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Article(id=1239211868510802323, tenantId=1146029695717560320, journalId=1238823019242635269, issueId=1239211861397270994, articleNumber=null, orderNo=null, doi=10.12465/j.issn.0253-4339.2025.01.086, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1696953600000, receivedDateStr=2023-10-11, revisedDate=1700150400000, revisedDateStr=2023-11-17, acceptedDate=1704297600000, acceptedDateStr=2024-01-04, onlineDate=1773380732895, onlineDateStr=2026-03-13, pubDate=1739635200000, pubDateStr=2025-02-16, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773380732895, onlineIssueDateStr=2026-03-13, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773380732895, creator=13701087609, updateTime=1773380732895, updator=13701087609, issue=Issue{id=1239211861397270994, tenantId=1146029695717560320, journalId=1238823019242635269, year='2025', volume='46', issue='1', pageStart='1', pageEnd='166', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=0, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773380731200, creator=13701087609, updateTime=1773384112372, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1239226043106652319, tenantId=1146029695717560320, journalId=1238823019242635269, issueId=1239211861397270994, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1239226043106652320, tenantId=1146029695717560320, journalId=1238823019242635269, issueId=1239211861397270994, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=86, endPage=93, ext={EN=ArticleExt(id=1239211868754071965, articleId=1239211868510802323, tenantId=1146029695717560320, journalId=1238823019242635269, language=EN, title=Performance of Cooling and Heating System with Dual-Evaporating Temperature and Mechanical Subcooling Using CO2 for Data Centers, columnId=null, journalTitle=Journal of Refrigeration, columnName=null, runingTitle=null, highlight=null, articleAbstract=

A CO2 data center cooling and heating system integrated with dedicated mechanical subcooling and dual-temperature evaporation technology (DMS-DE) is proposed to realize green and efficient cooling for data centers and improve comprehensive energy efficiency. A thermodynamic and carbon emission performance system model was established and compared with the basic CO2 system (Base) and a single evaporating-temperature CO2 system with dedicated mechanical subcooling (DMS-SE). The results demonstrated that the DMS-DE system had the maximum coefficient of performance (COP), optimal subcooling degree, and discharge pressure. Therefore, adopting the DMS-DE can significantly increase the system COP and exergy efficiency. Compared