Article(id=1295064748207395145, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1295064706872528996, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202504057, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1744646400000, receivedDateStr=2025-04-15, revisedDate=1746460800000, revisedDateStr=2025-05-06, acceptedDate=1746633600000, acceptedDateStr=2025-05-08, onlineDate=1786697097112, onlineDateStr=2026-08-14, pubDate=1771948800000, pubDateStr=2026-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1786697097112, onlineIssueDateStr=2026-08-14, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1786697097112, creator=13701087609, updateTime=1786697097112, 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=23, endPage=31, ext={EN=ArticleExt(id=1295064748383555914, articleId=1295064748207395145, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Thermodynamic performance analysis and optimization of a novel Carnot battery system based on coal-fired power unit, columnId=1295064707514257509, journalTitle=Thermal Power Generation, columnName=Energy storage materials, devices, and systems, runingTitle=null, highlight=null, articleAbstract=

A Carnot battery system based on coal-fired power units can efficiently absorb curtailed power of new energy while utilizing the existing infrastructure of coal-fired plants for energy release, thereby addressing the challenges posed by high-penetration renewable energy on the power supply-side flexibility. A novel supercritical carbon dioxide reverse Brayton-Rankine cycle Carnot battery system is proposed based on the concept of split-flow expansion, and a comprehensive investigation is conducted through thermodynamic modeling in EBSILON Professional, parameter sensitivity analysis, and multi-objective optimization using genetic algorithms. The results indicate that under design conditions, the turbine power output and waste heat recovery of the novel system are improved by 59.84% and 43.23%, respectively, compared to the reference system. The energy storage cycle achieves a coefficient of performance (COP) of 1.32 and a round-trip efficiency (RTE) of 57.68%, representing an increase of 0.10 in COP and 4.37 percentage points in RTE over the reference system. Both COP and RTE increase with higher pressure ratios, higher flow split ratios, and lower top-end temperature differences in recuperator 2. When the flow split ratio is 0.23, the pressure ratio is 3.09, and the top-end temperature difference in recuperator 2 is 12.60 ℃, the COP of the Carnot battery storage cycle reaches a maximum of 1.37, with a corresponding RTE of 59.87%. The study provides a technical reference for enhancing the operational flexibility of coal-fired power plants and optimizing renewable energy integration through advanced thermal storage technologies.

, authors=Ling LI1, Dawei XIA1, Buting ZHANG1, Changshuang ZHI1, Shifei ZHAO2, authorsList=Ling LI, Dawei XIA, Buting ZHANG, Changshuang ZHI, Shifei ZHAO, authorCompany=null, correspAuthors=Shifei ZHAO, 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=1295064751705444699, articleId=1295064748207395145, tenantId=1146029695717560320, journalId=1210938733613449225, language=CN, title=基于燃煤机组的新型卡诺电池系统热力学性能分析与优化, columnId=1295064707795275879, journalTitle=热力发电, columnName=储能材料、装置及系统, runingTitle=null, highlight=null, articleAbstract=

基于燃煤发电机组的卡诺电池系统可在高效接纳新能源弃电的同时,利用现役燃煤机组的设备完成释能过程,以应对高比例可再生能源接入对电力供应侧调节能力的挑战。基于分流膨胀的思想提出了一种新型“超临界二氧化碳逆布雷顿-朗肯循环”卡诺电池系统,并借助EBSILON Professional平台对系统进行建模,分析其热力学性能和关键参数敏感性,最后通过遗传算法获得了系统的最优设计参数。结果表明:在设计工况下,新型系统储能循环的透平做功量和余热回收量较原系统分别提高了59.84%和43.23%;储能过程能效系数(COP)和储能往返效率(RTE)分别为1.32和57.68%,较参考系统提高了0.10和4.37百分点;随着压比和分流比的升高和回热器2上端差的降低,新型系统的COP和RTE均提高;当分流比为0.23、压比为3.09、回热器2上端差为12.60 ℃时,卡诺电池储能循环的COP最高为1.37,此时卡诺电池RTE为59.87%。研究结果可为燃煤机组提高灵活性和可再生能源的高效接纳提供技术参考。

, authors=李玲1, 夏大伟1, 张步庭1, 支长双1, 赵世飞2, authorsList=李玲, 夏大伟, 张步庭, 支长双, 赵世飞, authorCompany=null, correspAuthors=赵世飞, authorNote=

李玲(1975),女,硕士研究生,高级工程师,主要研究方向为网源协调、供热机组调峰等相关技术,

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赵世飞(1991),男,博士,副教授,主要研究方向为燃煤热电联产机组高效灵活运行技术,
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李玲(1975),女,硕士研究生,高级工程师,主要研究方向为网源协调、供热机组调峰等相关技术,

