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Article(id=1236345972788351557, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236345965947449499, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202412176, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=1734105600000, revisedDateStr=2024-12-14, acceptedDate=null, acceptedDateStr=null, onlineDate=1772697450110, onlineDateStr=2026-03-05, pubDate=1750780800000, pubDateStr=2025-06-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772697450110, onlineIssueDateStr=2026-03-05, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772697450110, creator=13701087609, updateTime=1772697450110, updator=13701087609, issue=Issue{id=1236345965947449499, tenantId=1146029695717560320, journalId=1210938733613449225, year='2025', volume='54', issue='6', pageStart='1', pageEnd='210', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1772697448479, creator=13701087609, updateTime=1772697609456, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1236346641175859638, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236345965947449499, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1236346641175859639, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236345965947449499, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=130, endPage=138, ext={EN=ArticleExt(id=1236345973069369939, articleId=1236345972788351557, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Cost simulation and sensitivity analysis of carbon capture, compression and liquefaction based on piperazine-based mixed amine absorbents, columnId=1236345968304640424, journalTitle=Thermal Power Generation, columnName=Innovation and process optimization of carbon capture technology, runingTitle=null, highlight=null, articleAbstract=

Post-combustion capture is a bottom-up technology for achieving carbon neutrality, but the high costs associated with carbon capture are detrimental to the application of this technology. In order to investigate the sensitivities to changes in the cost of carbon capture, compression and liquefaction, the costs incurred by different process parameters and absorbent types were modelled. The results show that, increasing the number of plates in the absorption tower promotes the efficiency of CO2 capture by absorbent, with a corresponding rise in investment costs. The increase of absorber temperature at the inlet of the absorber tower does not show a significant decrease in capture rate, but the reduction of coolant and water usage reduces the operating cost to a certain extent. In addition, the reboiling ratio has the greatest influence on the CO2 capture rate and cost, which may be the key factor for cost reduction. At the same time, the energy consumption of the system with different liquefaction pressures and different numbers of compression stages was compared, and it is found that the lower the liquefaction pressure and the higher the number of compression stages, the higher the total cost, and the equipment investment cost and operation and maintenance cost changes more obviously, while the utility costs are less affected.

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燃烧后捕集是实现碳中和的托底技术，但碳捕集所产生的高额成本不利于这项技术的应用。为了研究碳捕集、压缩和液化成本变化的敏感因素，模拟了不同工艺参数和吸收剂类型产生的成本。结果表明：增加吸收塔塔板数可以促进吸收剂对CO2的捕集效率，相应的投资成本也会升高；吸收塔进口吸收剂温度升高，捕集率未出现明显下降，反而冷却剂和水用量减少，运行成本有一定程度降低；此外，再沸比对CO2捕集率和成本影响最大，可能是降低成本的关键因素；同时，比较了不同液化压力、不同压缩级数的能耗，发现液化压力越低、压缩级数越多，总成本越高，其中设备投资成本和运营维护成本变化较明显，而公用工程成本受影响较小。

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侯大伟（1990），男，硕士，工程师，主要研究方向为CO2捕集技术与工艺模拟，。

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侯大伟（1990），男，硕士，工程师，主要研究方向为CO2捕集技术与工艺模拟，。

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侯大伟（1990），男，硕士，工程师，主要研究方向为CO2捕集技术与工艺模拟，。

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ArticleFig(id=1236390484977963792, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236345972788351557, language=EN, label=Tab.1, caption=

Main chemical reactions involved in the simulation

, figureFileSmall=null, figureFileBig=null, tableContent=
反应物反应式编号
水2H2O ↔ H3O+ + OH–(1)
H2O + HCO3–↔ H3O+ + CO32–(2)
CO2 + OH–↔ HCO3–(3)
PZPZ + CO2 + H2O ↔ PZCOO– + H3O+(4)
PZCOO– + CO2 + H2O ↔ PZ(COO–)2 + H3O+(5)
PZCOO– + CO2 + H2O ↔ H+PZCOO– + 2HCO3–(6)
H+PZCOO– + H2O ↔ PZCOO– + H3O+(7)
PZ + H3O+↔ PZH+ + H2O(8)
MEAMEA+H2O+CO2↔ MEACOO– + H3O+(9)
DEADEA+H2O+CO2↔ DEACOO– + H3O+(10)
), ArticleFig(id=1236390485082821395, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236345972788351557, language=CN, label=表1, caption=