with Base and DMS-SE, COP increased by 14.1% and 9.0%, and the exergy efficiency increased by 13.24% and 4.31%, respectively. The life cycle carbon emissions of the DMS-DE system were reduced by 16.1% and 9.3% compared with Base and DMS-SE, respectively. This study can provide a technical reference for the highly efficient and clean operation of combined heating and cooling utilization for data center scenarios.

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Liu Shengchun, professor, School of Mechanical Engineering, Tianjin University of Commerce, 86-13920682426, E-mail: . Research fields: replacement of natural working medium, energy saving and optimization of refrigeration system.
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为实现数据中心绿色高效制冷，并提高能源综合利用率，提出了集成机械过冷和双温蒸发技术的CO2数据中心冷却供热系统（DMS-DE）。建立了系统热力学和碳排放特性分析模型，并与基本CO2系统（Base）和单温蒸发机械过冷CO2系统（DMS-SE）进行对比分析。结果表明：DMS-DE存在最大COP（性能系数）、最优过冷度和排气压力。采用机械过冷技术和双温蒸发技术可显著提升系统COP和效率。与Base和DMS-SE相比，COP分别提高14.1%和9.0%，效率分别提高13.24%和4.31%。DMS-DE的生命周期碳排放相对Base和DMS-SE分别降低16.1%和9.3%。

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刘圣春，男，教授，天津商业大学机械工程学院，13920682426，E-mail：。研究方向：自然工质替代，制冷系统节能与优化。
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Energy Conversion and Management, 2017, 151: 98-106., articleTitle=Comprehensive experimental study on a transcritical CO2 ejector-expansion refrigeration system, refAbstract=null)], funds=[Fund(id=1239224541403205976, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239211868510802323, awardId=2023M732582, language=EN, fundingSource=Postdoctoral Science Foundation project(2023M732582), fundOrder=null, country=null), Fund(id=1239224541470314841, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239211868510802323, awardId=2023M732582, language=CN, fundingSource=中国博士后科学基金项目(2023M732582), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1239224536147742953, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239211868510802323, xref=1., ext=[AuthorCompanyExt(id=1239224536156131562, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239211868510802323, companyId=1239224536147742953, 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label=图8, caption=不同系统损随送风温度的变化

Valve节流阀；Ej引射器；GC气体冷却器；Sub过冷器；Cond冷凝器；Com压缩机；Evap蒸发器。