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李玲(1975),女,硕士研究生,高级工程师,主要研究方向为网源协调、供热机组调峰等相关技术,

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Renewable and Sustainable Energy Reviews, 2023, 175: 113134., articleTitle=Thermodynamic evaluation of a pumped thermal electricity storage system integrated with large-scale thermal power plants, refAbstract=null), Reference(id=1295064771867464145, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, doi=null, pmid=null, pmcid=null, year=2025, volume=14, issue=4, pageStart=1461, pageEnd=1470, url=null, language=null, rfNumber=[26], rfOrder=38, authorNames=于博旭, 韩瑞, 刘倩, journalName=储能科学与技术, refType=null, unstructuredReference=于博旭,韩瑞,刘倩,. 耦合火电厂灵活改造的卡诺电池储能系统热力学性能研究[J]. 储能科学与技术202514(4):1461-1470., articleTitle=耦合火电厂灵活改造的卡诺电池储能系统热力学性能研究, refAbstract=null), Reference(id=1295064771997487571, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, doi=null, pmid=null, pmcid=null, year=2025, volume=14, issue=4, pageStart=1461, pageEnd=1470, url=null, language=null, rfNumber=[26], rfOrder=39, authorNames=YU Boxu, HAN Rui, LIU Qian, journalName=Energy Storage Science and Technology, refType=null, unstructuredReference=YU Boxu, HAN Rui, LIU Qian, et al. 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figureFileBig=MIcDx7xfavqqzUZQTM9rxg==, tableContent=null), ArticleFig(id=1295064756864438669, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=EN, label=Fig.5, caption=T-s diagram of energy storage cycle in the novel system, figureFileSmall=ZbqtR3RPSgj3J+vNBwtQYw==, figureFileBig=ddRA5/SAq9K95d7yTkSqxw==, tableContent=null), ArticleFig(id=1295064756931547534, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=CN, label=图5, caption=新型系统储能循环T-s, figureFileSmall=ZbqtR3RPSgj3J+vNBwtQYw==, figureFileBig=ddRA5/SAq9K95d7yTkSqxw==, tableContent=null), ArticleFig(id=1295064757028016527, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=EN, label=Fig.6, caption=Effect of pressure ratio β on thermodynamic performance of the two systems, figureFileSmall=2SgdEYw5JoigVl8uP1j5qQ==, figureFileBig=9TWi9PHwLStlfPBtca6lNg==, tableContent=null), 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articleId=1295064748207395145, language=EN, label=Fig.8, caption=Effect of upper terminal difference of recuperator 2 on thermodynamic performance of the novel system with a certain split ratio and pressure ratio, figureFileSmall=ZYw0BHusPkqyhzL/jcLWxw==, figureFileBig=AWSRiGzjacqXW8ZoQd21Aw==, tableContent=null), ArticleFig(id=1295064757413892500, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=CN, label=图8, caption=分流比和压比一定时回热器2上端差对新型系统热力学性能的影响, figureFileSmall=ZYw0BHusPkqyhzL/jcLWxw==, figureFileBig=AWSRiGzjacqXW8ZoQd21Aw==, tableContent=null), ArticleFig(id=1295064757468418453, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=EN, label=Tab.1, caption=

Thermodynamic parameters of the S-CO2 reverse Brayton cycle

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项目数值
冷源加热器出口工质温度/℃32
压缩机入口压力/MPa7.40
压缩机出口压力/MPa20.00
压缩机出口温度/℃570
熔盐加热器出口温度/℃431
透平等熵效率0.90
压缩机等熵效率0.90
), ArticleFig(id=1295064757539721622, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=CN, label=表1, caption=

S-CO2逆布雷顿循环热力学参数

, figureFileSmall=null, figureFileBig=null, tableContent=
项目数值
冷源加热器出口工质温度/℃32
压缩机入口压力/MPa7.40
压缩机出口压力/MPa20.00
压缩机出口温度/℃570
熔盐加热器出口温度/℃431
透平等熵效率0.90
压缩机等熵效率0.90
), ArticleFig(id=1295064757623607703, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=EN, label=Tab.2, caption=

Main thermodynamic parameters of the coal-fired power unit

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项目数值
主蒸汽流量/(t·h–1915.09
主蒸汽压力/MPa16.67
主蒸汽温度/℃537
再热蒸汽流量/(t·h–1756.12
再热蒸汽压力/MPa3.20
再热蒸汽温度/℃537
乏汽流量/(t·h–1541.20
乏汽损失/MW362.13
发电量/MW300.15
背压/kPa5.39
), ArticleFig(id=1295064757703299480, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=CN, label=表2, caption=