模拟过程主要化学反应

, figureFileSmall=null, figureFileBig=null, tableContent=
反应物反应式编号
水2H2O ↔ H3O+ + OH–(1)
H2O + HCO3–↔ H3O+ + CO32–(2)
CO2 + OH–↔ HCO3–(3)
PZPZ + CO2 + H2O ↔ PZCOO– + H3O+(4)
PZCOO– + CO2 + H2O ↔ PZ(COO–)2 + H3O+(5)
PZCOO– + CO2 + H2O ↔ H+PZCOO– + 2HCO3–(6)
H+PZCOO– + H2O ↔ PZCOO– + H3O+(7)
PZ + H3O+↔ PZH+ + H2O(8)
MEAMEA+H2O+CO2↔ MEACOO– + H3O+(9)
DEADEA+H2O+CO2↔ DEACOO– + H3O+(10)
), ArticleFig(id=1236390485170901785, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236345972788351557, language=EN, label=Tab.2, caption=

Main parameters involved in the simulation

, figureFileSmall=null, figureFileBig=null, tableContent=
项目参数数值
入口烟气温度/℃40
压力/kPa100
烟气体积流量/(m3·h–1)10 000
吸收塔塔板数15
贫液温度/℃40
压力/kPa100
吸收剂体积流量/(m3·h–1)45
CO2负荷/(mol·mol–1)0.10~0.17
再生塔塔板数12
富液泵压力/Pa2
富液温度/℃50~55
CO2负荷/(mol·mol–1)0.56~0.70
), ArticleFig(id=1236390485233816348, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236345972788351557, language=CN, label=表2, caption=

模拟主要参数

, figureFileSmall=null, figureFileBig=null, tableContent=
项目参数数值
入口烟气温度/℃40
压力/kPa100
烟气体积流量/(m3·h–1)10 000
吸收塔塔板数15
贫液温度/℃40
压力/kPa100
吸收剂体积流量/(m3·h–1)45
CO2负荷/(mol·mol–1)0.10~0.17
再生塔塔板数12
富液泵压力/Pa2
富液温度/℃50~55
CO2负荷/(mol·mol–1)0.56~0.70
), ArticleFig(id=1236390485342868258, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236345972788351557, language=EN, label=Tab.3, caption=

Parameters related to the simulated flow strand of the CO2 compression liquefaction and purification system

, figureFileSmall=null, figureFileBig=null, tableContent=
项目流股1流股2流股3流股4流股5流股6流股7流股8流股9流股10流股11
温度/℃10.97110.99112020124-20
压力/kPa110202090.342020122.136606602 0002 000
质量流量/
(kg·h–1)		1 0001 000988988988983983983980980980
摩尔焓/
(kJ·(kg·mol)–1)		-382 880-387 659-390 534-387 808-391 134-392 437-388 467-392 939-393 682-389 782-409 027
热流/(kJ·h–1)-8 964 650-9 076 549-8 8907 559-8 8286 959-89 044 089-88 239 179
), ArticleFig(id=1236390485565166375, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236345972788351557, language=CN, label=表3, caption=

CO2压缩液化和净化系统模拟流股相关参数

, figureFileSmall=null, figureFileBig=null, tableContent=
项目流股1流股2流股3流股4流股5流股6流股7流股8流股9流股10流股11
温度/℃10.97110.99112020124-20
压力/kPa110202090.342020122.136606602 0002 000
质量流量/
(kg·h–1)		1 0001 000988988988983983983980980980
摩尔焓/
(kJ·(kg·mol)–1)		-382 880-387 659-390 534-387 808-391 134-392 437-388 467-392 939-393 682-389 782-409 027
热流/(kJ·h–1)-8 964 650-9 076 549-8 8907 559-8 8286 959-89 044 089-88 239 179
), ArticleFig(id=1236390485695189801, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236345972788351557, language=EN, label=Tab.4, caption=

Annual average exchange rate of USD to RMB from 2019 to 2023

, figureFileSmall=null, figureFileBig=null, tableContent=
年份201920202021202220232019—2023
年平均汇率6.936.926.476.757.106.83
), ArticleFig(id=1236390485833601836, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236345972788351557, language=CN, label=表4, caption=