, figureFileSmall=isloHfxLl73v89l4O+y7tg==, figureFileBig=einIBDzMUFThgHWbwvyJSQ==, tableContent=null), ArticleFig(id=1239224540719534414, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239211868510802323, language=EN, label=Fig.9, caption=Exergic efficiency of different systems varies with supply air temperature, figureFileSmall=XG6T1AAkIM+UXifDDcTwRg==, figureFileBig=blCzpHrn90uXuKB4RxB8nw==, tableContent=null), ArticleFig(id=1239224540795031888, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239211868510802323, language=CN, label=图9, caption=不同系统的效率随送风温度的变化, figureFileSmall=XG6T1AAkIM+UXifDDcTwRg==, figureFileBig=blCzpHrn90uXuKB4RxB8nw==, tableContent=null), ArticleFig(id=1239224540866335058, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239211868510802323, language=EN, label=Fig.10, caption=LCCP of different systems used in different cities, figureFileSmall=IlO5Uie45njzyxJaZtuANw==, figureFileBig=j8i3nadHtePWkpHsWNrduw==, tableContent=null), ArticleFig(id=1239224540950221139, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239211868510802323, language=CN, label=图10, caption=不同系统在各城市使用时的LCCP, figureFileSmall=IlO5Uie45njzyxJaZtuANw==, figureFileBig=j8i3nadHtePWkpHsWNrduw==, tableContent=null), ArticleFig(id=1239224541038301524, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239211868510802323, language=EN, label=Tab.1, caption=Data center operation mode, figureFileSmall=null, figureFileBig=null, tableContent=
模式冷却/供热运行条件运行设备
模式1数据中心冷却室外温度低于数据中心室内温度空气冷却器、泵、风机
模式2数据中心冷却和供热室外温度高于数据中心室内温度压缩机、气体冷却器、节流阀
), ArticleFig(id=1239224541101216085, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239211868510802323, language=CN, label=表1, caption=数据中心运行模式, figureFileSmall=null, figureFileBig=null, tableContent=
模式冷却/供热运行条件运行设备
模式1数据中心冷却室外温度低于数据中心室内温度空气冷却器、泵、风机
模式2数据中心冷却和供热室外温度高于数据中心室内温度压缩机、气体冷却器、节流阀
), ArticleFig(id=1239224541176713558, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239211868510802323, language=EN, label=Tab.2, caption=Rated operating conditions and operating boundary conditions of the system[11], figureFileSmall=null, figureFileBig=null, tableContent=
关键运行参数数值
空气回风温度Tair,return27
空气送风温度Tair,supply17
回水温度Tw,in40
供水温度Tw,out65
蒸发温度TEvap12
气冷器窄点温差ΔTGC5
过冷器窄点温差ΔTSC5
), ArticleFig(id=1239224541260599639, tenantId=1146029695717560320, journalId=1238823019242635269, articleId=1239211868510802323, language=CN, label=表2, caption=系统运行额定工况和运行边界条件[11], figureFileSmall=null, figureFileBig=null, tableContent=
关键运行参数数值
空气回风温度Tair,return27
空气送风温度Tair,supply17
回水温度Tw,in40
供水温度Tw,out65
蒸发温度TEvap12
气冷器窄点温差ΔTGC5
过冷器窄点温差ΔTSC5
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基于机械过冷的双温蒸发CO2数据中心冷却供热系统性能
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代宝民 1, 2 , 孔子昻 2 , 刘圣春 2 , 钱家宝 2 , 李伟锋 1 , 章立标 3
制冷学报 | 2025,46(1): 86-93
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制冷学报 | 2025, 46(1): 86-93
基于机械过冷的双温蒸发CO2数据中心冷却供热系统性能
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代宝民1, 2, 孔子昻2, 刘圣春2 , 钱家宝2, 李伟锋1, 章立标3
作者信息
  • 1天津大学医学工程与转化医学研究院　天津　300072