燃煤发电机组THA工况主要热力学参数

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项目数值
主蒸汽流量/(t·h–1915.09
主蒸汽压力/MPa16.67
主蒸汽温度/℃537
再热蒸汽流量/(t·h–1756.12
再热蒸汽压力/MPa3.20
再热蒸汽温度/℃537
乏汽流量/(t·h–1541.20
乏汽损失/MW362.13
发电量/MW300.15
背压/kPa5.39
), ArticleFig(id=1295064757778796953, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=EN, label=Tab.3, caption=

Comparison of the simulated and actual values of the steam turbine’s power generation capacity under different operating conditions

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工况主蒸汽流量/(t·h–1实际值/MW模拟值/MW误差/%
THA915.09300.15300.130.01
75%THA666.57226.22226.620.18
50%THA453.83151.77151.230.36
40%THA373.80121.67121.490.15
30%THA290.7091.4391.010.46
), ArticleFig(id=1295064757850100122, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=CN, label=表3, caption=

不同工况下汽轮机发电功率模拟值和实际值对比

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工况主蒸汽流量/(t·h–1实际值/MW模拟值/MW误差/%
THA915.09300.15300.130.01
75%THA666.57226.22226.620.18
50%THA453.83151.77151.230.36
40%THA373.80121.67121.490.15
30%THA290.7091.4391.010.46
), ArticleFig(id=1295064757942374811, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=EN, label=Tab.4, caption=

Validation of the heat pump system models[9]

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项目实际值/MW模拟值/MW误差/%
压比3.783.780
压缩机入口压力/MPa7.507.500
压缩机做功/MW18.2218.210.05
透平耗功/MW4.304.290.23
弃电量/MW13.9113.910
透平入口温度/℃146.85146.360.33
压缩机入口温度/℃435.15435.150
CO2质量流量/(t·h–1287.01287.650.22
), ArticleFig(id=1295064758017872284, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=CN, label=表4, caption=

热泵系统模型验证[9]

, figureFileSmall=null, figureFileBig=null, tableContent=
项目实际值/MW模拟值/MW误差/%
压比3.783.780
压缩机入口压力/MPa7.507.500
压缩机做功/MW18.2218.210.05
透平耗功/MW4.304.290.23
弃电量/MW13.9113.910
透平入口温度/℃146.85146.360.33
压缩机入口温度/℃435.15435.150
CO2质量流量/(t·h–1287.01287.650.22
), ArticleFig(id=1295064758143701405, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=EN, label=Tab.5, caption=

Thermodynamic performance of the energy-storage cycles of the reference system and the novel system

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项目参考系统新型系统差值
工质流量/(t·h–12 566.102 767.89201.79
压缩机耗功/MW115.14124.209.06
回热器2 上端差/℃15
分流比0.20
透平做功/MW15.1424.209.06
透平1 做功/MW12.67
透平2 做功/MW11.53
回热器总回热量/MW370.55358.99–11.56
回热器1 回热量/MW125.18
回热器2 回热量/MW233.81
余热回收量/MW22.2331.849.61
能效系数cCOP1.221.320.10
往返效率ηRTE/%53.3157.684.37
), ArticleFig(id=1295064758223393182, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=CN, label=表5, caption=

参考系统和新型系统储能循环的热力学性能对比

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项目参考系统新型系统差值
工质流量/(t·h–12 566.102 767.89201.79
压缩机耗功/MW115.14124.209.06
回热器2 上端差/℃15
分流比0.20
透平做功/MW15.1424.209.06
透平1 做功/MW12.67
透平2 做功/MW11.53
回热器总回热量/MW370.55358.99–11.56
回热器1 回热量/MW125.18
回热器2 回热量/MW233.81
余热回收量/MW22.2331.849.61
能效系数cCOP1.221.320.10
往返效率ηRTE/%53.3157.684.37
), ArticleFig(id=1295064758286307743, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=EN, label=Tab.6, caption=

Key parameters of the genetic algorithm

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项目数值
种群规模50
交叉概率0.60
突变概率0.50
每代取代的个体0.75
终止代数30
), ArticleFig(id=1295064758374388128, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=CN, label=表6, caption=

遗传算法关键参数

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项目数值
种群规模50
交叉概率0.60
突变概率0.50
每代取代的个体0.75
终止代数30
), ArticleFig(id=1295064758449885601, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=EN, label=Tab.7, caption=

Optimization ranges of key parameters

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项目范围
分流比α0~1
回热器2 上端差D/℃10~50
压比β2~4
), ArticleFig(id=1295064758525383074, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=CN, label=表7, caption=

各关键参数优化范围

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项目范围
分流比α0~1
回热器2 上端差D/℃10~50
压比β2~4
), ArticleFig(id=1295064758609269155, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=EN, label=Tab.8, caption=

