Article(id=1295064787893903600, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1295064706872528996, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202506132, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1751212800000, receivedDateStr=2025-06-30, revisedDate=1756569600000, revisedDateStr=2025-08-31, acceptedDate=1756915200000, acceptedDateStr=2025-09-04, onlineDate=1786697106573, onlineDateStr=2026-08-14, pubDate=1771948800000, pubDateStr=2026-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1786697106573, onlineIssueDateStr=2026-08-14, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1786697106573, creator=13701087609, updateTime=1786697106573, updator=13701087609, issue=Issue{id=1295064706872528996, tenantId=1146029695717560320, journalId=1210938733613449225, year='2026', volume='55', issue='2', pageStart='1', pageEnd='192', issueExtLink='null', onlineDate='null', pubDate='1771948800000', pubDateStr='2026-02-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1786697087257, creator='13701087609', updateTime=1786698896936, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1295072297266733103, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1295064706872528996, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1295072297266733104, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1295064706872528996, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=95, endPage=107, ext={EN=ArticleExt(id=1295064788355277041, articleId=1295064787893903600, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Thermodynamic decoupling and peak-shaving research on a 660 MW coal-fired unit coupled with AA-CAES system, columnId=1295064787906490372, journalTitle=Thermal Power Generation, columnName=Peak shaving and frequency regulation technology for energy storage system coupled with thermal power unit, runingTitle=null, highlight=null, articleAbstract=

The large-scale integration of renewable energy poses significant challenges to the peak-shaving capacity of coal-fired units. To enhance operational flexibility and address energy flow conflicts in typical coal-fired systems coupled with compressed air energy storage systems during peak shaving, this study investigates a 660 MW coal-fired unit using EBSILON software. Three energy storage schemes and two energy release schemes are proposed and evaluated through thermo-economic analysis, focusing on thermal-time decoupling capability, peak-shaving paradox elimination, and system performance. The results show that during energy storage, the scheme utilizing intermediate-pressure cylinder exhaust for thermal oil heating achieves the highest thermal storage gain ratio (1.370) and the lowest heat rate (8 814.976 kJ/(kW·h)). During energy release, the scheme absorbing heat from No.3 high-pressure heater drain outlet yields the minimum heat rate (7 547.945 kJ/(kW·h)). After 8 hours of operation, the system retains 38.503 MW·h of utilizable thermal energy and reduces the peak-shaving paradox index to –0.041. Parameter optimization improves the round-trip efficiency of the compressed air energy storage system by 2.702 percentage points and increases the unit’s peak-shaving depth by 2.481%. This study provides a viable solution for synergistic optimization of coal-fired units and energy storage systems.

, authors=Chuankun XU1, Jie ZHANG2, Xingchi MA1, Lei LI2, authorsList=Chuankun XU, Jie ZHANG, Xingchi MA, Lei LI, authorCompany=null, correspAuthors=Jie ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1295064792952234257, articleId=1295064787893903600, tenantId=1146029695717560320, journalId=1210938733613449225, language=CN, title=660 MW燃煤机组与AA-CAES耦合系统热解耦及调峰研究, columnId=1295064788145565702, journalTitle=热力发电, columnName=储能系统耦合火电机组调峰调频技术, runingTitle=null, highlight=null, articleAbstract=

可再生能源装机大规模并网给燃煤机组调峰带来严峻挑战。为提高燃煤机组的灵活调节能力并解决典型压缩空气储能系统与燃煤机组耦合系统调峰过程中的能量矛盾,以660 MW燃煤机组为研究对象,基于EBSILON软件,提出了3种储能耦合方案与2种释能耦合方案,对不同储能、释能耦合方案采用热经济性指标进行对比,并对耦合系统的热能-时间解耦能力、消除调峰悖论能力和调峰性能进行分析。结果表明:在储能阶段,抽取中压缸排汽加热导热油方案具有最高的储热增益比1.370和最低的热耗率8 814.976 kJ/(kW·h);在释能阶段,抽取3号高压加热器疏水出口吸收导热油热能方案具有最低的热耗率7 547.945 kJ/(kW·h);经过8 h储热,耦合系统仍维持38.503 MW·h有效利用热能,且调峰悖论指数降低至–0.041。通过改变空气参数可使压缩空气储能系统往返效率提升2.702百分点,燃煤机组调峰深度提升了2.481%。研究结果为燃煤机组与储能系统协同优化提供了可行方案。

, authors=徐传坤1, 张杰2, 马行驰1, 李磊2, authorsList=徐传坤, 张杰, 马行驰, 李磊, authorCompany=null, correspAuthors=张杰, authorNote=

徐传坤(2001),男,硕士研究生,主要研究方向为压缩空气储能系统耦合,

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张杰(1980),男,硕士,高级工程师,主要研究方向为压缩空气储能系统优化,
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caption=膨胀机空气质量流量对综合能源利用率与CAES系统往返效率的影响, figureFileSmall=0sHq7sjdgNZemErT9lNKNw==, figureFileBig=bItsWXUMDFoBwYINnPgZ1g==, tableContent=null), ArticleFig(id=1295064801315676500, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=EN, label=Fig.13, caption=Impact of the compressor air mass flow rate on downward peak regulation capacity of the unit, figureFileSmall=/HLpD32qJsC/B6veww7hug==, figureFileBig=tmmn/adFtWX7Q8rzICMrOg==, tableContent=null), ArticleFig(id=1295064801391173973, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=CN, label=图13, caption=压缩机入口空气质量流量对燃煤机组向下调峰容量的影响, figureFileSmall=/HLpD32qJsC/B6veww7hug==, figureFileBig=tmmn/adFtWX7Q8rzICMrOg==, tableContent=null), ArticleFig(id=1295064801449894230, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=EN, label=Fig.14, caption=Effect of the compressor inlet air mass flow rate on peak-shaving depth of the coal-fired power unit, figureFileSmall=ciM3oXnP1rdaSXkApT78Qg==, figureFileBig=5Ui1EgG4OXU6N6HKyd8iqw==, tableContent=null), ArticleFig(id=1295064801592500567, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=CN, label=图14, caption=压缩机入口空气质量流量对燃煤机组调峰深度的影响, figureFileSmall=ciM3oXnP1rdaSXkApT78Qg==, figureFileBig=5Ui1EgG4OXU6N6HKyd8iqw==, tableContent=null), ArticleFig(id=1295064801663803736, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=EN, label=Tab.1, caption=