2019—2023年美元对人民币年平均汇率

, figureFileSmall=null, figureFileBig=null, tableContent=
年份201920202021202220232019—2023
年平均汇率6.936.926.476.757.106.83
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基于哌嗪类复配胺吸收剂的碳捕集、压缩液化成本模拟及敏感性分析
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侯大伟
热力发电 | 碳捕集技术创新与工艺优化 2025,54(6): 130-138
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热力发电 | 碳捕集技术创新与工艺优化 2025, 54(6): 130-138
基于哌嗪类复配胺吸收剂的碳捕集、压缩液化成本模拟及敏感性分析
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侯大伟
作者信息
  • 中国大唐集团科学技术研究总院有限公司华东电力试验研究院，合肥　安徽　230088

    • 侯大伟（1990），男，硕士，工程师，主要研究方向为CO2捕集技术与工艺模拟，。

Cost simulation and sensitivity analysis of carbon capture, compression and liquefaction based on piperazine-based mixed amine absorbents
Dawei HOU
Affiliations
  • China Datang Corporation Science and Technology General Research Institute Co Ltd East China Electric Power Test & Research Institute, Hefei 230088, China
出版时间: 2025-06-25 doi: 10.19666/j.rlfd.202412176
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摘要
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燃烧后捕集是实现碳中和的托底技术，但碳捕集所产生的高额成本不利于这项技术的应用。为了研究碳捕集、压缩和液化成本变化的敏感因素，模拟了不同工艺参数和吸收剂类型产生的成本。结果表明：增加吸收塔塔板数可以促进吸收剂对CO2的捕集效率，相应的投资成本也会升高；吸收塔进口吸收剂温度升高，捕集率未出现明显下降，反而冷却剂和水用量减少，运行成本有一定程度降低；此外，再沸比对CO2捕集率和成本影响最大，可能是降低成本的关键因素；同时，比较了不同液化压力、不同压缩级数的能耗，发现液化压力越低、压缩级数越多，总成本越高，其中设备投资成本和运营维护成本变化较明显，而公用工程成本受影响较小。

碳排放  /  碳捕集  /  碳交易  /  压缩和液化  /  成本

Post-combustion capture is a bottom-up technology for achieving carbon neutrality, but the high costs associated with carbon capture are detrimental to the application of this technology. In order to investigate the sensitivities to changes in the cost of carbon capture, compression and liquefaction, the costs incurred by different process parameters and absorbent types were modelled. The results show that, increasing the number of plates in the absorption tower promotes the efficiency of CO2 capture by absorbent, with a corresponding rise in investment costs. The increase of absorber temperature at the inlet of the absorber tower does not show a significant decrease in capture rate, but the reduction of coolant and water usage reduces the operating cost to a certain extent. In addition, the reboiling ratio has the greatest influence on the CO2 capture rate and cost, which may be the key factor for cost reduction. At the same time, the energy consumption of the system with different liquefaction pressures and different numbers of compression stages was compared, and it is found that the lower the liquefaction pressure and the higher the number of compression stages, the higher the total cost, and the equipment investment cost and operation and maintenance cost changes more obviously, while the utility costs are less affected.

