高产热密度数据机房冷却技术研究
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摘要
随着信息产业的快速发展，全社会对各类高性能数据机房的需求越来越大。以刀片式服务器为代表的高性能IT设备的广泛应用已经使得标准42U机柜的容量从早年的不足1kW跃升到10~20kW，大型数据中心单位面积IT设备发热量高达1~3kW，如此高的产热密度使空调能耗大幅上升，目前已占机房总用电量的40%左右，不仅增加机房运营成本，制约机房升级扩容，还直接影响着未来绿色数据机房的发展。如何有效降低机房空调能耗已成为亟待解决的问题。基于此，本文从机房传热过程的本质入手，从传热动力损失角度重新审视和分析机房传热过程，开展以下研究：
对机房传热过程本质的研究。指出机房排热的核心任务是在给定的散热量和可用的传热动力（机房室内外温差）下，通过减少各换热环节的温差消耗，用高温冷源完成热量从室内到室外的搬运，并结合实测数据给出机房实际传热过程的的温度分布，指出室内冷热空气混合对机房传热性能有重要的影响。
对机房传热过程分析方法的研究。对于给定传热温差求最大热流的优化问题，分别用传统热力学方法（熵产，火用损失）和热学方法（火积耗散）分析，结果表明热学原理（也称热质理论）适合研究机房传热过程，用火积耗散表征传热动力损失，指出机房排热的核心任务是减少传热火积损失，结合实测数据分析了机房传热过程中由温差传热、冷热流体混合、流量不匹配等因素引起的火积耗散，并分析了在不同工况下投入体系的压缩功以及在不同结构的换热网络中流体流量的变化对体系传热火积耗散的影响。
分布式冷却技术研究。基于传热火积损失最小原则提出机房分布式冷却方案，通过与传统集中式冷却流程对比，指出分布式冷却在消除冷热空气混合、改善传热过程匹配性、减少火积耗散以及改善机房热环境、降低排热能耗等方面的优势，在此基础上提出了内置多级分离式热管的内冷型机柜以及冷却塔与多级冷机串联运行的大温差冷水系统，消除冷热空气混合；通过自然冷却和机械制冷联合运行并连续调节供冷能力，有效延长自然冷却时间，提高机房排热效率。
工程应用。对北京市某数据机房空调系统节能改造，通过对全年不同工况下改造前后空调性能对比测试，采用分布式冷却系统后，机房空调系统全年综合能效从2.6提高到5.7，机房年均PUE值从1.6降低到1.35，证明了热学原理和分布式冷却技术在高产热密度数据机房的适用性，为今后的推广应用积累了经验。
With the rapid growth of information industry, demand for high performance datacenter is increasing. Blade servers have lifted the capacity of a normal42U rack fromless than1kW in early years to recent10~20kW, rising IDC heat density up to1~3kW/m2,and nearly40%of data center operating cost is spent on air-conditioning.Reducing cooling cost is an urgent issue which affects management and development ofhigh heat density data centers. This paper characterizes the thermal behavior and thegoverning rules through the analysis on heat transfer ability loss of data centers fromfollowing aspects
The essence of data center heat transfer. The central work is to remove the givenheat under available driven force (temperature difference between indoor and outdoor),with minimum temperature difference dissipation and cold source of high temperature.The temperature distribution of a real data center indicates that the mix of hot and coldair has a significant impact on heat transfer performance.
The analysis method of data center heat transfer. Maximizing heat flux undergiven temperature difference by flow rate optimization is performed using boththermodynamic method (entropy generation and exergy loss) and entransy analysis(entranssy dissipation). The results show that entransy analysis is suitable for heattransfer optimization by minimizing heat transfer ability loss, which is represented byentransy dissipation caused by temperature difference driven heat conduct, mixing ofhot and cold air and unmatching flowrate in heat exchangers. The influence of inputwork and flowrate change in heat exchanger network on entransy dissipation is alsoanalysed with test data.
Distributed cooling system. Based on minimum principle of entransy dissipation.distributed cooling solution is brought up to improve data center cooling performance.Inner cooled racks with multi separated heat pipes inside eliminate hot and cold airmixing by multi-stage heat removal, and cooling water loop comprised of serialconnected cooling tower and multi-chiller enables continuous distribution of freecooling capacity and mechanical cooling capacity according to the outdoor condition,making more free cooling available. Such cooling loop has large temperature differenceof supply and returen water, which improves multi-chiller performance. With more free cooling and higher chiller COP, distributed cooling can be more energy efficient.