Main parameters settings and verification results of the AA-CAES system

, figureFileSmall=null, figureFileBig=null, tableContent=
项目设计值模拟值相对误差/%
环境温度/℃25250
压缩机额定功率/MW20.00020.015+0.075
膨胀机额定功率/MW20.00020.0000
储能时长/h220
释能时长/h1.1901.1900
蓄冷罐压力/MPa0.6000.6000
蓄热罐压力/MPa0.6000.598–0.333
储气压力/MPa10.00010.0000
膨胀机工作压力/MPa9.5009.5000
压缩机入口温度/℃45450
膨胀机入口温度/℃1741740
往返效率/%59.50059.450–0.084
), ArticleFig(id=1295064801756078425, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=CN, label=表1, caption=

AA-CAES系统主要参数设置与验证结果

, figureFileSmall=null, figureFileBig=null, tableContent=
项目设计值模拟值相对误差/%
环境温度/℃25250
压缩机额定功率/MW20.00020.015+0.075
膨胀机额定功率/MW20.00020.0000
储能时长/h220
释能时长/h1.1901.1900
蓄冷罐压力/MPa0.6000.6000
蓄热罐压力/MPa0.6000.598–0.333
储气压力/MPa10.00010.0000
膨胀机工作压力/MPa9.5009.5000
压缩机入口温度/℃45450
膨胀机入口温度/℃1741740
往返效率/%59.50059.450–0.084
), ArticleFig(id=1295064801873518938, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=EN, label=Tab.2, caption=

Comparison between the design and simulation values of coal-fired unit under THA working condition

, figureFileSmall=null, figureFileBig=null, tableContent=
项目设计值模拟值相对误差%
额定负荷/MW6606600
主蒸汽压力/MPa28280
主蒸汽流量/(kg·s–1521.490526.867+1.029
主蒸汽温度/℃6006000
再热蒸汽压力/MPa5.5395.5390
再热蒸汽温度/℃6206200
背压/MPa0.011 50.011 50
), ArticleFig(id=1295064802020319579, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=CN, label=表2, caption=

THA工况下燃煤机组设计值与模拟值对比

, figureFileSmall=null, figureFileBig=null, tableContent=
项目设计值模拟值相对误差%
额定负荷/MW6606600
主蒸汽压力/MPa28280
主蒸汽流量/(kg·s–1521.490526.867+1.029
主蒸汽温度/℃6006000
再热蒸汽压力/MPa5.5395.5390
再热蒸汽温度/℃6206200
背压/MPa0.011 50.011 50
), ArticleFig(id=1295064802108399964, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=EN, label=Tab.3, caption=

Comparison between the design and simulation values of coal-fired unit under 30%THA working condition

, figureFileSmall=null, figureFileBig=null, tableContent=
项目设计值模拟值相对误差/%
输出功率/MW1981980
主蒸汽压力/MPa10100
主蒸汽流量/(kg·s–1160.251161.264+0.632
主蒸汽温度/℃6006000
再热蒸汽压力/MPa1.6041.6040
再热蒸汽温度/℃5705700
背压/MPa0.011 50.011 50
), ArticleFig(id=1295064802171314525, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=CN, label=表3, caption=

30%THA工况下燃煤机组设计值与模拟值对比

, figureFileSmall=null, figureFileBig=null, tableContent=
项目设计值模拟值相对误差/%
输出功率/MW1981980
主蒸汽压力/MPa10100
主蒸汽流量/(kg·s–1160.251161.264+0.632
主蒸汽温度/℃6006000
再热蒸汽压力/MPa1.6041.6040
再热蒸汽温度/℃5705700
背压/MPa0.011 50.011 50
), ArticleFig(id=1295064802238423390, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=EN, label=Tab.4, caption=

Simulation results of the coupling schemes in energy storage stage

, figureFileSmall=null, figureFileBig=null, tableContent=
项目原始机组方案1方案2方案3
热耗率/(kJ·(kW·h)–18 512.5419 069.9748 833.1028 814.976
储热增益比0.6451.3581.370
标准煤耗率/(g·(kW·h)–1315.877336.561327.772327.099
抽汽温度/℃352.016377.183272.183
抽汽量/(kg·s–11817.50060
), ArticleFig(id=1295064802330698079, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=CN, label=表4, caption=

储能阶段耦合方案模拟结果对比

, figureFileSmall=null, figureFileBig=null, tableContent=
项目原始机组方案1方案2方案3
热耗率/(kJ·(kW·h)–18 512.5419 069.9748 833.1028 814.976
储热增益比0.6451.3581.370
标准煤耗率/(g·(kW·h)–1315.877336.561327.772327.099
抽汽温度/℃352.016377.183272.183
抽汽量/(kg·s–11817.50060
), ArticleFig(id=1295064802402001248, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=EN, label=Tab.5, caption=

Simulation results of the coupling schemes at the energy release stage

, figureFileSmall=null, figureFileBig=null, tableContent=
项目原始机组方案1方案2
汽轮机组热耗率/(kJ·(kW·h)–17 600.4327 547.9457 548.129
热效率/%47.70247.615
标准煤耗率/(g·(kW·h)–1282.031280.107280.106
除氧器抽汽量/(kg·s–119.09519.428
), ArticleFig(id=1295064802502664545, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=CN, label=表5, caption=

释能阶段耦合方案模拟结果

, figureFileSmall=null, figureFileBig=null, tableContent=
项目原始机组方案1方案2
汽轮机组热耗率/(kJ·(kW·h)–17 600.4327 547.9457 548.129
热效率/%47.70247.615
标准煤耗率/(g·(kW·h)–1282.031280.107280.106
除氧器抽汽量/(kg·s–119.09519.428
), ArticleFig(id=1295064802582356322, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=EN, label=Tab.6, caption=

Comparison of thermal economic parameters between the original unit and the coupling system

, figureFileSmall=null, figureFileBig=null, tableContent=
项目原始机组储能阶段释能阶段
汽轮机组热耗率/(kJ·(kW·h)–17 600.4328 814.9767 547.945
热效率/%47.732
标准煤耗率/(g·(kW·h)–1282.031327.099280.107
储能增益比1.370
), ArticleFig(id=1295064802641076579, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=CN, label=表6, caption=

原始机组与耦合系统热经济性参数对比

, figureFileSmall=null, figureFileBig=null, tableContent=
项目原始机组储能阶段释能阶段
汽轮机组热耗率/(kJ·(kW·h)–17 600.4328 814.9767 547.945
热效率/%47.732
标准煤耗率/(g·(kW·h)–1282.031327.099280.107
储能增益比1.370
), ArticleFig(id=1295064802712379748, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=EN, label=Tab.7, caption=