carbon emissions  /  carbon capture  /  carbon trading  /  compression and liquefaction  /  costs
侯大伟. 基于哌嗪类复配胺吸收剂的碳捕集、压缩液化成本模拟及敏感性分析. 热力发电, 2025 , 54 (6) : 130 -138 . DOI: 10.19666/j.rlfd.202412176
Dawei HOU. Cost simulation and sensitivity analysis of carbon capture, compression and liquefaction based on piperazine-based mixed amine absorbents[J]. Thermal Power Generation, 2025 , 54 (6) : 130 -138 . DOI: 10.19666/j.rlfd.202412176
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全球温度持续升高，联合国政府间气候变化专门委员会（IPCC）AR6综合报告指出，2011—2020年全球地表温度比1850—1900年的全球地表温度高出1.09 ℃[1]。在各国签订的《巴黎协定》中，要求参与成员提交并实行CO2减排计划，将全球气温升高限制在工业化前期的1.5~2.0 ℃[2]。然而，从当前的升温形势来看，我们正处于错失控制全球升温1.5 ℃目标的边缘[3]。
化石燃料燃烧是人类活动向环境排放CO2的主要途径[4]，CO2作为一种主要的温室气体（greenhouse gas，GHG），其在大气中含量升高会给环境带来诸多不利影响，例如全球变暖、气候变化和粮食危机等[5-6]。清洁能源（核能、太阳能及潮汐能等）具有经济和环保效益[7]，在减少人们对化石燃料的依赖方面具有巨大潜力。近年来，在各项政策支持下，清洁能源在能源市场的份额处于增长状态，但清洁能源的不稳定性和不确定性，导致化石燃料依然占有极高的使用量（约83%）[8-9]，CO2大量排放依然还是一个无法避免的问题。
在众多燃烧后CO2捕集（post-combustion capture，PCC）技术中，胺溶液吸收法可用于低浓度CO2烟气捕集，且技术成熟、改造成本低，广泛用于捕集燃煤电厂烟气中CO2气体[10-11]。高昂的捕集成本是限制胺溶液吸收剂法大规模应用的主要因素，例如乙醇胺（MEA）工艺对CO2捕集非常有效，其再生能量高达3.7~4.0 GJ/t[12-14]，这远高于可接受的能耗值（0.72 GJ/t）[15]。DWSIM软件被广泛用于胺溶液捕集工艺仿真，可预测CO2捕集工艺和工况对能耗成本的影响。例如Xu等人[16]使用DWSIM软件模拟了N-甲基二乙醇胺（MDEA）用于250 MW整体煤气化联合循环（IGCC）的碳捕集效果，在对煤气化装置工艺优化后，捕集能耗大幅度降低到了50%以下。Tiwari等人[17]评估了哌嗪（PZ）、三乙烯四胺（TETA）和N-甲基二乙醇胺（MDEA）混合吸收剂在430 MW发电厂碳捕集的经济性，通过优化吸收剂配方，可大幅度降低碳捕集成本，最低可下降27.33%的运行成本。Gabriela等人[18]使用DWSIM软件对比了共晶溶剂（氯化胆碱和MEA组成）和质量分数30%的MEA在350 MW发电厂烟气碳捕集的捕集效率，结果表明，共晶溶剂在40 ℃和环境压力下的CO2吸收性能是MEA的2倍。
通过压缩液化技术，CO2气体可以被转换为液态，这极大地减小了其体积，从而在传输和储存的过程中减少了对空间的需求。目前，CO2的主要利用方式之一就是进行直接液化，通过化学方法把它转化成液体形式的燃料。经过液化处理的CO2在地下或其他合适的存储位置更为容易保存，在碳捕获利用与封存（carbon capture utilization and storage，CCUS）系统的传输和封存环节中，这一点显得尤为关键，尤其是在进行长距离管道传输和地下封存的过程中。当前，使用最广泛的方法是利用高压CO2直接进行低温液体的液化。因此，CO2压缩液化技术是其中的关键环节之一，如何有效降低CO2压缩和液化的成本CCUS也是推动CCUS技术商业化应用的关键问题之一[19-21]。
本文基于DWSIM软件模拟工艺参数、吸收剂种类相应的碳捕集、压缩和液化成本，研究这些因素所导致的成本变化趋势及分析敏感因素，为降低碳捕集、压缩液化成本提供一定的理论基础。
1　成本计算方法
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1.1　CO2捕集成本分析方法