Engineering application. Through the air-conditioning retrofitting project of a highheat density data center in Beijing, the performance of two cooling solutions, distributedcooling and centralized cooling, are tested and compared after one year operation. Theresults show that after using distributed cooling, the data center’s annual average EER(Energy Efficiency Ratio) of air-conditioning system increases from2.6to5.7, and thedata center’s annual average PUE (Power Utilization Effectiveness) decreases from1.6to1.35, indicating the applicability of entransy analysis and distributed cooling solutionin data centers of high heat density. This retrofitting project enriches the experience forthe widely use of distributed cooling system in data centers in the future.
对机房传热过程本质的研究。指出机房排热的核心任务是在给定的散热量和可用的传热动力（机房室内外温差）下，通过减少各换热环节的温差消耗，用高温冷源完成热量从室内到室外的搬运，并结合实测数据给出机房实际传热过程的的温度分布，指出室内冷热空气混合对机房传热性能有重要的影响。
对机房传热过程分析方法的研究。对于给定传热温差求最大热流的优化问题，分别用传统热力学方法（熵产，火用损失）和热学方法（火积耗散）分析，结果表明热学原理（也称热质理论）适合研究机房传热过程，用火积耗散表征传热动力损失，指出机房排热的核心任务是减少传热火积损失，结合实测数据分析了机房传热过程中由温差传热、冷热流体混合、流量不匹配等因素引起的火积耗散，并分析了在不同工况下投入体系的压缩功以及在不同结构的换热网络中流体流量的变化对体系传热火积耗散的影响。
分布式冷却技术研究。基于传热火积损失最小原则提出机房分布式冷却方案，通过与传统集中式冷却流程对比，指出分布式冷却在消除冷热空气混合、改善传热过程匹配性、减少火积耗散以及改善机房热环境、降低排热能耗等方面的优势，在此基础上提出了内置多级分离式热管的内冷型机柜以及冷却塔与多级冷机串联运行的大温差冷水系统，消除冷热空气混合；通过自然冷却和机械制冷联合运行并连续调节供冷能力，有效延长自然冷却时间，提高机房排热效率。
工程应用。对北京市某数据机房空调系统节能改造，通过对全年不同工况下改造前后空调性能对比测试，采用分布式冷却系统后，机房空调系统全年综合能效从2.6提高到5.7，机房年均PUE值从1.6降低到1.35，证明了热学原理和分布式冷却技术在高产热密度数据机房的适用性，为今后的推广应用积累了经验。
With the rapid growth of information industry, demand for high performance datacenter is increasing. Blade servers have lifted the capacity of a normal42U rack fromless than1kW in early years to recent10~20kW, rising IDC heat density up to1~3kW/m2,and nearly40%of data center operating cost is spent on air-conditioning.Reducing cooling cost is an urgent issue which affects management and development ofhigh heat density data centers. This paper characterizes the thermal behavior and thegoverning rules through the analysis on heat transfer ability loss of data centers fromfollowing aspects
The essence of data center heat transfer. The central work is to remove the givenheat under available driven force (temperature difference between indoor and outdoor),with minimum temperature difference dissipation and cold source of high temperature.The temperature distribution of a real data center indicates that the mix of hot and coldair has a significant impact on heat transfer performance.
The analysis method of data center heat transfer. Maximizing heat flux undergiven temperature difference by flow rate optimization is performed using boththermodynamic method (entropy generation and exergy loss) and entransy analysis(entranssy dissipation). The results show that entransy analysis is suitable for heattransfer optimization by minimizing heat transfer ability loss, which is represented byentransy dissipation caused by temperature difference driven heat conduct, mixing ofhot and cold air and unmatching flowrate in heat exchangers. The influence of inputwork and flowrate change in heat exchanger network on entransy dissipation is alsoanalysed with test data.
Distributed cooling system. Based on minimum principle of entransy dissipation.distributed cooling solution is brought up to improve data center cooling performance.Inner cooled racks with multi separated heat pipes inside eliminate hot and cold airmixing by multi-stage heat removal, and cooling water loop comprised of serialconnected cooling tower and multi-chiller enables continuous distribution of freecooling capacity and mechanical cooling capacity according to the outdoor condition,making more free cooling available. Such cooling loop has large temperature differenceof supply and returen water, which improves multi-chiller performance. With more free cooling and higher chiller COP, distributed cooling can be more energy efficient.
Engineering application. Through the air-conditioning retrofitting project of a highheat density data center in Beijing, the performance of two cooling solutions, distributedcooling and centralized cooling, are tested and compared after one year operation. Theresults show that after using distributed cooling, the data center’s annual average EER(Energy Efficiency Ratio) of air-conditioning system increases from2.6to5.7, and thedata center’s annual average PUE (Power Utilization Effectiveness) decreases from1.6to1.35, indicating the applicability of entransy analysis and distributed cooling solutionin data centers of high heat density. This retrofitting project enriches the experience forthe widely use of distributed cooling system in data centers in the future.
引文
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