Article(id=1215700881031479797, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1215700878661702357, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202403041, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1710000000000, receivedDateStr=2024-03-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1767775276668, onlineDateStr=2026-01-07, pubDate=1719244800000, pubDateStr=2024-06-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1767775276668, onlineIssueDateStr=2026-01-07, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1767775276668, creator=13701087609, updateTime=1767775276668, updator=13701087609, issue=Issue{id=1215700878661702357, tenantId=1146029695717560320, journalId=1210938733613449225, year='2024', volume='53', issue='6', pageStart='1', pageEnd='150', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1767775276102, creator=13701087609, updateTime=1767775427616, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1215701514199417515, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1215700878661702357, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1215701514199417516, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1215700878661702357, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=87, endPage=95, ext={EN=ArticleExt(id=1215700881257972219, articleId=1215700881031479797, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Parameter estimation and performance analysis of a recuperative microturbine cycle, columnId=1211002405299294959, journalTitle=Thermal Power Generation, columnName=Thermal energy science research, runingTitle=null, highlight=null, articleAbstract=

By taking the test bench of a micro gas turbine cycle system as the research object, a mathematical model for regenerative cycle system of the micro gas turbine is established. On this basis, the performance prediction and analysis for the regenerative cycle system is carried out. Considering the performance parameters of the system’s key components are presently unknown, the maximum likelihood estimation method is employed to estimate them by using the experimental data. The results show that, the error between the model predicted value and the experimental value is smaller than 3%, indicating the model can accurately predict the thermal performance of the cycle. Subsequently, based on the established model, a performance simulation of the recuperative cycle is conducted under various working conditions. The variation rules of power, generation efficiency, exhaust gas energy, and exhaust gas temperature with the changes of load and ambient temperature are obtained, and the compressor’s operating range is also obtained. The information regarding the key components of the microturbine and the performance characteristics acquired through this study can serve as valuable references for related research.

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以某微燃机循环系统试验台为对象,构建了微燃机回热循环系统模型,并基于此开展了回热循环系统的性能预测与分析。考虑到系统的关键部件性能参数未知,利用极大似然估计法,结合实验数据对其进行了估计,所得预测值和实验值的误差在3%以下,表明模型能够较为准确地预测回热循环的热力性能。然后基于建立的模型,开展了全工况的回热循环系统模拟,获得了不同环境温度下随负荷变化时微燃机功率、发电效率、排烟热量和排烟温度等的变化规律以及压气机的工作区间。所获得的微燃机关键部件信息和系统性能变化规律可为相关研究提供一定的参考。

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张士杰(1971),男,博士,研究员,主要研究方向为先进燃气轮机循环和分布式能源系统优化集成,
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常有润(1997),男,博士研究生,主要研究方向为燃气轮机循环模拟,

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常有润(1997),男,博士研究生,主要研究方向为燃气轮机循环模拟,

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常有润(1997),男,博士研究生,主要研究方向为燃气轮机循环模拟,

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articleId=1215700881031479797, language=EN, label=Fig.11, caption=Operating range of the compressor, figureFileSmall=5FroOnF5Bn2thmT4SBk7SQ==, figureFileBig=sKclE+mtsp1CbLcycZK9kg==, tableContent=null), ArticleFig(id=1215700892821668783, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1215700881031479797, language=CN, label=图11, caption=压气机工作情况, figureFileSmall=5FroOnF5Bn2thmT4SBk7SQ==, figureFileBig=sKclE+mtsp1CbLcycZK9kg==, tableContent=null), ArticleFig(id=1215700892918137777, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1215700881031479797, language=EN, label=Tab.1, caption=

Initial given values of key component parameters

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参数ηc,dπc,dηT,dε
给定值71.104.3589.500.87
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关键部件参数的初始给定值

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参数ηc,dπc,dηT,dε
给定值71.104.3589.500.87
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Estimated values of key component parameters

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项目估计值95%置信区间95% t
ηc,d70.800.703100.80
πc,d4.330.08153.75
ηT,d90.200.641140.80
ε0.872.02230.65
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关键部件参数的求解结果