Thermodynamic performance of the novel system before and after optimization

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项目优化前优化后差值
压比2.703.090.39
回热器2 上端差/℃15.0012.60–2.40
分流比0.200.230.03
工质流量/(t·h–12 767.892 519.11–248.78
压缩机耗功/MW124.20126.642.44
透平做功/MW24.1926.642.44
透平1 做功/MW12.6615.432.77
透平2 做功/MW11.5311.21–0.32
回热器总回热量/MW358.99365.096.10
回热器1 回热量/MW125.1876.28–48.90
回热器2 回热量/MW233.81288.8054.99
余热回收量/MW31.8436.754.91
能效系数cCOP1.321.370.05
往返效率ηRTE/%57.6859.872.19
), ArticleFig(id=1295064760295379364, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1295064748207395145, language=CN, label=表8, caption=

优化前、后新型系统热力学性能对比

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项目优化前优化后差值
压比2.703.090.39
回热器2 上端差/℃15.0012.60–2.40
分流比0.200.230.03
工质流量/(t·h–12 767.892 519.11–248.78
压缩机耗功/MW124.20126.642.44
透平做功/MW24.1926.642.44
透平1 做功/MW12.6615.432.77
透平2 做功/MW11.5311.21–0.32
回热器总回热量/MW358.99365.096.10
回热器1 回热量/MW125.1876.28–48.90
回热器2 回热量/MW233.81288.8054.99
余热回收量/MW31.8436.754.91
能效系数cCOP1.321.370.05
往返效率ηRTE/%57.6859.872.19
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基于燃煤机组的新型卡诺电池系统热力学性能分析与优化
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李玲 1 , 夏大伟 1 , 张步庭 1 , 支长双 1 , 赵世飞 2
热力发电 | 储能材料、装置及系统 2026,55(2): 23-31
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热力发电 |储能材料、装置及系统 2026 , 55 (2) : 23 -31
基于燃煤机组的新型卡诺电池系统热力学性能分析与优化
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李玲1 , 夏大伟1, 张步庭1, 支长双1, 赵世飞2
作者信息
  • 1.国网河南省电力公司电力科学研究院,河南 郑州 450052
  • 2.华北水利水电大学能源与动力工程学院,河南 郑州 450045
通讯作者:
赵世飞(1991),男,博士,副教授,主要研究方向为燃煤热电联产机组高效灵活运行技术,
作者简介:

李玲(1975),女,硕士研究生,高级工程师,主要研究方向为网源协调、供热机组调峰等相关技术,

Thermodynamic performance analysis and optimization of a novel Carnot battery system based on coal-fired power unit
Ling LI1 , Dawei XIA1, Buting ZHANG1, Changshuang ZHI1, Shifei ZHAO2
Affiliations
  • 1.State Grid Henan Electric Power Company Electric Power Science Research Institute, Zhengzhou 450052, China
  • 2.College of Energy and Power Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
出版时间: 2026-02-25 doi: 10.19666/j.rlfd.202504057
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基于燃煤发电机组的卡诺电池系统可在高效接纳新能源弃电的同时,利用现役燃煤机组的设备完成释能过程,以应对高比例可再生能源接入对电力供应侧调节能力的挑战。基于分流膨胀的思想提出了一种新型“超临界二氧化碳逆布雷顿-朗肯循环”卡诺电池系统,并借助EBSILON Professional平台对系统进行建模,分析其热力学性能和关键参数敏感性,最后通过遗传算法获得了系统的最优设计参数。结果表明:在设计工况下,新型系统储能循环的透平做功量和余热回收量较原系统分别提高了59.84%和43.23%;储能过程能效系数(COP)和储能往返效率(RTE)分别为1.32和57.68%,较参考系统提高了0.10和4.37百分点;随着压比和分流比的升高和回热器2上端差的降低,新型系统的COP和RTE均提高;当分流比为0.23、压比为3.09、回热器2上端差为12.60 ℃时,卡诺电池储能循环的COP最高为1.37,此时卡诺电池RTE为59.87%。研究结果可为燃煤机组提高灵活性和可再生能源的高效接纳提供技术参考。