  • 2天津市制冷技术重点实验室　天津商业大学机械工程学院　天津　300134
  • 3浙江国祥股份有限公司　上虞　312300

通讯作者:

刘圣春，男，教授，天津商业大学机械工程学院，13920682426，E-mail：。研究方向：自然工质替代，制冷系统节能与优化。
Performance of Cooling and Heating System with Dual-Evaporating Temperature and Mechanical Subcooling Using CO2 for Data Centers
Baomin Dai1, 2, Ziang Kong2, Shengchun Liu2 , Jiabao Qian2, Weifeng Li1, Libiao Zhang3
Affiliations
  • 1.Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China
  • 2.Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, Tianjin, 300134, China
  • 3.Zhejiang King Refrigeration Industry Co., Ltd., Shangyu, 312300, China
出版时间: 2025-02-16 doi: 10.12465/j.issn.0253-4339.2025.01.086
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摘要
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为实现数据中心绿色高效制冷，并提高能源综合利用率，提出了集成机械过冷和双温蒸发技术的CO2数据中心冷却供热系统（DMS-DE）。建立了系统热力学和碳排放特性分析模型，并与基本CO2系统（Base）和单温蒸发机械过冷CO2系统（DMS-SE）进行对比分析。结果表明：DMS-DE存在最大COP（性能系数）、最优过冷度和排气压力。采用机械过冷技术和双温蒸发技术可显著提升系统COP和效率。与Base和DMS-SE相比，COP分别提高14.1%和9.0%，效率分别提高13.24%和4.31%。DMS-DE的生命周期碳排放相对Base和DMS-SE分别降低16.1%和9.3%。

A CO2 data center cooling and heating system integrated with dedicated mechanical subcooling and dual-temperature evaporation technology (DMS-DE) is proposed to realize green and efficient cooling for data centers and improve comprehensive energy efficiency. A thermodynamic and carbon emission performance system model was established and compared with the basic CO2 system (Base) and a single evaporating-temperature CO2 system with dedicated mechanical subcooling (DMS-SE). The results demonstrated that the DMS-DE system had the maximum coefficient of performance (COP), optimal subcooling degree, and discharge pressure. Therefore, adopting the DMS-DE can significantly increase the system COP and exergy efficiency. Compared with Base and DMS-SE, COP increased by 14.1% and 9.0%, and the exergy efficiency increased by 13.24% and 4.31%, respectively. The life cycle carbon emissions of the DMS-DE system were reduced by 16.1% and 9.3% compared with Base and DMS-SE, respectively. This study can provide a technical reference for the highly efficient and clean operation of combined heating and cooling utilization for data center scenarios.

代宝民, 孔子昻, 刘圣春, 钱家宝, 李伟锋, 章立标. 基于机械过冷的双温蒸发CO2数据中心冷却供热系统性能. 制冷学报, 2025 , 46 (1) : 86 -93 . DOI: 10.12465/j.issn.0253-4339.2025.01.086
Baomin Dai, Ziang Kong, Shengchun Liu, Jiabao Qian, Weifeng Li, Libiao Zhang. Performance of Cooling and Heating System with Dual-Evaporating Temperature and Mechanical Subcooling Using CO2 for Data Centers[J]. Journal of Refrigeration, 2025 , 46 (1) : 86 -93 . DOI: 10.12465/j.issn.0253-4339.2025.01.086
正文