Comparison of peak regulation performance between the proposed coupling system and the one in literature [22]

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项目文献[22]值本文耦合系统模拟值
原始机组出力/MW210.000210.000
燃煤机组实际出力/MW221.000201.621
压缩机耗功/MW81.00021.220
调峰悖论指数0.050–0.041
), ArticleFig(id=1295064802850791781, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064787893903600, language=CN, label=表7, caption=

本文耦合系统与文献[22]系统调峰性能对比

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项目文献[22]值本文耦合系统模拟值
原始机组出力/MW210.000210.000
燃煤机组实际出力/MW221.000201.621
压缩机耗功/MW81.00021.220
调峰悖论指数0.050–0.041
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660 MW燃煤机组与AA-CAES耦合系统热解耦及调峰研究
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徐传坤 1 , 张杰 2 , 马行驰 1 , 李磊 2
热力发电 | 储能系统耦合火电机组调峰调频技术 2026,55(2): 95-107
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热力发电 |储能系统耦合火电机组调峰调频技术 2026 , 55 (2) : 95 -107
660 MW燃煤机组与AA-CAES耦合系统热解耦及调峰研究
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徐传坤1 , 张杰2 , 马行驰1, 李磊2
作者信息
  • 1.上海电力大学能源与机械工程学院,上海 200090
  • 2.中国电力工程顾问集团华东电力设计院有限公司,上海 200063
通讯作者:
张杰(1980),男,硕士,高级工程师,主要研究方向为压缩空气储能系统优化,
作者简介:

徐传坤(2001),男,硕士研究生,主要研究方向为压缩空气储能系统耦合,

Thermodynamic decoupling and peak-shaving research on a 660 MW coal-fired unit coupled with AA-CAES system
Chuankun XU1 , Jie ZHANG2 , Xingchi MA1, Lei LI2
Affiliations
  • 1.College of Energy and Mechanical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
  • 2.China Power Engineering Consulting Group East China Electric Power Institute, Shanghai 200063, China
出版时间: 2026-02-25 doi: 10.19666/j.rlfd.202506132
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可再生能源装机大规模并网给燃煤机组调峰带来严峻挑战。为提高燃煤机组的灵活调节能力并解决典型压缩空气储能系统与燃煤机组耦合系统调峰过程中的能量矛盾,以660 MW燃煤机组为研究对象,基于EBSILON软件,提出了3种储能耦合方案与2种释能耦合方案,对不同储能、释能耦合方案采用热经济性指标进行对比,并对耦合系统的热能-时间解耦能力、消除调峰悖论能力和调峰性能进行分析。结果表明:在储能阶段,抽取中压缸排汽加热导热油方案具有最高的储热增益比1.370和最低的热耗率8 814.976 kJ/(kW·h);在释能阶段,抽取3号高压加热器疏水出口吸收导热油热能方案具有最低的热耗率7 547.945 kJ/(kW·h);经过8 h储热,耦合系统仍维持38.503 MW·h有效利用热能,且调峰悖论指数降低至–0.041。通过改变空气参数可使压缩空气储能系统往返效率提升2.702百分点,燃煤机组调峰深度提升了2.481%。研究结果为燃煤机组与储能系统协同优化提供了可行方案。

压缩空气储能系统  /  燃煤机组  /  耦合系统  /  热解耦  /  深度调峰  /  调峰悖论  /  往返效率

The large-scale integration of renewable energy poses significant challenges to the peak-shaving capacity of coal-fired units. To enhance operational flexibility and address energy flow conflicts in typical coal-fired systems coupled with compressed air energy storage systems during peak shaving, this study investigates a 660 MW coal-fired unit using EBSILON software. Three energy storage schemes and two energy release schemes are proposed and evaluated through thermo-economic analysis, focusing on thermal-time decoupling capability, peak-shaving paradox elimination, and system performance. The results show that during energy storage, the scheme utilizing intermediate-pressure cylinder exhaust for thermal oil heating achieves the highest thermal storage gain ratio (1.370) and the lowest heat rate (8 814.976 kJ/(kW·h)). During energy release, the scheme absorbing heat from No.3 high-pressure heater drain outlet yields the minimum heat rate (7 547.945 kJ/(kW·h)). After 8 hours of operation, the system retains 38.503 MW·h of utilizable thermal energy and reduces the peak-shaving paradox index to –0.041. Parameter optimization improves the round-trip efficiency of the compressed air energy storage system by 2.702 percentage points and increases the unit’s peak-shaving depth by 2.481%. This study provides a viable solution for synergistic optimization of coal-fired units and energy storage systems.