卡诺电池  /  燃煤机组  /  逆布雷顿循环  /  热力学性能  /  敏感性分析

A Carnot battery system based on coal-fired power units can efficiently absorb curtailed power of new energy while utilizing the existing infrastructure of coal-fired plants for energy release, thereby addressing the challenges posed by high-penetration renewable energy on the power supply-side flexibility. A novel supercritical carbon dioxide reverse Brayton-Rankine cycle Carnot battery system is proposed based on the concept of split-flow expansion, and a comprehensive investigation is conducted through thermodynamic modeling in EBSILON Professional, parameter sensitivity analysis, and multi-objective optimization using genetic algorithms. The results indicate that under design conditions, the turbine power output and waste heat recovery of the novel system are improved by 59.84% and 43.23%, respectively, compared to the reference system. The energy storage cycle achieves a coefficient of performance (COP) of 1.32 and a round-trip efficiency (RTE) of 57.68%, representing an increase of 0.10 in COP and 4.37 percentage points in RTE over the reference system. Both COP and RTE increase with higher pressure ratios, higher flow split ratios, and lower top-end temperature differences in recuperator 2. When the flow split ratio is 0.23, the pressure ratio is 3.09, and the top-end temperature difference in recuperator 2 is 12.60 ℃, the COP of the Carnot battery storage cycle reaches a maximum of 1.37, with a corresponding RTE of 59.87%. The study provides a technical reference for enhancing the operational flexibility of coal-fired power plants and optimizing renewable energy integration through advanced thermal storage technologies.