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数据中心（DC, data center）是现代信息社会的必要基础设施，其运行过程伴随大量的余热生成[1]，且余热资源充足，对余热进行回收利用是实现“双碳”目标的可靠途径。然而，数据中心余热温度通常低于供热设计温度，可采用热泵技术将数据中心余热品位进行提升用于区域供热[2]。
许多学者对基于热泵的数据中心余热回收技术进行了研究。M. Deymi-Dashtebayaz等[3]对比了应用4种不同制冷剂的热泵对数据中心进行余热回收，结果表明与R404A、R407C、R410A相比，使用R134a为制冷剂的热泵系统具有最佳性能，COP可提高至5.47。Z. M. Marshall等[4]对比研究了在数据中心冷却中使用R161、R1234yf、R134a/R245fa等对系统性能的影响，发现使用R161的系统COP优于其他制冷剂。J. J. Monsalves等[5]预测了在丹麦利用热泵进行余热回收的一体化数据中心的性能，结果显示碳排放可减少760~1 050 kt。崔科等[6]提出利用高温热泵回收数据中心余热+市政锅炉补热的联合供热方案，发现每年将减少标煤消耗3 286.7 t。
通过上述研究可发现对数据中心进行余热回收的热泵系统多数采用GWP（全球变暖潜值，Global Warming Potential）较高的常规工质。然而，《〈蒙特利尔议定书〉基加利修正案》[7]对我国已正式生效，采用低GWP的环境友好工质是未来热泵系统发展的必然选择，其中自然工质CO2由于优良的环保特性和热物性引起了广泛关注。还可以发现前人研究的用于数据中心余热回收的热泵回收均采用常规热泵系统。当采用CO2用于供热场景时，回水温度过高导致较大的节流损失，且对数据中心的回风进行冷却过程中蒸发温度恒定，导致换热不可逆损失过大，系统整体性能偏低。
针对上述问题提出采用机械过冷技术用于改善回水温度过高时性能衰减的缺陷，并采用基于引射器的双温蒸发技术解决单温蒸发导致的空气侧换热不匹配问题。因此，本文提出了基于机械过冷的双温蒸发CO2数据中心供冷供热系统，分析其用于数据中心供冷及余热回收进行供热的性能提升及减排潜力，为数据中心制冷制热系统的优化和节能运行提供理论依据。
1 模型建立
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1.1 基本CO2数据中心冷却供热系统
基本CO2数据中心冷却供热系统如图1所示。其制冷模式包括自由冷却模式[8]（模式1）和CO2冷却供热模式（模式2）。当室外温度低于数据中心的室内温度时，系统切换至自由冷却模式；当室外温度高于数据中心的室内温度时，切换至CO2冷却供热模式，运行模式及设备如表1所示。
基本CO2系统（Base）由压缩机、气体冷却器、节流阀和蒸发器组成。从蒸发器流出的低温低压CO2蒸气经压缩机压缩后成为高温高压的过热蒸气，在气体冷却器中加热回水，加热后的热水为热用户供热。冷却后的CO2流体流经节流阀降压后成为低温低压的气液两相状态，液态CO2在蒸发器中蒸发吸收来自数据中心的热空气（DC机房回风）的热量，冷却后的空气（DC机房送风）对数据中心的发热部件进行冷却。
1.2 机械过冷CO2数据中心冷却供热系统
机械过冷CO2数据中心冷却供热系统的运行模式与基本系统一致，即当室外温度低于数据中心的室内温度时，为自由冷却模式，反之为CO2系统冷却供热模式。为避免重复，下文仅对机械过冷CO2系统进行介绍。
1.2.1 单温蒸发机械过冷CO2数据中心系统
单温蒸发机械过冷CO2数据中心冷却供热系统（DMS-SE, dedicated mechanical subcooling-single evaporator）原理如图2所示。系统由CO2循环和过冷循环构成。基于CO2循环，在其气体冷却器出口设置过冷循环，即采用常规制冷剂的蒸气压缩循环，采用R1234yf作为制冷剂，蒸发器为CO2系统的过冷器，以降低CO2节流前的温度，减小CO2的节流损失，气体冷却器和冷凝器用于加热回水，为用户供热。
1.2.2 双温蒸发机械过冷CO2数据中心系统
双温蒸发机械过冷CO2数据中心冷却供热系统（DMS-DE, dedicated mechanical subcooling-dual evaporator）原理如图3所示。
在单温蒸发机械过冷CO2数据中心冷却供热系统的基础上，增加了一个蒸发器和一个引射器。从过冷器流出的CO2作为一次流进入引射器，引射高温级蒸发器流出的二次流并混合。从引射器流出的气液两相CO2进入气液分离器，分离出的饱和液体分为两股，一股经节流阀减压进入低温级蒸发器，另一股直接进入高温级蒸发器，并与气液分离器分离出的饱和蒸气汇合进入压缩机。数据中心机房回风依次流过高温级和低温级蒸发器，实现空气的双温蒸发梯级冷却。
CO2数据中心冷却供热系统建立基于以下假设：
1）系统在稳定工况下工作；
2）引射器内的流动是一维流动，出口动能可忽略不计，一次流体和二次流体在混合室中定压混合[9]；
3）气体冷却器、冷凝器和蒸发器的窄点温差均设为5 ℃[10]；
4）气体冷却器、过冷器、冷凝器和蒸发器等换热器中的流动设置为逆流；
5）忽略各部件与管路的压降和散热损失。
系统运行参数及运行边界条件如表2所示。
2 模型分析
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2.1 数据中心负荷
数据中心的负荷PDC考虑建筑维护结构负荷Pb和IT（information technology）设备散热负荷PTT[12]，kW：
2.1.1 建筑围护结构负荷
式中：K为总传热系数，W/（m2· ℃）；A为围护结构面积，m2；tdesign为数据中心机房设计温度，℃；ta为数据中心外部环境温度，℃。
2.1.2 数据中心设备负荷
数据中心设备负荷考虑服务器（Pserver)、网络设备（Pnetwork）和配电设备（Pdis）的散热[13]，kW：
选取我国不同气候区的5个典型城市（哈尔滨、北京、上海、昆明、广州），并针对一个占地面积为2 000 m2，包括1 000个机柜（每个机柜14个服务器）的数据中心进行分析，以评估新型系统对位于不同气候区数据中心的适用性。