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项目估计值95%置信区间95% t
ηc,d70.800.703100.80
πc,d4.330.08153.75
ηT,d90.200.641140.80
ε0.872.02230.65
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Basic parameters under design condition of the recuperative microturbine cycle

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项目数值
压气机进气流/(kg·s–1)0.943
压比4.33
等熵效率/%70.8
燃烧室压损系数/%4.5
QLHV/(kJ·kg–1)45 386
效率/%99.5
透平膨胀比3.63
等熵效率/%90.2
进气温度/℃937
回热器效能0.87
空气侧压损系数/%6
烟气侧压损系数/%4
冷却气比例/%6
空气进口损失/%1
烟气出口损失/%1
), ArticleFig(id=1215700893383705539, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1215700881031479797, language=CN, label=表3, caption=

微燃机回热循环设计工况基本参数

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项目数值
压气机进气流/(kg·s–1)0.943
压比4.33
等熵效率/%70.8
燃烧室压损系数/%4.5
QLHV/(kJ·kg–1)45 386
效率/%99.5
透平膨胀比3.63
等熵效率/%90.2
进气温度/℃937
回热器效能0.87
空气侧压损系数/%6
烟气侧压损系数/%4
冷却气比例/%6
空气进口损失/%1
烟气出口损失/%1
), ArticleFig(id=1215700893480174536, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1215700881031479797, language=EN, label=Tab.4, caption=

Sensitivity analysis for the parameters

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损失系数燃烧室压损系数回热器空气侧压损系数回热器烟气侧压损系数空气进口损失烟气出口损失
性能参数初始值/%4.56.04.01.01.0
浮动范围/%10.010.010.010.010.0
压气机出口温度/K00000
00000
透平排烟温度/K-3.76-0.51-0.33-0.080-0.080
+3.81+0.51+0.33+0.080+0.080
发电效率/%+0.05+0.01000
-0.05-0.01000
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参数的敏感性分析结果

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损失系数燃烧室压损系数回热器空气侧压损系数回热器烟气侧压损系数空气进口损失烟气出口损失
性能参数初始值/%4.56.04.01.01.0
浮动范围/%10.010.010.010.010.0
压气机出口温度/K00000
00000
透平排烟温度/K-3.76-0.51-0.33-0.080-0.080
+3.81+0.51+0.33+0.080+0.080
发电效率/%+0.05+0.01000
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微燃机回热循环的参数估计与性能分析
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常有润 1, 2 , 张士杰 1, 2 , 王波 1, 2 , 路源 1, 2 , 赵丽凤 1, 2
热力发电 | 热能科学研究 2024,53(6): 87-95
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热力发电 | 热能科学研究 2024, 53(6): 87-95
微燃机回热循环的参数估计与性能分析
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常有润1, 2 , 张士杰1, 2 , 王波1, 2, 路源1, 2, 赵丽凤1, 2
作者信息
  • 1.中国科学院先进能源动力重点实验室(工程热物理研究所),北京 100190
  • 2.中国科学院大学,北京 100049
  • 常有润(1997),男,博士研究生,主要研究方向为燃气轮机循环模拟,

通讯作者:

张士杰(1971),男,博士,研究员,主要研究方向为先进燃气轮机循环和分布式能源系统优化集成,
Parameter estimation and performance analysis of a recuperative microturbine cycle
Yourun CHANG1, 2 , Shijie ZHANG1, 2 , Bo WANG1, 2, Yuan LU1, 2, Lifeng ZHAO1, 2
Affiliations
  • 1.Key Laboratory of Advanced Energy and Power (Institute of Engineering Thermophysics), Chinese Academy of Sciences, Beijing 100190, China
  • 2.University of Chinese Academy of Sciences, Beijing 100049, China
出版时间: 2024-06-25 doi: 10.19666/j.rlfd.202403041
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以某微燃机循环系统试验台为对象,构建了微燃机回热循环系统模型,并基于此开展了回热循环系统的性能预测与分析。考虑到系统的关键部件性能参数未知,利用极大似然估计法,结合实验数据对其进行了估计,所得预测值和实验值的误差在3%以下,表明模型能够较为准确地预测回热循环的热力性能。然后基于建立的模型,开展了全工况的回热循环系统模拟,获得了不同环境温度下随负荷变化时微燃机功率、发电效率、排烟热量和排烟温度等的变化规律以及压气机的工作区间。所获得的微燃机关键部件信息和系统性能变化规律可为相关研究提供一定的参考。

