 terawatt-hours (TWh) of electricity globally by 2026, with potential energy use hitting 2,200 TWh by 2030 [7] - Cooling systems account for nearly 40% of a facility's total energy usage, making efficiency metrics like Power Usage Effectiveness (PUE) critical for operational and investment decisions [7][8] Regulatory Impact - Regulatory momentum in North America and Europe is influencing investment decisions, with stricter standards on energy reporting and environmental performance being imposed [8]