Carnot battery  /  coal-fired power unit  /  reverse Brayton cycle  /  thermodynamic performance  /  sensitivity analysis
李玲, 夏大伟, 张步庭, 支长双, 赵世飞. 基于燃煤机组的新型卡诺电池系统热力学性能分析与优化. 热力发电, 2026 , 55 (2) : 23 -31 . DOI: 10.19666/j.rlfd.202504057
Ling LI, Dawei XIA, Buting ZHANG, Changshuang ZHI, Shifei ZHAO. Thermodynamic performance analysis and optimization of a novel Carnot battery system based on coal-fired power unit[J]. Thermal Power Generation, 2026 , 55 (2) : 23 -31 . DOI: 10.19666/j.rlfd.202504057
随着“双碳”目标的推进,能源系统加速向清洁低碳转型,可再生能源与燃煤机组均面临严峻挑战[1]。风电、光伏等可再生能源出力具有强波动性和随机性,导致电网消纳能力不足,弃风弃光现象频发。据统计,我国弃风弃电量长期维持在4%以上,亟需新型储能技术平抑波动、提升灵活调节能力[2]。燃煤机组作为传统调峰主力,其调节速率与深度难以匹配新能源高渗透率电网的需求。现有煤电机组调峰能力普遍较低,频繁启停或低负荷运行不仅效率骤降,还加剧设备损耗与碳排放。在此背景下,卡诺电池储能技术为破解困境提供了创新路径[3]。其核心通过电热转换与热力循环发电,将电能转化为高温热能存储,并在用电高峰时驱动汽轮机发电[4]。该技术可无缝对接燃煤机组,替代或部分替代燃煤锅炉,保留原有汽轮机及辅机系统,实现“锅炉-储能”耦合改造。
作为一种新型储能技术,卡诺电池具有储能密度高,建设不受地理位置限制,储能周期长等优势[5-7]。赵永亮等[8]对基于跨临界CO2的卡诺电池储能系统进行了热力学性能分析,从热力学性能和经济性角度得出系统最优构型。Tafur-Escanta等人[9]提出了一种基于超临界CO2(S-CO2)的热泵储能系统,得出系统的往返效率为59.63%。Xi等人[10]研究了4种基于有机朗肯循环和蒸汽压缩热泵的卡诺电池系统,构建了能量、㶲和经济(3E)模型,分析了不同系统配置的热力学性能和经济性能。Dostal等人[11]从热力学和经济性两方面比较了S-CO2、氦气布雷顿循环、过热蒸汽循环和超临界蒸汽循环,分析了S-CO2的特点以及未来的研究方向。Geyer等人[12]提出将即将退役的燃煤电厂改造为熔盐卡诺电池储能系统。卢沛等[13]提出将余热与有机朗肯循环耦合的全时段耦合余热的卡诺电池系统。韩瑞等[14]将传统燃煤电厂与熔盐卡诺电池相耦合,探究了以氩气、氮气和CO2作为循环工质,以及有无回热系统对往返效率的影响。Hu等人[15]提出了一种基于熔盐储能的热电联产系统,通过将低谷电价转化为热能并储存建立了经济学模型和热力学模型并进行了参数分析。Zhang等人[16]提出了从火电厂中提取蒸汽用于辅助卡诺电池,提高其热泵能效系数和储能往返效率。孙瑞强等[17]对S-CO2工质的热泵储电系统展开研究,建立了热力学与技术经济性分析模型。封官斌等[18]分析了高温卡诺电池储热、电加热和双向循环系统的优势与挑战,指出其在地理独立性和大规模储能中的潜力。Zhang等人[19]提出了基于CO₂混合物的跨临界储能系统,并进行了多参数优化和蒙特卡洛经济性分析。林小杰等[20]提出基于相变材料的蒸汽卡诺电池热力学循环,通过优化参数和多级压缩结构,循环效率和供热㶲效率分别达到56.96%和68.74%。
可见,卡诺电池储能系统具有很高的研究价值和广泛的应用前景。但是,目前基于燃煤机组的卡诺电池研究都还处在初级阶段,循环工质多以氩气、空气和CO2为主[21]。相较于其他气体,S-CO2具有临界点接近环境温度,高密度,来源广泛和成本低等优势[22]。同时,S-CO2在临界点位置比热容较大,且膨胀过程无液化,在工程上更方便实现。但目前为止,对以S-CO2为工质的卡诺电池研究多以简单布雷顿循环或带回热的布雷顿循环为主,较少涉及进一步的流程优化。
鉴于此,本文提出了一种基于燃煤发电机组的新型“S-CO2逆布雷顿-朗肯循环”卡诺电池系统。利用EBSILON Professional软件对系统进行建模,在此基础上开展热力学和敏感性分析,最后利用遗传算法对关键参数进行优化。
选取S-CO2逆布雷顿循环为储能循环,熔盐储热罐作为储热系统,燃煤发电机组作为释能循环,构成卡诺电池系统(简称参考系统),系统示意如图1所示。在S-CO2逆布雷顿循环中,弃电和透平共同驱动压缩机将S-CO2进行压缩后经熔盐加热器对熔盐放热,完成储热过程。之后S-CO2经回热器放热后进入透平做功,透平出口的S-CO2依次经冷源加热器和回热器加热后,进入压缩机完成储能循环。其中,冷源加热器的热源为燃煤机组乏汽,实现了燃煤机组的余热回收。储能循环的主要热力学参数见表1。储热系统以二元盐(60%的硝酸钠+40%的硝酸钾)为介质,储、释热温度分别为320、560 ℃。储热时,冷罐的熔盐经熔盐加热器加热后存入热罐;释热时,热罐中的熔盐分流经过再热器和过热器对蒸汽加热后汇合,之后进入蒸发器和预热器加热锅炉给水。燃煤发电机组选取典型300 MW亚临界燃煤机组,机组型号为N300-16.67/537/537,汽轮机型式为一次中间再热、单轴、凝气式汽轮机,回热系统采用“三高四低一除氧”运行,机组背压为5.39 kPa。表2给出了燃煤机组THA工况下的关键参数。
图2为参考系统储能循环的温度-比熵(T-s)图。由于S-CO2在临界点附近等压线较为密集,导致透平做功过程(6-1)的比功较小,为21.25 kW/kg。若在回热环节(5-6)中部分工质提前做功,有助于提高单位工质在透平的比功。