微燃机  /  回热循环  /  实验  /  参数估计  /  性能分析

By taking the test bench of a micro gas turbine cycle system as the research object, a mathematical model for regenerative cycle system of the micro gas turbine is established. On this basis, the performance prediction and analysis for the regenerative cycle system is carried out. Considering the performance parameters of the system’s key components are presently unknown, the maximum likelihood estimation method is employed to estimate them by using the experimental data. The results show that, the error between the model predicted value and the experimental value is smaller than 3%, indicating the model can accurately predict the thermal performance of the cycle. Subsequently, based on the established model, a performance simulation of the recuperative cycle is conducted under various working conditions. The variation rules of power, generation efficiency, exhaust gas energy, and exhaust gas temperature with the changes of load and ambient temperature are obtained, and the compressor’s operating range is also obtained. The information regarding the key components of the microturbine and the performance characteristics acquired through this study can serve as valuable references for related research.

microturbine  /  recuperative cycle  /  experiment  /  parameter estimation  /  performance analysis
常有润, 张士杰, 王波, 路源, 赵丽凤. 微燃机回热循环的参数估计与性能分析. 热力发电, 2024 , 53 (6) : 87 -95 . DOI: 10.19666/j.rlfd.202403041
Yourun CHANG, Shijie ZHANG, Bo WANG, Yuan LU, Lifeng ZHAO. Parameter estimation and performance analysis of a recuperative microturbine cycle[J]. Thermal Power Generation, 2024 , 53 (6) : 87 -95 . DOI: 10.19666/j.rlfd.202403041