compressed air energy storage system  /  coal-fired unit  /  coupling system  /  thermal decoupling  /  dееp pеak shaving  /  peak shaving paradox  /  round-trip efficiency
徐传坤, 张杰, 马行驰, 李磊. 660 MW燃煤机组与AA-CAES耦合系统热解耦及调峰研究. 热力发电, 2026 , 55 (2) : 95 -107 . DOI: 10.19666/j.rlfd.202506132
Chuankun XU, Jie ZHANG, Xingchi MA, Lei LI. Thermodynamic decoupling and peak-shaving research on a 660 MW coal-fired unit coupled with AA-CAES system[J]. Thermal Power Generation, 2026 , 55 (2) : 95 -107 . DOI: 10.19666/j.rlfd.202506132
为落实“双碳”战略目标,我国正加快推进可再生能源技术发展,并连续出台了多项配套支持政策[1-2]根据国家能源局统计数据[3],截至2024年12月底,全国累计发电装机容量约33.5亿千瓦,同比增长14.6%,其中太阳能(发电装机容量约8.9亿千瓦,同比增长45.2%)与风电(发电装机容量约5.2亿千瓦,同比增长18.0%)装机增速尤为显著。然而,可再生能源发电的不可预测性[4]与不连续性[5]特征导致其并网发电量存在显著不确定性,给电网负荷调节带来严峻挑战。在此背景下,对电力系统的灵活调节要求进一步提高,而燃煤机组因其良好的可控性,仍然承担着深度调峰的重要责任。因此,提高燃煤机组消纳新能源[6-8]的能力就必须提高燃煤机组的调峰能力和灵活性[9-11]
为协同解决燃煤机组调峰能力与可再生能源消纳问题,大规模储能技术已成为协同提升燃煤机组调峰能力与可再生能源消纳效率的关键路径。基于原理差异,可将储能技术分为3类[12-13]:1)物理储能,如压缩空气储能、抽水蓄能、飞轮储能等;2)电化学储能,如锂离子电池、氢燃料电池、钠硫电池等;3)电磁储能,如超级电容储能、超导电磁储能等[14]。压缩空气储能(compressed air energy storage,CAES)系统因结构简单、容量大、寿命长等优势,已成为最具商业化潜力的大规模储能方案之一。其中,先进绝热压缩空气储能(advanced adiabatic compressed air energy storage,AA-CAES)系统是一种取消常规CAES技术燃料补燃环节的清洁能源储能技术[15]
在新型电力系统结构中,AA-CAES系统通过“削峰填谷”机制增强电网稳定性:高峰时段储电(电能→空气势能),低谷时段发电(空气势能→电能)。相较于电化学等储能技术,AA-CAES具有储能周期长、循环寿命高、清洁环保和电-电效率高等优点。目前,我国电力系统整体缺乏优质的灵活性电源,因此提高电力系统灵活性一方面需要大力发展储能产业,另一方面需要提升燃煤机组的调节能力[16],充分挖掘煤电灵活性。在此背景下,AA-CAES与燃煤机组耦合成为突破性技术路径,既能通过热能梯级利用提高AA-CAES系统往返效率,又可扩展燃煤机组负荷调节范围,为可再生能源消纳创造更大空间。
现有研究采用去除典型CAES系统的蓄热/冷罐的技术方案,实现AA-CAES系统与燃煤机组的直接热耦合,以此为基础围绕耦合方案、热源整合及热电联产三大方向展开。赫广迅等[17]研究了AA-CAES与燃煤机组的耦合系统,对比了汽驱与电驱压缩机的经济性,并分析了蒸汽和烟气2种热源对系统效率与调峰能力的影响,结果表明,烟气热源使系统效率降低0.67%,调峰性能仅提升2.17%。李斌等[18]将10 MW CAES系统与燃煤机组耦合,提出了4种储能和7种释能方案,并基于热耗率与热效率选取了最佳耦合方式,为CAES-燃煤机组协同运行提供了新思路。王晓露等[19]提出抽凝式热电联产机组与CAES的集成系统,分析了供电、供热及独立发电3种运行模式,热力学分析表明,耦合系统的㶲效率可提升4%~31.4%,热电比调节范围显著扩大,此外,既有研究在建模方法上呈现显著差异。李哲等[2]采用EBSILON软件建立了燃煤机组-CAES耦合系统,优化了储能阶段压缩热利用和释能阶段抽汽加热,使机组热效率提高了19.18%,热耗率降低了969 kJ/(kW·h),显著提升了火电调峰能力。高墉[20]采用EBSILON软件建立了CAES-燃煤机组耦合模型,结合改进粒子群优化算法,系统度电成本降低了10.75%,泛㶲效率提升了6.59%。罗天赐[21]采用Aspen Plus建立了燃煤机组-CAES耦合模型,结果表明,系统热效率提升但经济性降低,且机组负荷率越低,热耗率越高。
尽管已有成果显著,但是仍存在一定矛盾性。首先是调峰方向与热量流动的固有矛盾(以下简称调峰悖论):Gong等人[22]的模拟研究表明,当尝试通过70 MW压缩机将燃煤机组负荷从30%THA(210 MW)调降至140 MW时,由于压缩热回流,机组出力反而增加,最终需要配置81 MW压缩机才能实现预期调峰目标,这一现象凸显了热量流动方向与调峰需求之间的本质冲突。其次是热能时间耦合约束,薛小军等[23]对CAES与燃煤机组耦合系统进行了能量分析,发现CAES系统与燃煤机组进行实时热量交换,但缺乏热能管理机制。
综上所述,现有耦合技术虽在调峰性能与系统效率上相较于独立系统有所提升,但仍存在2个关键科学问题:
1)调峰悖论。当耦合系统向下调峰时,压缩机消耗燃煤机组的电能产生压缩热回到燃煤机组,使燃煤机组出力增加,这与向下调峰产生悖论;当耦合系统需要向上顶峰时,CAES系统通过吸收燃煤机组蒸汽的热量提高膨胀机入口温度实现做功,导致燃煤机组出力下降,这与向上顶峰产生悖论。
2)热能时间耦合约束。耦合系统在储能阶段,压缩机产生的压缩热必须实时回馈至燃煤机组热力系统;在释能阶段,膨胀机又需从燃煤机组即时抽取热能用于空气加热。现有耦合系统设计缺乏有效的时间解耦能力,制约了整体运行效率的提升。