鉴于此,本文提出一种新型“S-CO2逆布雷顿-朗肯循环”卡诺电池系统(简称新型系统),其流程示意如图3所示。相较于参考系统,新型系统将回热器分为2个,并在回热器1后增加了分流膨胀。此时,经回热器1放热后的工质一部分进入回热器2继续回热并进入透平2做功;另一部分则直接通过透平1膨胀做功。两部分工质在冷源加热器之后汇合。此时,透平1中的工质在远离临界点的状态膨胀,可显著提高工质膨胀过程的比功。
采用EBSILON Professional软件对新型系统进行建模[23],该软件被广泛用来模拟热力循环过程,并对热力系统进行设计和优化。新型系统的模型建构如图4所示。模型主要假设:
1)工质在压缩机中的压缩和工质在透平中的膨胀均为绝热过程;
2)忽略管道和换热器中的散热损失;
3)所有过程均达到稳定状态;
4)熔盐储释热过程均不考虑最小不凝结流量;
5)熔盐储热罐无散热损失;
6)电动机效率、锅炉效率和发电效率分别为99%、93%和99%。
新型系统中CO2的物性参数来源于美国国家标准与技术研究所(NIST)的物性数据库Refprop。压缩机耗功WC和透平输出功WT分别可表示为[24]
WC=m(hout,Chin,C)=m(hout,Chin,C)ηs,C
WT=m(hin,Thout,T)=m(hin,Thout,T)ηs,T
式中:下标C和T分别代表压缩机和透平;m为通过压缩机和透平的质量流量,kg/s;hinhout分别为进、出口实际比焓,kJ/kg;hout为出口的理想比焓(定熵过程),kJ/kg;ηs为等熵效率,%。
压比β定义为:
β=pout,Cpin,C=pin,Tpout,T
式中:pinpout分别代表压缩机和透平的进、出口压力,MPa。
分流比α定义为进入透平1的工质的流量比例,可表示为:
α=Min,TM
式中:Min,TM分别代表直接进入透平1的工质质量流量和工质总的质量流量,kg/s。
回热器、熔盐换热器和冷源换热器的换热量Q可表示为:
Q=mc(hout,chin,c)=mh(hin,hhout,h)
式中:下标c和h分别代表换热器冷侧和热侧。
蒸汽吸热量QS为:
QS=QB+QR
式中:QBQR分别为蒸汽在燃煤锅炉和储热系统放热过程的吸热量,kW。
蒸汽在燃煤锅炉中吸热量QB可表示为:
QB=QcoalηB=[mms(hout,mshin,ms)+mrs(hout,rshin,rs)]
式中:下标ms和rs分别代表进入燃煤锅炉的主蒸汽和再热蒸汽;Qcoal为锅炉消耗燃煤热量,kW;ηB为锅炉效率。
蒸汽在熔盐放热过程的吸热量QR可表示为:
QR=mms(hout,mshin,ms)+mrs(hout,rshin,rs)
式中:mmsmrs分别为进入熔盐放热过程过热器和再热器的蒸汽质量流量,kg/s。
汽轮机膨胀做功为:
W=i=1nWi=i=1n(miΔhiηs,iηm,i)
式中:n为汽轮机膨胀级数;Wi为第i级膨胀级做功量,kW;Δhi为第i级膨胀级理想焓降,kJ/kg;ηm为机械效率。
膨胀级变工况遵循弗留格尔公式:
mAmB=pin,A2pout,A2pin,B2pout,B2Tin,BTin,A
式中:下标A、B分别代表2种工况;Tin表示膨胀级进口温度,K。
基于上述公式和模型,表3给出了不同工况下汽轮机发电功率模拟值和实际值的对比。可以看出模拟值与电厂汽轮机的实际值具有高度的一致性。表4给出了热泵系统各状态点参数与现有文献数据的对比。表4数据表明本文模型具有较高的准确性。
选取储能循环的能效系数(coefficient of performance,COP)和新型系统的往返效率(round trip efficiency,RTE)评价储能环节和整个储放电环节的热力学性能。其中储能循环的能效系数cCOP可表示为:
cCOP=QMWCWT=QMEw
式中:QM为储能循环熔盐吸热量,kW;Ew为储能循环接纳的弃电功率,kW。
新型系统的往返效率ηRTE可表示为[25]
ηRTE=CCOPηeηpηm
式中:ηeηmηp分别为发电机效率、机械效率和释能过程热转电效率。选取75%THA工况为典型释能过程[26]ηp取44.59%。
在新型系统回热器2的上端差为15 ℃、分流比为0.2的工况下,图5给出了新型系统储能循环的T-s图。其中,透平1中膨胀过程(4—5)的比功为82.37 kW/kg,透平2中膨胀过程(8—9)的比功为18.75 kW/kg。膨胀过程的平均比功为31.47 kW/kg,较原系统高10.22 kW/kg。这使得新型系统在接纳弃电均为100 MW且压比不变的情况下,压缩机的工质流量提高。
表5进一步给出了参考系统和新型系统储能循环的热力学性能对比。
可以看出,在设计工况下,新型系统的透平做功量、余热回收量和COP均较参考系统有所提高。其中新型系统的透平做功量较参考系统提高9.06 MW,提高了59.84%。此时,压缩机耗功也相应提高了9.06 MW。鉴于压缩比功不变,新型系统的工质流量较参考系统提高了201.79 t/h。因此,虽然有分流膨胀,但新型系统中冷源换热器的余热回收量仍较参考系统高9.61 MW,提高了43.23%。此时,新型系统储能循环的COP为1.32,较参考系统提高了0.10。以燃煤机组发电75%THA工况为典型释能工况,新型系统的RTE为57.68%,较参考系统提高了4.37百分点。
新型系统中压比β、分流比和回热器2上端差均对系统热力学性能有较大影响。鉴于此,在压缩机出口工质温度为570 ℃,储能循环接纳弃电量为100 MW的条件下,针对上述参数开展敏感性分析。
图6为压比β变化对2个系统透平做功、能效系数和往返效率等热力学性能的影响。
图6a)可看出,随着压比β的提高,2个系统透平做功均增加,且二者差值也在增加。此外,新型系统中透平做功量的提高主要来源于透平2。当压比由2.0提高到4.0,参考系统的透平做功由14.63 MW增加到16.22 MW,提高了10.87%。新型系统的透平做功由16.48 MW增加到20.52 MW,提高了24.51%。2个系统透平做功的差值由1.59 MW提高到4.04 MW。同时,新型系统中透平2的做功量由11.36 MW增加到12.19 MW,提高了7.31%。由图6b)可以看出,2个系统的COP和RTE都随着压比的增加而增大,且新型系统的COP和RTE始终都大于参考系统。当压比由2.0提高到4.0,新型系统和参考系统的COP分别提高0.16和0.13,RTE分别提高6.93百分点和5.66百分点。新型系统的COP和RTE最大分别为1.35和58.87%。