模拟烟气成分为：CO2、N2、H2O和O2的体积分数分别为13.50%、69.93%、13.02%、3.55%，其中13.5%的CO2参考了经湿式电除尘处理后烟气中CO2（湿基）体积分数范围在12%~15%。由于文中主要讨论吸收-再生成本变化，模拟的碳捕集工艺中没有设置预处理塔，假设烟气的SO2和SO3等微量物质已经被预处理塔完全脱除。
哌嗪（PZ）是一种被常用于碳捕集的环胺，有着比MEA更高的吸收负荷和吸收速率[22]，然而PZ产物的难溶性限制了其在溶液中的浓度[23]。因此，本文选择质量分数20%的PZ、10%PZ+10%MEA、10%PZ+10%二乙醇胺DEA的水溶液作为模拟溶剂，模拟不同工艺条件对吸收剂捕集率和捕集成本的影响。
基于PR状态方程和电解质非随机双液活度系数模型，使用DWSIM软件构建CO2净化系统，具体的化学反应式见表1。
工艺模拟中涉及的主要操作条件和流程分别见表2和图1。
1.2　CO2捕集成本核算
CO2捕集涉及的成本由总投资成本、运营维护成本、公用工程成本（设备运行的用水，用电和蒸汽使用费用）3部分组成。其中，总投资成本包括设备成本（吸收塔、再生）和安装成本。运营维护成本可分为固定成本和可变成本。固定成本由维护成本和运营劳动力成本组成，维护成本按设备安装成本（EIC）的3%确定，运营劳动力成本取决于工人的数量和全年的运营时间。公用工程成本包括水耗、电耗、制冷剂和蒸汽的费用。
1.3　CO2压缩液化成本核算
图2为CO2压缩液化和净化系统工艺流程。利用DWSIM软件在中压压缩液化方式基础上对CO2压缩液化和净化系统工艺流程进行模拟，液化过程模拟参数见表3。
气源采用有机胺吸收捕集到的CO2和H2O混合气，其摩尔比为0.95:0.05，温度为103.1 ℃，压力为110 kPa，模拟系统中原料气质量流量设置为1 000 kg/h。其中，泵和压缩机的绝热效率为75%，换热器采用简单加权模型，压降设置为0。直接利用DWSIM软件中的经济分析功能对CO2压缩液化流程进行成本分析。根据软件设置，项目使用寿命为5年，每年运行8 000 h。
CO2压缩液化成本由总投资成本、运营维护成本、公用工程成本3部分组成。根据CO2压缩液化成本构成可以看到，总费用与设备的选择、流程运行过程紧密相关。故在此部分详细探究CO2不同液化压力、压缩级数对费用的影响。级间冷却压力均为20 ℃，且压缩过程均是等比压缩。
分析液化压力对成本影响时，选择常温高压压缩、中压压缩和低温低压压缩3种液化压力，通过常温高压压缩将气源压缩至30 ℃、7 600 kPa，通过中压压缩将气源压缩至-24 ℃、2 000 kPa，通过低温低压压缩将气源压缩至-50 ℃、800 kPa。分析压缩级数对成本影响时，在中压压缩方案的基础上，对压缩液化流程分别进行3级压缩、4级压缩、5级压缩以及6级压缩分析。
2　结果与讨论
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2.1　碳捕集工艺流程
目前，工业CCUS工艺主要流程如图3所示。吸收剂在吸收塔中与烟气逆向接触，脱碳后的烟气从吸收塔上方流出，并进入水洗塔，净化后排入大气。富集CO2的吸收剂经富相泵从吸收塔下方流入贫富液热交换器，换热后进入解吸塔再生，再生过程会形成CO2混合气体和贫液，其中CO2混合气体经冷却、分离后，进入下一个阶段。贫液通过换热器和冷却器降温并达到目标温度后进入吸收塔，吸收剂构成循环。本研究主要分析CO2吸收-再生的成本及敏感性，因此，没有建立关于脱碳烟气水洗净化的流程。
2.2　CO2捕集系统成本模拟结果
2.2.1　吸收剂种类对碳捕集工艺成本影响
根据对2019—2023年美元对人民币的平均汇率统计（表4），按平均汇率计算吸收剂种类对碳捕集工艺成本。
图4为吸收剂种类对碳捕集率和成本的影响。由图4可见，在不改变工艺参数情况下，吸收剂种类的变化对捕集效果有明显影响，PZ、PZ-MEA和PZ-DEA对CO2的捕集率分别在97%、94%和86%，碳捕集率变化和有机胺对CO2的反应动力学相关，反应动力学从快到慢的排序为PZ>MEA>DEA[24-35]。由于它们的工艺参数相同，吸收塔和再生塔的建设和安装成本相近，它们的成本差异主要集中在蒸汽使用、冷却水使用、换热器等。PZ和PZ-MEA的投资成本、维护成本和公共成本相近，PZ-DEA的3项成本明显低于PZ和PZ-MEA，这可能与PZ-DEA的捕集率低有关。CO2与有机胺的化学反应属于放热反应[36-37]，因此捕集率低的吸收剂离开吸收塔的温度更低，与富相换热效果更好。例如PZ、PZ-MEA和PZ-DEA进入贫液冷却器时的温度分别是73、72、68 ℃，这有利于减少制冷剂的使用。