针对上述问题,本文创新性地采用“蓄冷/热罐保留式”间接耦合架构,将20 MW AA-CAES系统与660 MW超超临界燃煤机组耦合。该设计通过重构热量流路径,解决调峰方向与能量流动的固有矛盾与热能时间耦合约束问题。基于热耗率、热效率和储热增益比等多维度评价体系,系统对比分析了不同耦合方案的综合性能,深入研究了耦合系统的热能–时间解耦特性及其对调峰矛盾的抑制效果。通过关键运行参数的敏感性分析,揭示了空气质量流量及压缩机/膨胀机入口温度对耦合系统性能、调峰能力的影响规律。
本文采用的20 MW四级压缩三级膨胀AA-CAES系统主要由压缩机、储气罐、蓄热/蓄冷罐等核心部件组成。为分析该系统热力学特性,首先需对其关键部件进行建模[24-30]
压缩机等熵效率ηAc[31]
ηAc=hout,shinhouthin
式中:hin为压缩机入口空气焓值,kJ/kg;hout,s为实际压缩机出口空气焓值,kJ/kg;hout为等熵压缩出口空气焓值,kJ/kg。
压缩机和膨胀机入口空气温度与出口空气温度为[32]
Tci=Tci(βci)k1k
Tei=Tei[1ηei(1(1βei)k1k)]
式中:T'ci为下一级压缩机出口温度,K;T'ei为下一级膨胀机出口温度,K;TciTei分别为上一级压缩机和膨胀机的入口温度,K;βci为上一级压缩机压缩比;βei为上一级膨胀机膨胀比;ηei为膨胀机的等熵效率;k为空气的绝热指数,取1.4。
AA-CAES系统运行包含2个典型工况:储能阶段与释能阶段。在储能阶段,压缩机消耗电网电能将大气中的空气压缩至高压状态并送入储气罐。由于压缩过程会产生大量压缩热,为提升能量利用效率,系统在压缩机出口设置级间换热器,并以Therminol VP1(密度1 050 kg/m3,比热容25 kJ/(kg·K),沸点315 ℃)作为传热介质将压缩热存储于蓄热罐中。该合成导热油具有显著的热稳定性(工作温度范围12~400 ℃)和优异的传热特性,可确保系统在宽工况范围内的热力学性能。在释能阶段,蓄热罐存储的高温导热油通过换热器对高压空气进行再加热,生成的高温高压空气驱动膨胀机做功发电,完成电能回馈电网的转换过程。本研究基于文献[1821-2224-25]设置AA-CAES系统参数(见表1)。基于设计工况参数,建立AA-CAES系统模型,并验证模型的有效性,模拟结果表明:关键参数(包括压缩/膨胀机额定功率和往返效率等)的相对误差均控制在±2%以内,满足工程应用精度要求。
以660 MW超超临界、一次再热、纯凝式燃煤机组为耦合对象,该燃煤机组热力系统采用8级回热抽汽设计,包括4台高压加热器、1台除氧器和3台低压加热器。基于燃煤机组设计工况参数,利用EBSILON热力系统仿真软件分别建立了汽轮机热耗率验收(turbine heat acceptance,THA)工况与30%THA工况下的精确模型。为验证模型准确性,对关键参数包括压缩/膨胀机额定功率和往返效率等进行了模拟值与设计值对比,结果见表2表3。由表2表3可以看出,在THA和30%THA 2种典型运行条件下,各主要热力参数的模拟误差均控制在±2%以内:THA工况下主蒸汽流量模拟误差仅为+1.029%,30%THA工况下主蒸汽流量误差仅为+0.632%。以上验证满足工程计算精度要求。
图1为典型CAES-燃煤机组耦合系统架构[28],其通过取消蓄热/冷罐实现直接耦合,但如前所述,存在调峰悖论和热能时序约束。
本文提出的燃煤机组与AA-CAES耦合系统(图2)旨在提升燃煤机组灵活运行的可行性。耦合系统通过热-电调控机制,实现了“削峰填谷”和灵活性提升。该系统有2种运行模式:储能模式与释能模式。针对现有耦合系统存在的热能–时间耦合与调峰悖论,本研究创新性地引入AA-CAES蓄热罐作为热能缓冲媒介:在可再生能源发电量高峰期时,将部分来自燃煤机组的热能和压缩热存储于蓄热罐中,进一步降低燃煤机组出力;当燃煤机组顶峰时,释放蓄热罐的热能提升燃煤机组发电效率。耦合系统具体原理为:储能模式下,利用电网富余的可再生能源发电驱动压缩机,将空气压入储气罐,在此过程中,导热油同步吸收压缩热,并通过两级换热器进一步储存来自燃煤机组给水系统和蒸汽的热量(简称燃煤机组蓄热)于蓄热罐中,进一步降低燃煤机组出力;释能模式下,高温导热油经过两级换热器将部分热能回送至燃煤机组的给水与凝结水系统以提升燃煤机组发电效率,剩余热能用于加热高压空气推动膨胀机做功发电。值得注意的是,根据热力学第二定律,所储存的热能在释能阶段无法完全利用,使得导热油温度仍高于蓄冷罐温度,耦合系统通过换热器将这部分余热再次回收至燃煤机组,实现能量梯级利用。如图2所示,该集成系统通过热力优化设计,同步实现热能时间解耦、调峰悖论消除及燃煤机组灵活性提升,为新型电力系统建设提供关键技术支撑。
汽轮机热耗率q0是指汽轮机每发1 kW·h电所消耗的热量,表达如下:
q0=Dfw(h0hfw)+DrhΔhrhPe
式中:Dfw为给水质量流量,kg/s;h0为主蒸汽焓值,kJ/kg;hfw为给水焓值,kJ/kg;Drh为再热蒸汽质量流量,kg/s;Δhrh为再热蒸汽热段与冷段的焓差,kJ/kg;Pe为CAES系统向燃煤机组吸收或释放热能而造成的燃煤机组实际出力,MW。
标准煤耗率bn是燃煤机组每发1 kW·h电所消耗的标准燃煤量,表达式如下:
bn=B0W
式中:B0为供电标准煤耗量,g;W为燃煤机组实际供电量,kW·h。
储热增益比H定义为系统储存的有效热量(燃煤机组蓄热和压缩热)与抽汽导致的发电损失之比,用于评价抽汽储热策略的能量置换效率,表达式如下:
H=QstΔPe
式中:H为储热增益比;Qst为有效储热量,MW;ΔPe为燃煤机组发电损失,MW。
向下瞬时调峰容量ΔPcha是储能阶段原始机组输出电功率与耦合系统输出电功率之差,表达式为:
ΔPcha=PCFPPPcha,e
式中:Pcha,e为耦合系统中燃煤机组在储能阶段的实际输出功率,MW;PCFPP为原始机组的输出功率,MW。
调峰深度φcha是耦合系统在储能阶段瞬时调峰容量与原始机组额定功率的比值,表达式如下:
φcha=ΔPchaP0
式中:φcha为向下调峰深度;ΔPcha为向下调峰瞬时调峰容量,%;P0为燃煤机组额定电功率,%。
CAES系统往返效率ηCAES,RTE指在一个充放电周期内压缩空气储能系统的电-电转换效率:
ηCAES,RTE=WA,out+ΔWextrWA,in
式中:WA,out为独立CAES系统在设计工况下的输出电量,MW·h;ΔWextr为释能阶段额外热能增加的膨胀机的发电量,MW·h;WA,in为储能阶段压缩机所消耗的电量,MW·h。
综合能源利用率ηCER用于评价系统整体能源利用率,包含电能和热能的协同效应。其分子是一个循环最后得到的收益,分母是储能阶段的成本:
ηCER=Wexp+ΔWCFPPWcom+ΔWCFPP
式中:Wexp为CAES系统膨胀机发电量,MW·h;ΔWCFPP为返回燃煤机组的热量所增加的发电量,MW·h;ΔWCFP为因抽取蒸汽储热导致的燃煤机组发电量亏损,MW·h;Wcom为CAES系统压缩机耗电量,MW·h。
热效率ηe表示燃煤机组产生的总电能与吸收的总热能的比值,用于评价燃煤机组的效益:
ηe=PCFPPQfw+Qrh
式中:Qfw为给水吸热量,MW;Qrh为再热蒸汽吸热量,MW。
汽轮机热耗率相对变化率q˙0是热耗率相对变化的幅度,用于量化燃煤机组与CAES耦合后其热力学性能的变化程度,表达式如下:
q˙0=q0(T+10)q0(T)q0(T)
式中:q0(T是膨胀机入口空气温度为T时的汽轮机热耗率,kJ/(kW·h);q0(T+10 ℃)为膨胀机入口空气温度在T(℃)基础上增加10 ℃的汽轮机热耗,kJ/(kW·h)。
时间解耦系数ηTD是用于量化热能供需在时间维度上解耦程度的指标,反映系统将热能与时间分离的能力(ηTD=1,完全解耦;0<ηTD<1,部分解耦;ηTD=0,未解耦)。表达式如下:
ηTD=1QactQtotal
式中:Qact为实时消耗的热量,MJ;Qtotal为实时进入CAES系统的总热量(压缩热与燃煤机组蓄热之和),MJ。
调峰悖论指数N是用于量化燃煤机组与CAES耦合系统中调峰方向与实际热量流动矛盾程度的指标。N>0,有调峰矛盾;N≤0,无调峰矛盾。
N=PePCFPPPCFPP
为匹配实际电网运行需求,本文耦合系统设定燃煤机组在30%THA工况下运行。压缩过程产生的压缩热由导热油吸收,为进一步降低燃煤机组出力和实现热能与时间解耦,导热油进一步吸收燃煤机组蓄热,并将热能储存在蓄热罐中,所储存的热能可在释能阶段按需释放,从而实现热能的时间平移和灵活调度。由于蒸汽参数的变化会显著影响燃煤机组的热力学性能及出力特征,本小节重点探讨不同抽汽位置对燃煤机组-CAES耦合系统运行特性的影响。
导热油在吸收压缩热后温度升至179 ℃,而目标储热温度需达到260 ℃。由于热力学限制,热源温度必须高于260 ℃才能实现有效传热,这将导致单级换热器的端温差过大,显著降低换热效率。为此,采用两级梯级换热方案以优化传热过程并降低不可逆损失:第1级换热器将导热油加热至220 ℃,热源来自给水段末级高压加热器出口给水,回水至2号高压加热器(高加)出口;第2级换热器将导热油加热至260 ℃,热源来自3种不同的抽蒸汽方案,分别为再热冷段蒸汽、除氧器抽汽和中压缸排汽,所有方案的回汽均接入低压缸。以上回蒸汽/水位置是根据能量梯级利用原理确定,确保回流温度与回点位置的温度差在±5℃以内[18]。储能阶段各个耦合方案示意如图3所示。
表4对比了储能阶段3种耦合方案的模拟结果。分析发现,抽汽点位置的选择直接影响燃煤机组汽轮机热耗率和标准煤耗率,其中方案3综合性能最优。
方案1的蒸汽来自再热冷段(1.760 MPa、353.016 ℃),经过换热器加热导热油,此时高压蒸汽(1.759 MPa、228 ℃)经过节流阀压力降至与低压缸入口压力相同,被送入低压缸(0.123 MPa、229.964 ℃)做功。这使得一部分再热冷段蒸汽未能进入再热器提高蒸汽焓值并进入中压缸做功,导致汽轮机机组热耗率和标准煤耗率最高,该方案虽储存了高品位热能,但发电损失显著,其储热增益比为三者中最低。
方案2抽取除氧器抽汽(0.419 MPa、377 ℃,品位相对方案3较高),经过换热器后蒸汽(0.418 MPa、231 ℃)经节流阀被送入低压缸,一部分蒸汽未能进入中压缸使得汽轮机机组热耗率和标准煤耗率较高。
方案3抽取中压缸排汽(0.193 MPa、272.183 ℃,品位相对较低),经过换热器后蒸汽(0.192 MPa、228.709 ℃)经节流阀进入低压缸。因为该方案中压缸排汽与低压缸入口处焓差和压差较小,所以汽轮机做功循环的影响较小,因此热耗率、标准煤耗率及储热增益比均优于其他方案。
释能阶段通常对应可再生能源发电低谷期,因此本研究基于燃煤机组100%THA工况模拟运行。在释能阶段,高压空气从储气罐经过换热器提升温度至174 ℃后进入膨胀机做功;导热油经过换热器从260 ℃下降为179 ℃。为避免单一换热器端温差过小导致换热面积增加(成本上升)或过大影响换热效率,耦合系统采用两级换热设计,端温差控制在±10~40 ℃内。第1级换热器冷源分别选取给水泵出口和3号高加疏水器出口作为释能阶段2种耦合方案比较,且回水点均为2号高加疏水器入口;第2级换热器冷源来自6号低压加热器(低加)疏水器出口,回水至除氧器入口。导热油释热后温度降至55 ℃,仍高于蓄冷罐内导热油温度(30 ℃),为避免热量浪费,在蓄冷罐入口前设置换热器,通过抽取凝结水泵出口凝结水吸收导热油热量,回水至8号低加疏水器出口,将这部分热量送给燃煤机组加以利用。其中回水点的确定依据2.1节提到的能量梯级利用原理。
释能阶段各耦合方案如图4所示。各方案模拟结果对比见表5
表5可知,释能阶段将导热油的热量回收至燃煤机组可以降低汽轮机组热耗率和标准煤耗率。方案1和方案2抽水温度分别为198.794、193.041 ℃,且回水温度均为234 ℃。在导热油放热量相同的情况下,2种方案抽水温度和抽水量相近,使得汽轮机组热耗率、热效率和标准煤耗率相差不大。由于2种方案抽水使除氧器抽汽量有所变化,方案1除氧器抽汽量比方案2小,进入汽轮机做功的蒸汽量更多,使得汽轮机组热耗率比方案2低,热效率较高,因此方案1作为释能阶段最佳耦合方案。
基于对储能阶段与释能阶段耦合方案的对比分析,最终确定的最佳耦合系统方案如图5所示。在储能阶段,导热油在第1级换热器吸收来自1号高加出口释放的热能,回水至3号高加出口;在第2级换热器导热油进一步吸收来自中压缸排汽释放的蒸汽热能,回至低压缸入口。在释能阶段,高温导热油在第1级换热器释放的热量由4号高加疏水器出口的给水吸收,回水至3号高加疏水器出口;在第2级换热器释放的热量由6号低加疏水器出口的凝结水吸收,回水至除氧器入口。为评估耦合系统热力性能,在热平衡状态下对原始机组与耦合系统进行了关键指标对比,包括标准煤耗率、热效率、储热增益比及汽轮机组热耗率,具体数据见表6