2.2 系统能量模型
2.2.1 DMS-SE系统能量模型
CO2循环压缩机功耗（kW）：
过冷循环制冷剂流量mMS（kg/s）：
过冷循环压缩机功耗WMS（kW）：
DMS-SE系统总压缩机功耗Wtot（kW）、制热量Qh（kW）：
式中：mCom为CO2循环压缩机中CO2的质量流量，kg/s；h为比焓，kJ/kg，其下标均为图2中对应的状态点，下标2s、2s′分别为CO2循环和过冷循环等熵压缩后的排气状态点；为CO2循环压缩机的等熵效率[14]；p1、p2分别为CO2循环压缩机的吸排气压力，MPa；ηg,MS为过冷循环压缩机等熵效率[15]，p1′、p2′分别为机械过冷循环压缩机的吸气、排气压力，MPa。
2.2.2 DMS-DE系统能量模型
DMS-DE系统在DMS-SE系统的基础上多了一个蒸发器和引射器，引射器的模型详见文献[16]。
制冷量Qc（kW）：
式中：mL,Evap、mH,Evap别为低温级、高温级蒸发器中CO2的质量流量，kg/s；各下标为图3中对应的状态点。
COP:
系统制热量、压缩机功耗计算同DMS-SE系统，不再赘述。
2.3 系统分析模型
各状态点的Ei（kW）[17]：
各部件的损ED,k（kW）：
式中：i为系统的每个状态点；EF,k和EP,k分别为第k个部件的燃料和生产, kW。
系统总损ED,tot（kW）及单位制热量的总损eD,tot（kW/kW）：
系统效率ηex：
2.4 系统碳排放分析模型
全生命周期气候性能（LCCP, life cycle climate performance）是评价系统在全生命周期碳排放的重要参数，由直接排放和间接排放两部分构成[18]：
式中：Edirect、Eindirect分别为直接碳排放、间接碳排放，t；C为制冷剂充注量，kg；L为设备平均寿命，取20 a；αALR（annual leakage rate）为年泄漏率，4%；αEOL（end of life refrigerant leakage）为寿命终时制冷剂泄漏率，15%；GWP为全球变暖潜值，kg CO2/kg；GWPAdp为制冷剂降解对应的GWP, kg CO2/kg；QAEC（annual energy consumption）为年能耗，kW·h；μEM（emissions）为碳排放系数，kg CO2/kg；m为各原材料的质量，kg；μMM（material emissions）为原材料碳排放系数，kg CO2/kg；mr（mass of recycled material）为可循环回收材料的质量，kg；μRM（recycled material）为回收材料时碳排放系数，kg CO2/kg；μRFM（refrigerant manufacturing emissions）为生产制冷剂碳排放系数，kg CO2/kg；μRFD（refrigerant disposal emissions）为处理制冷剂的碳排放系数，kg CO2/kg。
3 结果与讨论
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3.1 模型验证
将本文中的单温蒸发机械过冷CO2系统的结果与R. Llopis等[19]的理论结果进行对比，并进一步将本文带有引射器的CO2制冷循环的结果与Zhu Yinhai等[20]的实验结果进行对比，发现COP的平均相对误差分别为3.67%和5.08%，表明本文模型可靠。
3.2 冷却供热系统性能分析
图4所示为DMS-SE和DMS-DE在额定工况下COP随排气压力和过冷度的变化。可以发现，COP随排气压力和过冷度均呈现先增加后减小的变化规律。在额定工况下系统均存在最优排气压力和最优过冷度。
对于DMS-SE系统，在过冷度为13.0 ℃、排气压力为11.7 MPa时，系统COP最大为5.528；对于DMS-DE，在过冷度为10.0 ℃、排气压力为11.9 MPa时，系统COP最大为5.990，大于DMS-SE的最大COP。这是由于双温蒸发和引射器的应用，极大降低了节流和换热的不可逆损失。因此，排气压力和过冷度是影响系统性能的两个重要运行参数，以下结果均基于相应工况下的最优排气压力和过冷度进行分析。
各系统最大COP随数据中心机房送风温度的变化如图5所示。可以发现，在送风温度Tair,supply为12~22 ℃，各系统最大COP均呈上升趋势。在Tair,supply=17 ℃时，DMS-DE的COP为6.13，相对Base和DMS-SE分别提高了23.3%和15.6%。且送风温度越高，采用机械过冷技术和双温蒸发技术的能效提升越显著。在Tair,supply=22 ℃时，DMS-DE的COP相对Base和DMS-SE的提升率高达14.1%和9.0%。这是由于机械过冷可显著降低节流前CO2流体的温度，降低节流不可逆损失；引射器的引入使空气通过双温蒸发实现梯级冷却，显著降低换热过程的温差和不可逆损失，并且相对于传统单温蒸发过程，双温蒸发使压缩机的吸气压力升高，压缩比降低，压缩机的效率增加。以上两种改进技术的集成使DMS-DE能效显著提升。
两种机械过冷系统的最优过冷度随数据中心送风温度的变化如图6所示。在Tair,supply为12~22 ℃时，DMS-SE和DMS-DE最优过冷度均随送风温度的增加而降低，这是由于随蒸发温度增加，蒸发温度与气体冷却器出口温度的温差降低，节流损失减小，系统所需过冷度也逐渐减小。DMS-SE的最优过冷度始终高于DMS-DE，在Tair,supply为22 ℃时，DMS-DE的最优过冷度为5.9 ℃，比DMS-SE低2.8 ℃。这是因为DMS-SE的节流损失降低仅通过机械过冷技术实现，而对于DMS-DE，机械过冷和引射技术均可降低节流损失，但过冷度越大，引射器可回收的膨胀功越少，导致机械过冷技术和引射器技术对性能改进的贡献随过冷度呈此消彼长的关系。因此，引入引射器的DMS-DE的过冷度低于DMS-SE。