微燃机因体积小、环保性能优越、维护成本低等特点,近年来得到迅速发展。在实际应用中,针对微燃机循环系统进行性能预测[1-3]、运行优化[4-6]以及故障诊断[7-8]等是十分必要的,但开展这些工作的前提是掌握微燃机循环及其关键部件信息。然而,因厂家保密、装配维修和性能退化等原因,循环系统的关键部件性能参数的准确性无法得到保证[9-10]。对微燃机循环系统的关键部件性能参数进行预估,继而准确预测与把握循环系统的热力性能,具有重要的理论意义和工程应用价值。
在推测系统模型参数即参数估计方面,不少学者针对燃气轮机开展了一些研究。Li等人[9]提出了一种改进的燃气轮机非设计性能自适应方法,以预测的性能曲线和各部件的性能回归曲线的相似度作为评估标准,并将其应用于某燃气轮机进行验证;Saturday等人[11]以燃气轮机简单循环为对象采用搜索算法实现参数估计,并比较了在手动调整效率等参数时所获得的性能。在微燃机的参数估计方面,欧阳艳艳等[12]以模拟数据作为反问题的求解条件,利用极大似然估计反推循环系统单元部件额定效率和压气机特性方程的模型参数;KIAEE等人[13]通过设计点适应获得部件设计参数,以非设计适应获得压缩机和涡轮机特性方程系数,并与文献数据进行验证。需要指出,微燃机一般为回热循环,与燃气轮机的简单循环形式有明显不同。如微燃机有回热器,且其性能对循环性能至关重要,而回热器的换热效率一般难以获得。目前,以微燃机为对象,基于实际运行数据的参数估计研究较为缺乏。
另一方面,微燃机在热电联供等分布式能源系统领域得到广泛的应用[14-17]。准确的系统热力性能变化规律,是进行分布式能源系统的优化配置和运行研究的前提和基础。Yang等人[18]在冷热电耦合的分布式能源系统优化时,需要考虑设备在部分负荷下的热力特性,如燃料消耗量与排烟热量、做功等的关系;印佳敏等[19]研究了基于热电联供的分布式能源系统的优化运行,需要预先给定循环机组的燃料消耗量、机组出力与部分负荷等的性能关系。但是,系统、详细的热力性能变化关系较难获得,而基于实际循环机组的运行数据尤为不足。
本文基于某一微燃机,构建了回热循环系统并开展相关研究。首先在该微燃机回热循环系统实验数据的基础上,应用极大似然估计法推算了微燃机系统关键部件参数;其次,运用推测所获得的部件性能参数,开展了微燃机回热循环的模拟研究,给出了循环的功率、效率、排烟热量和排烟温度等物理量的变化规律。本文根据实际运行数据给出的全面、系统的微燃机部件特性信息和系统热力性能变化规律也可为分布式能源系统优化配置等相关研究提供重要参考。
本文微燃机循环系统试验台由离心式压气机、燃烧室、轴流式透平、回热器、高速电机等构成。试验台的测量系统采用可编程逻辑控制器(PLC)的配置方案,可实时测量压气机进气流量和出口温度、透平进口压力和排烟温度、回热器冷热侧出口温度、输出功率、转速等关键参数。
微燃机中所采用的离心压气机具有容积流量小、单级压比高等特点。由于当前对压气机的流量、效率与压比的关系尚无准确的理论公式,在仿真模拟中通常采用特性曲线模型表示压气机的特性[20]。通过对压气机的特性曲线进行无量纲化处理,以插值计算的方式获取压气机的运行点(图1)。
压气机特性曲线包括相似转速ns、相似流量qs、压比π和等熵效率ηC 4个参数。在这些表征特性的参数中,只要其中任意2个参数已知,便可通过插值计算的方法获得未知参数的值。在无量纲化压气机特性曲线的基础下,相关参数同样进行无量纲化处理,计算公式如下。
无量纲相似转速:
n¯=100×nsns,d
无量纲相似流量:
q¯=qsqs,d
无量纲压比:
π¯=π1πd1
无量纲效率:
ηC¯=ηCηC,d
式中:ns=n/(RTC,in)qs=qC(RTC,in)/pC,inn为转速,r/min;q为质量流量,kg/s;η为效率;p为压力,Pa;下标in表示进口,s表示相似变量,C表示压气机,d表示设计工况。
压气机消耗功PC计算公式为:
PC=qC(hC,outhC,in)ηm,C
式中:P为功率,W;h为焓,J/kg;ηm,C为压气机的机械效率,取值0.99;下标out表示出口。
压缩空气和天然气燃料在燃烧室内发生化学反应,释放热量。在燃烧室模型的稳态计算中,仅从模型整体考虑完全燃烧对模型进出口参数的影响。燃烧室模型的质量守恒和能量守恒方程为:
qa+qf=qg
qaha+qf(hf+ηccQLHV)=qghg
式中:QLHV为燃料天然气的低位发热量,J/kg;下标cc表示燃烧室,a表示空气,f表示燃料,g表示烟气。