2.2.2　吸收剂进口温度对碳捕集效率和成本影响
吸收塔吸收剂进口温度对捕集效率和成本的影响如图5所示。由图5可见，吸收塔吸收剂进口温度变化对捕集率没有产生明显影响，PZ、PZ-MEA和PZ-DEA的碳捕集率分别处于97%、94%和86%。吸收塔进液温度降低对冷却的要求有所提高，可以看到，随着吸收液进口温度的下降，3项成本均有所增长，其中PZ的成本增长量大于PZ-MEA，PZ-DEA的成本增长不显著，吸收剂PZ的捕集成本受吸收液进口温度影响变化最为敏感，其次是PZ-MEA。
2.2.3　吸收塔塔板数对碳捕集效率和成本影响
吸收塔塔板数对捕集效率和成本的影响如图6所示。减少吸收塔塔板数量对碳捕集率有不利影响，3种吸收剂对CO2的捕集效果均有所下降。此外，吸收塔塔板数变化对投资成本也有着明显影响，吸收塔塔板数越少投资成本越低，而维护成本和公用成本的波动相对于投资成本波动较小。除了PZ-DEA在塔板数为15时的碳捕集效率低于90%，其余情况下碳捕集效率均大于90%，合理的塔板数对减少CCUS建设成本越有利。
2.2.4　再沸比对碳捕集效率和成本影响
再沸比对捕集效率和成本的影响如图7所示。由图7a)可见，随着再沸比的增加，再生塔出口贫液负荷逐渐减少，吸收剂循环容量升高，PZ、PZ-MEA和PZ-DEA的碳捕集率有所提升。在成本变化趋势上，3种吸收剂也表现出了相同的变化趋势，再沸比增加需要更多的蒸汽加大塔底的蒸发量，蒸汽量增大是导致运行成本增加的主要因素。此外，增大再沸比也会增大再沸器成本。例如PZ再沸比2.5的再沸器成本是再沸比为1.5的170%（图7b)—图7d)）。
从碳捕集效果方面可以看出，吸收塔吸收剂进口温度对碳捕集效率的影响较小，吸收塔塔板数和再沸比对吸收剂碳捕集效果均一定影响，随着再沸比和塔板数增加，吸收剂捕集效果越好。在成本波动方面，再沸比变化对捕集成本影响最为敏感。不同的吸收剂虽然工艺条件改变后表现出了相同的变化规律，但敏感度有所区别，例如从塔板数对吸收剂的捕集效果影响来看，PZ-DEA捕集率变化幅度大于其他2种吸收剂，此外，再沸比对PZ的捕集成本变化幅度要大于PZ-MEA和PZ-DEA。
2.3　压缩液化系统敏感性分析
设备总投资成本为689万元/a，运行维护成本1 254万元/a，公用工程成本72万元/a，总成本为2 015万元/a。
图8和图9为不同液化压力条件下的相关成本。从图8可见，高压压缩液化条件下，设备投资成本、运营维护成本以及公用工程成本均为最大，随着液化压力降低，不同成本呈不同程度下降趋势，其中设备投资成本变化最明显。由图9可见，随着液化压力降低，设备成本比例降低，运营维护成本比例增加，公用工程成本比例几乎不变。
图10和图11为不同压缩级数下CO2压缩液化系统成本相关参数。
由图10可知，随着压缩级数增加，设备投资成本、运营维护成本均增加，公用工程成本几乎没变化。由图11可知，随着压缩级数增加，设备投资成本的比列增加，运营维护成本比例降低，公用工程成本比例变化并不明显。
综上，CO2压缩液化净化系统总成本与液化条件、压缩级数有关，液化压力越低、压缩级数越多，总成本越高，其中设备投资成本和运营维护成本变化较明显，公用工程受影响较小。
3　结论
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本文使用DWSIM软件对碳捕集、压缩和液化成本进行模拟，在满足碳捕集率大于85%的前提下，比较工艺参数对碳捕集效果和成本的影响，分析工艺对捕集、压缩和液化成本的敏感性，研究结果如下。
1）吸收塔吸收剂进口温度对捕集和成本变化影响较低，吸收塔塔板数和再沸比对碳捕集率存在影响。其中，PZ-DEA的碳捕集率受塔板数变化影响尤为明显。此外，与其他2个参数相比，再沸比对成本的影响波动最大，影响成本的敏感性最高。
2）CO2压缩液化净化系统的总成本与液化条件和压缩级数密切相关。液化压力越低、压缩级数越多，系统的总成本就会越高。设备投资成本和运营维护成本会随着液化压力的降低和压缩级数的增加而增加，而公用工程成本方面的影响相对较小。
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doi: 10.19666/j.rlfd.202412176
  • 首发时间：2026-03-05
  • 出版时间：2025-06-25
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    中国大唐集团科学技术研究总院有限公司华东电力试验研究院，合肥　安徽　230088
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