各系统的最优排气压力随数据中心送风温度的变化如图7所示。在Tair,supply为12~22 ℃时，DMS-SE和DMS-DE的排气压力随送风温度的增加而增加，Base的排气压力不断降低，DMS-DE的最优排气压力最高。这是由于DMS-SE和DMS-DE引入了机械过冷技术，由图6可知，过冷度随蒸发温度的增加而不断减小，导致节流前CO2温度升高，而最优排气压力与节流前温度呈正相关，与蒸发温度呈负相关，但节流前温度对排气压力的敏感性高于蒸发温度，因此相应的最优排气压力也升高，从Base的排气压力变化也可以看出，随着蒸发温度的升高，其排气压力变化较小；DMS-DE的过冷度相较DMS-SE偏低，导致其排气压力最高。
不同系统各部件损随送风温度的变化如图8所示。可以看到，各系统损随送风温度的升高而减小，且DMS-DE损始终小于其他两个系统。在Tair,supply为22 ℃时，DMS-DE损减小至0.19 kW/kW，比Base和DMS-SE分别降低43.26%和12.42%。这是由于DMS-DE通过机械过冷和引射器技术的集成，大幅减小了节流损失和蒸发器的换热不可逆损失。在额定工况下，DMS-DE的引射器和节流阀的损之和分别比Base和DMS-SE节流阀损降低59.3%和5.9%，同时DMS-DE双温蒸发的蒸发器损分别比以上两系统降低85.6%和78.9%。此外，压缩机损也显著降低，DMS-DE的压缩机损也分别降低43.2%和6.6%。因此，DMS-DE的损最小。
各系统在不同送风温度下的效率如图9所示。可以看出，DMS-DE的效率始终优于其他两个系统。在Tair,supply为12 ℃时，DMS-DE效率最高为0.248，比Base和DMS-SE分别提高18.7%和4.6%，这同样归功于机械过冷和引射器技术的集成。还可以发现，送风温度越低，系统效率的提升效果越显著，结合图8各部件损的结果可以看出，这是由于送风温度越低，节流、蒸发器以及压缩机的损失越大，而通过两种技术的集成，系统的节流、蒸发器换热以及压缩机不可逆损失的降低效果越显著。
各系统在不同气候区的典型城市使用时的LCCP如图10所示。可以看出，DMS-DE的碳排放量均低于Base和DMS-SE。以北京为例，DMS-DE系统的碳排放量为3 312.4 t，比Base和DMS-SE分别降低16.1%和9.3%。而碳排放量受系统所在地气候条件的影响较小，这是由于相对建筑负荷，设备负荷占数据中心总负荷的绝大比例，而设备负荷受气候条件影响不显著，故对不同城市各系统的LCCP值差异较小。
4 结论
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本文提出了基于机械过冷的双温蒸发CO2数据中心冷却供热系统（DMS-DE)，解决了供热工况较高的回水温度下系统性能衰减的问题，并改善了蒸发器空气侧换热过程的温度匹配，使数据中心余热得到高效利用。与基本CO2系统（Base）和单温蒸发机械过冷CO2系统（DMS-SE）的热力学性能进行综合对比，并进一步分析了各系统全生命周期的碳排放（LCCP)，主要结论如下：
1）DMS-SE和DMS-DE的COP随过冷度和排气压力均先增大后减小，两系统均存在最大COP、最优过冷度和排气压力。
2）采用机械过冷技术和双温蒸发技术可显著提升系统COP。在送风温度为22 ℃时，DMS-DE的COP高达6.76，相对Base和DMS-SE分别提高14.1%和9.0%。
3）采用机械过冷技术和双温蒸发技术可降低系统损，提高系统效率。在额定工况下，DMS-DE效率相对Base和DMS-SE分别提高13.24%和4.31%。
4）DMS-DE的LCCP最低，DMS-DE在北京使用时的碳排放量为3 312.4 t，比Base和DMS-SE分别降低16.1%和9.3%。
基金
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  • 中国博士后科学基金项目(2023M732582)
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参考文献 引证文献
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2025年第46卷第1期
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doi: 10.12465/j.issn.0253-4339.2025.01.086
  • 接收时间：2023-10-11
  • 首发时间：2026-03-13
  • 出版时间：2025-02-16
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  • 收稿日期：2023-10-11
  • 修回日期：2023-11-17
  • 录用日期：2024-01-04
基金
Postdoctoral Science Foundation project(2023M732582)
中国博士后科学基金项目(2023M732582)
作者信息
    1天津大学医学工程与转化医学研究院　天津　300072
    2天津市制冷技术重点实验室　天津商业大学机械工程学院　天津　300134
    3浙江国祥股份有限公司　上虞　312300

通讯作者:

刘圣春，男，教授，天津商业大学机械工程学院，13920682426，E-mail：。研究方向：自然工质替代，制冷系统节能与优化。
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https://castjournals.cast.org.cn/joweb/zlxb/CN/10.12465/j.issn.0253-4339.2025.01.086
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2种不同金属材料的力学参数
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Number of
species		 占总种数比例
Percentage of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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