工质在燃烧室中因流动黏性、热交换等必然产生压力损失。在模型计算中,燃烧室的出口压力通常由压力损失系数δ给出,压力平衡计算公式为:
pcc,out=(1δ)pcc,in
本文微燃机采用轴流式透平,具有效率高等特点。与压气机建模的方法一致,可采用特性曲线或者特性方程模型[20]来表示透平的特性。
1)透平特性方程模型
透平中存在临界流动的情况,此时透平的工质流量仅与进口参数有关,而与背压无关,且在转速不变时,流量不再随膨胀比的增大而增大[21]。因此,在特性方程的模型中,以临界膨胀比为基准,存在阻塞工况关系式和非阻塞工况关系式。
临界膨胀比:
πT,cri=1(2γ+1)γγ1
阻塞工况关系式:
qTTT,inpT,in=AT1R2γγ1[(2γ+1)2γ1(2γ+1)γ+1γ1]
非阻塞工况关系式:
qTTT,inpT,in=AT1R2γγ1[πT2γπTγ+1γ]
式中:γ为绝热系数;πT为透平的膨胀比,πT=Pt,in/Pt,outA为面积,m2R为气体常数,R=8.314 J/(mol·K);下标T表示透平,cri表示临界状态。
2)透平特性曲线模型
与压气机模型类似,采用无量纲化方法处理特性曲线[22],通过插值计算的方法获得转速、质量流量、压力和效率等参数。
透平输出功PT计算公式为:
PT=ηm,TqT(hT,inhT,out)
式中:ηm,T为透平的机械效率,取值0.99。
回热器回收并利用透平排烟中的高品位热量,可以有效提高循环系统的发电效率。在稳态计算中,回热器模型采用效能-传热单元数(ε-NTU)方法[23]进行计算。
ε=λ1λ(qcp)ratio
NTU=kA(qcp)min
式中:k为传热系数,W/(m2·K);ε为效能;cp为定压比热容,J/(kg·K);λ为中间参数;NTU为传热单元数;(qcp)min为冷热流体中较小热容;(qcp)ratio为冷热流体中较小热容与较大热容的比值。
在变工况模型的计算时,受流体热阻等影响,需要根据实际工况的流量、温度和压力对传热系数和压力损失系数进行修正。
k=kd(qh,inqh,in,d)0.8
δph=δph,d(qh,inqh,in,d)1.84(Th,inTh,in,d)(ph,inph,in,d)1
δpc=δpc,d(qc,inqc,in,d)1.98
式中:下标h表示烟气侧,c表示空气侧,w表示壁面。
基于gPROMS过程模拟软件,采用模块化建模的方法,建立压气机、透平、燃烧室、回热器等单元部件模型,构建微燃机回热循环系统模型(图3),其中,一部分压气机出口空气用于透平冷却,但不参与透平做功。
在开展循环系统的实验与模拟对比研究时,需要在模拟软件中构建循环系统模型,但考虑到系统中部分关键部件的参数未知,无法准确获得相关数值,因此,通过实验数据反推得到循环系统的关键部件参数显得尤为重要[24]。本节便应用极大似然估计求解系统的关键部件性能参数,使模拟预测的性能值更为准确,更接近实验的性能值。
本文参数估计采用极大似然法,其目的在于通过寻找并确定模型的未知参数,最大概率地提高数学模型预测值的准确性。对于服从正态分布的样本,目标函数为:
Φ=N2ln(2π)+12minβ{i=1NEj=1NVik=1NMij[ln(σijk2)+(z˜ijkzijk)2σijk2]}+
式中:N为实验测量总次数;β为模型的待估参数;NE为实验次数;NVii次实验的测量变量数;NMiji次实验对变量j的测量次数;σijk2为测量方差;z˜ijk为测量值;zijk为预测值。
对参数估计结果的合理性的检验包括拟合偏差检验和参数t检验:
1)拟合偏差检验 如果加权残差平方和S小于95%置信水平x2值,则拟合成功,表明模型能够准确反应系统,其中,S=i=1NEj=1NVik=1NMij[(z˜ijkzijk)2σijk2]
2)参数t检验 如果待估参数95% tti大于95% t值的参考值t(0.95, N-Nβ),表明参数被准确估计,其中,ti=β^iXi(0.95)Xi(0.95)为变量的95%置信空间。