图7展示了分流比对新型系统热力学性能的影响。
图7a)可以看出,随着分流比的提高,回热器的总回热量变化较小,回热器1的回热比重增加,同时,透平2前的工质温度逐渐下降。当分流比从0.05增至0.45,回热器1的回热量从250.15 MW增至267.70 MW,回热器2的回热量从119.24 MW降至93.17 MW。透平前工质温度从75.90 ℃降至58.14 ℃。此时,若分流比进一步增大,则透平出口工质将变为液态。分流比的增大会增加透平1中工质的流量,由于透平1的比功较透平2大,随分流比增大,新型系统的透平做功量也增加。由图7b)可以看出,由于随着分流比的增大进入透平1的工质流量增加,透平1的做功量从1.78 MW增加至17.18 MW,透平2的做功从14.25 MW减少到7.00 MW,透平总做功量从16.03 MW增加到24.12 MW。COP从1.23增加至1.32,往返效率从53.83%增至57.60%。
图8给出了分流比和压比一定时回热器2上端差对新型系统热力学性能的影响。
图8a)可以看出,回热器2上端差的变化对分流处工质温度的影响较大,随着上端差从15 ℃增加至50 ℃,分流处的工质温度从298.59 ℃降低到127.69 ℃。回热器回热量变化较小,但回热器1的回热比重增加,回热器1的回热量从125.18 MW增加至293.44 MW,回热器2的回热量从233.8 MW减少到74.25 MW。由图8b)可以看出,透平做功量、COP和往返效率随回热器2上端差的增大而减小。总透平做功量减少是由透平1的做功量减少造成的,总透平做功量从24.20 MW减少到17.24 MW,减少了6.96 MW,透平1的做功量从12.67 MW减少到5.71 MW,减少了6.96 MW。端差的增大使得系统的COP从1.32降低到1.24,RTE从57.61%减小到54.39%。
鉴于分流比、压比以及回热器2上端差对新型系统的热力学性能有较大影响,进一步采用遗传算法对上述关键参数进行优化。遗传算法是一种广泛应用于工程设计的优化方法,是基于达尔文生物进化论的算法,通过模拟自然进化过程(选择、交叉和变异)来实现特定对象的优化[26-27]。遗传算法关键参数设置如表6所示。
在此次优化过程中,以压缩机出口温度570 ℃和透平2的排气干度x=1作为约束条件,RTE被选为目标函数,可以描述为:
RTE=f(β,D,α)
式中:D为回热器2上端差,℃。
在进化过程中,目标函数(即RTE)值较高的个体得以存活并被允许产生下一代,而RTE值较低的个体则被淘汰。在进化过程之后,将在最后一代中选择最佳值。各关键参数优化范围如表7所示。
参数优化前、后系统热力学性能对比见表8。优化后分流比、回热器2的上端差和压比分别为0.23、12.60 ℃和3.09。此时,工质流量较优化前减小了248.78 t/h。分流比的增大使透平1的做功增加了2.77 MW,优化后透平总做功增加了2.44 MW。同时,冷源加热器处余热回收量增加了4.91 MW。优化后储能循环的COP和系统的RTE分别较优化前提高了0.05和2.19百分点,达到1.37和59.87%。
1)采用分流膨胀,新型系统储能循环的透平做功量增加,进而提高系统的COP和RTE。新型系统储能循环的透平做功量较参考系统提高了9.06 MW,余热回收量提高了9.61 MW,COP提高了0.10。新型系统的RTE达到57.68%,较原系统提高了4.37百分点。
2)压比和分流比的增大以及回热器2上端差的下降可提高新型系统的RTE。当压比从2.0增加到4.0,新型系统的RTE从51.94%提高至58.87%。当分流比从0.05提高到0.45,新型系统的RTE从53.83%提高至57.60%。当回热器2上端差从15 ℃增大到50 ℃,新型系统的RTE从57.61%降低至54.39%。
3)经遗传算法优化,在压比为3.09、分流比为0.23、回热器2上端差为12.6 ℃时,新型系统储能循环的COP和RTE最大可分别达到1.37和59.87%。
  • 国家自然科学基金青年科学基金项目(52206012)
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doi: 10.19666/j.rlfd.202504057
  • 接收时间:2025-04-15
  • 首发时间:2026-08-14
  • 出版时间:2026-02-25
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  • 收稿日期:2025-04-15
  • 修回日期:2025-05-06
  • 录用日期:2025-05-08
基金
Young Scientists Fund of the National Natural Science Foundation of China(52206012)
国家自然科学基金青年科学基金项目(52206012)
作者信息
    1.国网河南省电力公司电力科学研究院,河南 郑州 450052
    2.华北水利水电大学能源与动力工程学院,河南 郑州 450045

通讯作者:

赵世飞(1991),男,博士,副教授,主要研究方向为燃煤热电联产机组高效灵活运行技术,
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
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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