针对耦合系统的热能时间平移特性及释能阶段关键参数影响开展深入分析,基于以下假设建立研究框架:
1)耦合系统热力损失方面,综合考虑管道传热与设备散热,设定总热损失率恒定不变;
2)压缩与膨胀过程方面,维持压缩机与膨胀机等熵效率恒定;
3)储气系统方面,假设储气罐内空气压力与总质量在释能阶段保持动态平衡;
4)在分析释能阶段参数敏感性时,固定储能阶段的初始运行条件。
由于文献[18]中的CAES系统容量(10 MW)和燃煤机组规模(350 MW)与本文(20 MW CAES+660 MW燃煤机组)显著不同,为确保研究结果具有可比性,本文采用以下统一边界条件:保持总膨胀比一致,修正膨胀机等熵效率,并通过调整空气质量流量实现输出功率等效。同时,将热耗率转化为相对变化率以消除基准差异。图6展示了本文耦合系统与文献[18]系统在100%THA工况(非采暖季)下释能阶段汽轮机热耗率的相对变化率对比。由图6可以看出,随着膨胀机入口空气温度的升高,文献[18]系统与本文耦合系统的热耗率变化趋势均较为平缓,但本文耦合系统的热耗率相对变化率整体更低。这是因为:首先,文献[18]系统采用直接耦合方式,而本文系统采用间接耦合;其次,在释能阶段,文献[18]系统利用5号低加抽汽加热高压空气,而本文系统则采用蓄热罐加热高压空气的方式。这种改进方式使本文耦合系统对燃煤机组热耗率的影响更温和。
为突显本耦合系统的热能解耦能力,本文将其与文献[18]所提系统在储能与释能阶段的热耗率及时间解耦特性进行对比。具体对比如下:
在储能阶段,以各自对应的独立燃煤机组为基准进行对比。文献[18]中,原始机组的热耗率为7 865.104 kJ/(kW·h),其耦合系统的模拟值为7 788.395 kJ/(kW·h);本文原始机组的热耗率为8 512.541 kJ/(kW·h),耦合系统的热耗率为8 814.976 kJ/(kW·h)。在时间解耦系数方面,原始机组因未参与耦合,不适用ηTD;文献[18]系统ηTD=0,而本文系统ηTD=1,表明其具备完全的时间解耦能力。由于热能与时间的解耦仅发生于储能阶段,释能阶段的分析仅以原始机组为参照进行热耗率对比。文献[18]原始机组热耗率为7 865.102 kJ/(kW·h),其系统模拟值为7 875.612 kJ/(kW·h);本文原始机组热耗率为7 600.432 kJ/(kW·h),耦合系统热耗率为7 547.945 kJ/(kW·h)。对比结果表明,两种系统在储能阶段的运行特性存在本质差异:文献[18]系统ηTD=0,反映其完全的时间依赖性;而本文系统ηTD=1,实现了完全时间解耦。该差异源于两者不同的热能管理机制:文献[18]系统通过将压缩热回流至燃煤机组以降低热耗率;本文系统则采用导热油吸收机组蓄热,造成热耗率上升。在释能阶段,文献[18]系统因需实时消耗燃煤机组热能加热高压空气,其热耗率高于原始机组;而本文系统通过调用储能阶段所储存的热能,有效降低了释能过程的热耗率。
本文耦合系统通过将热能储存于蓄热罐实现热能的时间平移。为研究热能的时间平移特性,参考文献[27]中典型火电机组周期负荷曲线,对蓄热罐进行8 h的储热模拟。结果如图7图8所示。在8 h内,罐体温度从260 ℃平稳降至241 ℃,储热总量从50.830 MW·h降至47.012 MW·h,热储存率为92.539%。耦合系统在整个储存时间内有效利用热能(热能经过一段时间平移后,CAES系统实际使用的热能与回流到燃煤机组的热能之和)仍有38.503 MW·h,占初始储热量的75.749%。
图9显示了固定空气流量时,膨胀机入口温度对汽轮机热耗率和CAES系统输出功率的影响。可以看出,汽轮机热耗率与膨胀机入口温度呈非线性关系,具体表现为:当膨胀机入口温度低于设计温度(<174 ℃)时,多余的压缩热随着入口空气温度提升进入燃煤机组的压缩热逐渐减少,温度每提升10 ℃,进入燃煤机组的压缩热减少约1%,导致热耗率相应增加0.511 kJ/(kW·h);当膨胀机入口温度高于设计温度(≥174 ℃)时,膨胀机需额外消耗燃煤机组蓄热(约2.982 MJ/s),引发除氧器抽汽量突增1 kg/s,导致热耗率突增。同时,CAES系统输出功率随入口温度升高而增加,这是由于高温空气焓值提升增强了膨胀机做功能力。
图10展示了入口空气温度对CAES系统往返效率与综合能源利用率的影响。由图10可以看出,在恒定储能工况条件下,随着入口温度升高,CAES系统往返效率与综合能源利用率呈线性增长趋势。系统往返效率变化规律可由式(9)解释,增大释能阶段膨胀机做功可以提高系统往返效率,在入口温度为194 ℃时可将系统往返效率提升至62.192%,较独立运行工况CAES系统提高2.702百分点。对综合能源利用率分析表明:在入口温度低于膨胀机设计入口温度(174 ℃)时,部分压缩热和燃煤机组蓄热返回燃煤机组,导致膨胀机出力降低;当入口温度高于174 ℃时,部分燃煤机组蓄热和压缩热进入膨胀机,使得膨胀机做功增加(相较于174 ℃)。直接促成了综合能源利用率随温度升高而持续提升的整体趋势。
图11展示了膨胀机空气质量流量对汽轮机热耗率与输出功率的影响。由图11可以看出,膨胀机空气质量流量对汽轮机热耗率与输出功率的影响规律相反。提升空气质量流量可显著改善汽轮机组热效率。在恒定入口温度工况下,增加空气质量流量需要更大的热量输入以维持设定温度。这一过程导致导热油温度上升,为保持系统预设的传热温差,需相应提高导热油质量流量。通过这种协同调节机制,燃煤机组单位时间内吸收的热量增加,从而有效降低单位发电量的热耗率。同时,膨胀机功率输出呈现对空气质量流量的高度敏感性:在固定运行工况下,提升进气流量将直接增加膨胀工质的质量流量,从而强化单位时间内的可用能转换能力,最终实现轴功率的线性增长。