在此微型回热循环系统试验台的实际测量时,系统测点参数包括压气机进气流量qc、压气机出口温度Tc,out、透平进口压力pT,in、透平排气温度TT,out、回热器空气出口温度Tc,out以及回热器烟气出口温度Th,out。其中,压力为绝对压力。在一定的实验环境条件下,采集了35、50、65、80、95、110 kW共6个负荷的测点参数实验值。基于采集的实验数据,开展循环系统的参数估计,以测点参数的实验值作为已知条件,求解关键部件参数,包括压气机压比和等熵效率、透平等熵效率以及回热器效能。回热循环系统模拟计算所需的部件设计工况参数,除所需求解的参数以外,其余参数均为已知参数。
在开展整个循环系统的参数估计前,依照先前经验以及文献[22,25],对压气机等在内的单元部件进行特性信息参数(特性曲线、部件参数等)的调整,当性能模拟值与实验值能够较好吻合时,确定为单元部件初始参数,具体见表1
结合实验数据开展问题求解,所得加权残差平方S为26.983,95%置信水x2值为49.802,S<x2,表明模型能较好地反映系统性能。其次,对循环系统的关键部件参数的估计结果见表2,95% t值的参考值为1.689,而待估参数的95% t值均远大于参考值,这表明系统的关键参数被准确估计。
图4为系统各测点参数实验值和预测值的比较。由图4可见,各测点参数值的预测值与实验值的误差均在3%以下,两者吻合程度较好,表明模拟系统利用参数估计法所得的关键部件参数能够较为准确地预测回热循环热力性能。
通过参数估计获得部件关键性能参数后,结合系统的设计工况,计算出透平膨胀比等其他参数,以便后续采用透平特性曲线模型开展模拟。回热循环系统的设计工况基本参数见表3
压损系数作为循环系统中不可忽视的部分,在前述的参数估计时,各压损系数作为已知参数给出,但其大小对性能计算也存在一定的影响,因此,有必要在设计发电功率下以给定的压损系数进行敏感性分析。表4为参数的敏感性分析结果。由表4可知:压损系数的变化对压气机出口温度均无影响,但对透平排烟温度均有影响,且燃烧室压损的影响最大;影响发电效率的主要是燃烧室压损和回热器空气侧压损。
在对回热循环系统开展模拟分析时,透平通常采用特性曲线模型,但在进行参数估计时,透平采用的是特性方程模型,其原因在于特性方程模型所需参数少,减少了计算繁琐度。
在应用图2所示的透平特性曲线后,对循环系统在不同负荷下的热力性能进行模拟,并与特性方程模型的结果进行对比分析,结果如图5所示。从图5可以看出,在不同负荷下,各测点参数的相对误差均在0.5%以下。因此,所采用的透平特性曲线模型无需进一步修正,可应用于研究以此微燃机为基础的动力循环系统。
循环系统试验台在孤网模式下,采用定转速方式运行,改变外界负载,循环系统的性能相应发生变化,同时,在实际环境中运行时,因环境温度改变,相同负荷时循环系统的热力性能会有所不同。给定不同的环境温度,通过模拟来预测并分析系统的热力性能以及运行情况,获得负荷变化时该循环系统性能的变化规律。
图6为在不同环境温度时,压气机消耗功和透平输出功随负荷的变化。由图6可见,当负荷增大时,燃料流量增加,透平入口温度上升,进气流量减小。透平入口温度是透平膨胀功的决定性因素,透平入口温度上升,因此,透平输出功增大。而压气机消耗功随负荷改变的变化幅度较小,即透平输出功的变化值与负荷变化值基本一致。当环境温度上升较高时,进气流量减小幅度变大,透平输出功和压气机消耗功下降幅度变大。
图7为发电效率变化曲线。由图7可见,循环的发电效率随负荷减少而降低,这符合回热循环的一般规律。
当负荷减少时,燃料流量减小,发电效率降低,负荷每减少10 kW,发电效率降低2%左右;再者,对于回热循环来说,燃料量减小,透平排烟温度下降,回热器热侧换热温差减小,热交换能力减弱,而压气机出口温度变化较小。因此,空气经回热器吸收热量减少,导致发电效率降低幅度较大。其次,在负荷相同时,环境温度越高,发电效率越高。这是因为在不控制透平入口温度时,环境温度上升,进气流量减小,燃料流量减小。
基于发电效率与负荷成非线性关系,拟合得出发电效率与负荷和环境温度的关系式,见式(19)。式中温度单位为K,负荷单位为kW。
ηe=0.0259(PPd)0.731(TaTa,d)0.063 1
从能量梯级利用角度来看,循环系统的排烟在余热利用方面仍具有一定的应用价值,因此,掌握排烟参数的变化规律是十分必要的。图8给出了在不同环境温度时此系统的排烟温度和排烟流量随负荷的变化规律。