图12展示了膨胀机空气质量流量对CAES系统往返效率的影响。由图12可以看出,膨胀机空气质量流量对CAES系统往返效率的影响有限,但会导致综合能源利用率出现负增长趋势。这一现象可以从热力学角度解释:对于CAES系统往返效率,由于储气室内的空气质量保持恒定,增大空气质量流量虽能提高瞬时输出功率,但会缩短耦合系统释能时间,导致总做功量基本保持不变。在综合能源利用率方面,虽然空气质量流量增加能提高单位时间内燃煤机组吸热量,但释能时间会相应缩短,使得整个释能时间内燃煤机组的总吸热量反而降低。这直接导致燃煤机组增加发电量减少。加之CAES系统往返效率基本不变,最终导致综合能源利用率呈现下降趋势。这一现象说明,单纯提高空气质量流量虽然可以增加瞬时功率输出,但会牺牲系统的整体能源利用效率。
本节研究耦合系统在储能阶段(燃煤机组30%THA低负荷工况)的调峰性能,重点分析其改善调峰矛盾的效果和第2、3和4级压缩机入口参数对调峰能力的提升作用。选取40~50 ℃为入口温度研究区间(依据文献[29]),该范围能保证压缩机稳定运行。
为验证本文耦合系统在解决调峰矛盾方面的优越性,基于调峰悖论指数(N)、原始机组出力以及实际燃煤机组出力等指标分析,将其与文献[22]中的耦合系统进行对比。考虑到文献[22]中燃煤机组(700 MW)与压缩空气储能系统(60 MW)的容量配置与本研究存在差异,统一将燃煤机组基准负荷设定为700 MW的30%THA工况,对压缩机功率进行等效化处理。对比结果见表7。可以看出,在向下调峰时,文献[22]耦合系统因压缩热回流至燃煤机组,导致机组出力增加11 MW,调峰悖论指数(N>0),这一现象与向下调峰的需求相矛盾;本文耦合系统通过优化热管理,避免了压缩热流入燃煤机组,还利用导热油进一步吸收燃煤机组蓄热,最终使燃煤机组实际出力降低8.404 MW,调峰悖论指数降至–0.041。
图13展示了30%THA工况下,压缩机空气质量流量与入口温度对燃煤机组向下调峰容量的影响。可以看出:入口温度恒定时,调峰容量随空气质量流量增加呈线性增长;空气质量流量固定时,调峰容量则随入口空气温度的升高而单调递减。其中,入口温度40 ℃、空气质量流量59.060 kg/s时调峰性能最佳,最大向下调峰容量为16.377 MW。从热力学角度看,恒定空气质量流量下入口温度升高会使压缩机出口温度上升,进而增加导热油的吸热量和温度,使得燃煤机组蓄热减少从而降低了向下调峰容量。相反,入口温度恒定时,增加空气质量流量会增加压缩热,耦合系统需提高导热油质量流量以维持端温差,使燃煤机组蓄热增加,调峰容量提升。
图14展示了30%THA工况下压缩机空气质量流量与入口空气温度对燃煤机组调峰深度的影响。可以看出,压缩机空气质量流量和入口温度对机组调峰深度具有显著影响:在恒定入口温度条件下,调峰深度与空气质量流量呈正相关关系,其变化趋势近似线性;当维持空气质量流量不变时,调峰深度则随入口温度升高呈现单调递减特性。系统在入口温度40 ℃、空气质量流量59.060 kg/s的工况组合下取得最优调峰性能,此时调峰深度提升了2.481%。需要指出的是,调峰深度作为表征机组负荷调节能力的相对指标,其数值由式(8)定义的向下调峰容量直接决定。因此,前文所述的压缩机参数(空气质量流量和入口温度)对调峰容量的影响机制同样适用于解释调峰深度的变化规律。
基于660 MW超超临界燃煤机组与AA-CAES系统,通过增设蓄冷/热罐重构热量流路径,解决了调峰方向与热量流动的固有矛盾,实现了热能与时间的解耦。在此基础上提出3种储能方案和2种释能方案,通过改变关键运行参数,分析其对耦合系统热力性能及调峰能力的影响,得出以下结论:
1)在储能阶段,耦合系统将压缩机产生的压缩热与燃煤机组蓄热协同存储于蓄热罐中,提出了3种差异化的储能方案;在释能阶段,根据不同回水点,设计了2套释热优化方案。基于热经济性评价分析,确定了综合性能最优的耦合系统方案。
2)典型耦合系统的ηTD=0,而本文耦合系统的ηTD=1,表明本文耦合系统实现了热能-时间解耦。该耦合系统在储能阶段的热耗率相对变化率波动小于典型耦合系统,在释能阶段性能优势更显著,热耗率更低,8 h储热后仍有38.503 MW·h有效热能(占初始储热量75.749%)。参数影响方面:入口温度194 ℃时,CAES系统往返效率提升2.702百分点,至62.192%。提升入口温度虽会增加汽轮机热耗率,但能提高综合能源利用率,优化整体性能;增加膨胀机空气质量流量可短暂提高瞬时输出功率,但会降低汽轮机热耗率和综合能源利用率,对CAES系统往返效率的影响较小。
3)在储能阶段,与典型耦合系统相比,本文耦合系统不仅能够将燃煤机组出力额外降低8.404 MW,还成功解决了调峰悖论问题(N= –0.041)。参数影响研究表明:入口温度为40 ℃、空气质量流量为59.060 kg/s时调峰深度(2.481%)与向下调峰容量(16.377 MW)达到最大值。
  • 中国电力工程顾问集团重大科技专项(DG-J02-2022)
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doi: 10.19666/j.rlfd.202506132
  • 接收时间:2025-06-30
  • 首发时间:2026-08-14
  • 出版时间:2026-02-25
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  • 收稿日期:2025-06-30
  • 修回日期:2025-08-31
  • 录用日期:2025-09-04
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Key Science and Technology Program of China Power Engineering Consulting Group(DG-J02-2022)
中国电力工程顾问集团重大科技专项(DG-J02-2022)
作者信息
    1.上海电力大学能源与机械工程学院,上海 200090
    2.中国电力工程顾问集团华东电力设计院有限公司,上海 200063

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张杰(1980),男,硕士,高级工程师,主要研究方向为压缩空气储能系统优化,
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