在一定环境温度时,当负荷增大时,透平排烟温度上升,热侧换热温差增大,排烟温度上升,排烟流量减小。当负荷改变10 kW时,排烟温度变化约6.0 K,排烟流量变化约0.035 kg/s;当环境温度改变1 ℃,相同负荷下的排烟温度改变约1.3 K,而排烟流量变化幅度随环境温度的上升而变大。
基于排烟温度与环境温度和负荷均接近为线性关系,拟合得出此系统排烟温度的关系式:
Th,out=49.94PPd+459.17TaTa,d+39.9
排烟热量定义为排烟流量与排烟比焓的乘积,图9为排烟热量的变化曲线。在一定环境温度下,当负荷增大时,排烟热量增大,负荷每改变10 kW,排烟热量变化约4.5 kW。当环境温度上升到一定温度时,排烟热量的变化幅度不大。这是因为当环境温度上升时,排烟比焓增大,而排烟流量减小。
图10给出了燃料流量与排烟热量和负荷的变化曲线,通过此曲线可以较为直观地获得在不同环境温度和负荷时,某一排烟热量所消耗的燃料流量。
图11为压气机工作运行情况,图11中蓝线为环境温度变化曲线,负荷变化范围为30~110 kW,红线为等负荷变化曲线,环境温度变化范围为0~30 ℃。在一定的环境温度时,当负荷增大时,压气机进气流量减小,无量纲相似流量减小,无量纲相似压比增大,工作点向喘振边界线靠近。在一定的负荷时,当环境温度上升时,无量纲相似转速减小,工作点向低转速区域移动,无量纲相似流量减小。在实际运行时,工作点基本在红蓝线区域移动,即均处于安全运行范围内,因此,此系统在不同环境温度时全工况内的运行安全能够得到保障。
本文利用模块化建模的方法构建了某微燃机回热循环的单元部件及系统的稳态模型,并基于此模型开展了循环系统的性能预测与分析。
1)在参数估计时,结合实验数据获得系统的关键部件性能参数,测点参数的预测值与实验值的误差均在3%以下,表明该方法能够较为准确地预测回热循环的热力性能。
2)基于参数估计获得的部件特性参数,分析了回热循环系统的全工况热力性能,获得在不同环境温度时回热循环系统的热力性能。在不同环境温度时,透平输出功与负荷成正比关系,而压气机消耗功变化幅度较小;得到发电效率基于负荷和环境温度的关系式,负荷每变化10 kW,发电效率降低2%左右;得到排烟热量与负荷和燃料流量的关系,负荷改变10 kW,排烟热量变化约4.5 kW;此循环系统在不同环境温度时全工况范围内的运行稳定性较为可靠,无压气机喘振问题。
  • 国家科技重大专项(2017-I-0009-0010)
  • 中国科学院青年创新促进会(E229020101)
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doi: 10.19666/j.rlfd.202403041
  • 接收时间:2024-03-10
  • 首发时间:2026-01-07
  • 出版时间:2024-06-25
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  • 收稿日期:2024-03-10
基金
National Science and Technology Major Project(2017-I-0009-0010)
国家科技重大专项(2017-I-0009-0010)
Youth Innovation Promotion Association CAS(E229020101)
中国科学院青年创新促进会(E229020101)
作者信息
    1.中国科学院先进能源动力重点实验室(工程热物理研究所),北京 100190
    2.中国科学院大学,北京 100049

通讯作者:

张士杰(1971),男,博士,研究员,主要研究方向为先进燃气轮机循环和分布式能源系统优化集成,
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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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