Article(id=1236345819553649279, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236345813933289655, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202403056, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1711123200000, receivedDateStr=2024-03-23, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1772697413576, onlineDateStr=2026-03-05, pubDate=1729785600000, pubDateStr=2024-10-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772697413576, onlineIssueDateStr=2026-03-05, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772697413576, creator=13701087609, updateTime=1772697413576, updator=13701087609, issue=Issue{id=1236345813933289655, tenantId=1146029695717560320, journalId=1210938733613449225, year='2024', volume='53', issue='10', pageStart='1', pageEnd='162', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1772697412236, creator=13701087609, updateTime=1772697498476, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1236346175725556508, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236345813933289655, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1236346175725556509, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236345813933289655, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=134, endPage=143, ext={EN=ArticleExt(id=1236345819943719564, articleId=1236345819553649279, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Control strategy optimization and energy saving analysis for slurry circulation pumps in fixed-frequency mode of desulfurization system in coal-fired power units, columnId=1211002409397129992, journalTitle=Thermal Power Generation, columnName=Power generation technology forum, runingTitle=null, highlight=null, articleAbstract=

To accommodate grid-connected large-scale renewable power, coal-fired power plants need to undertake more peak shaving and frequency regulation tasks, so it will engage in the processes of deep peak shaving and load cycling for a long time. In this situation, the performance of wet flue gas desulfurization system (WFGD) will degradation and the auxiliary power consumption will increase significantly. To solve this problem, the dynamic model of an ultra-supercritical 660 MW coal-fired power unit and the dynamic model of the WFGD system based on the double-membrane theory are established. The performance of the desulfurization system is simulated when the slurry circulation pumps are switched under different operating conditions during the load cycling processes. It is found that the precise matching of slurry and flue gas during load cycling processes can achieve the minimum power consumption of the desulfurization system while meeting the SO2 emission standard. Furthermore, when the slurry circulation flowrate changes stepwise during load cycling processes, the prediction model of changes in SO2 mass concentration at the WFGD system outlet is obtained. An optimization control strategy for the slurry circulation pumps in fixed-frequency mode is proposed, which can achieve the best match between the slurry and flue gas during load cycling processes. Finally, the energy saving potential for the proposed control strategy is analyzed. When the load cycling rates are 1.0%, 1.5% and 2.0% Pe/min, the energy saving potential is 20.12%, 21.52% and 22.82% during loading down processes from 75% THA to 50% THA conditions, and that value will be 10.04%, 9.90% and 8.66% during loading up processes, respectively. The difference in flue gas flowrate during load cycling processes is found as a key factor causing the disparate of energy saving potential during loading down and loading up processes.

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为消纳可再生能源大规模并网发电,燃煤发电机组的调峰调频任务剧增,长时间处于深度调峰和变负荷过程,导致湿法烟气脱硫系统的性能下降、厂用电率大幅上升。为此,建立了超超临界660 MW燃煤发电机组的动态模型及基于双膜理论的湿法脱硫系统动态模型;模拟了变负荷过程中不同工况点切换浆液循环泵时脱硫系统的性能,发现变负荷过程中浆液和烟气流量的精准匹配可使脱硫系统在满足SO2排放的前提下实现最小的电能消耗;进一步,获得了变负荷过程中浆液循环流量阶跃变化时SO2出口质量浓度的预测模型,提出了浆液循环泵定频运行优化控制策略,可实现变负荷过程中浆液与烟气流量的最佳匹配;最后,分析了优化控制策略的节能潜力。研究结果表明:75%THA~50%THA降负荷过程中,变负荷速率为1.0%、1.5%和2.0%Pe/min,分别可节能20.12%、21.52%和22.82%;而在升负荷过程中,分别可节能10.04%、9.90%和8.66%,变负荷过程中烟气流速变化的差异是造成降负荷和升负荷过程中节能潜力不同的根本原因。

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严俊杰(1967),男,教授,主要研究方向为热力系统节能与控制优化,
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高伟(1994),男,博士研究生,主要研究方向为燃煤机组灵活清洁协同机理与优化研究,

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高伟(1994),男,博士研究生,主要研究方向为燃煤机组灵活清洁协同机理与优化研究,

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高伟(1994),男,博士研究生,主要研究方向为燃煤机组灵活清洁协同机理与优化研究,

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Process Safety and Environmental Protection, 2022, 159: 698-707., articleTitle=Online application oriented dynamic modeling for the flue gas desulfurization tower in coal-fired power plants, refAbstract=null)], funds=[Fund(id=1236345829137633448, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236345819553649279, awardId=2022YFB4100402, language=EN, fundingSource=National Key R&D Program of China(2022YFB4100402), fundOrder=null, country=null), Fund(id=1236345829229908142, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236345819553649279, awardId=2022YFB4100402, language=CN, fundingSource=国家重点研发计划(2022YFB4100402), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1236345823185916730, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236345819553649279, xref=null, ext=[AuthorCompanyExt(id=1236345823194305339, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236345819553649279, 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Total slurry circulation flowrates and its operation mode at different loads

, figureFileSmall=null, figureFileBig=null, tableContent=
负荷总的浆液循环流量/(m3·h–1)运行方式不同浆液循环泵流量/(m3·h–1)
100%THA46 726A+B+C+D10 322(D)
75%THA36 404A+B+C10 680(C)
50%THA25 724A+B12 666(B)
30%THA13 058A13 058(A)
), ArticleFig(id=1236345829041164449, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236345819553649279, language=CN, label=表1, caption=

不同负荷下总的浆液循环流量及其运行方式

, figureFileSmall=null, figureFileBig=null, tableContent=
负荷总的浆液循环流量/(m3·h–1)运行方式不同浆液循环泵流量/(m3·h–1)
100%THA46 726A+B+C+D10 322(D)
75%THA36 404A+B+C10 680(C)
50%THA25 724A+B12 666(B)
30%THA13 058A13 058(A)
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燃煤机组脱硫浆液循环泵定频运行控制策略优化及节能分析
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高伟 , 刘明 , 赵永亮 , 王朝阳 , 严俊杰
热力发电 | 发电技术论坛 2024,53(10): 134-143
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热力发电 | 发电技术论坛 2024, 53(10): 134-143
燃煤机组脱硫浆液循环泵定频运行控制策略优化及节能分析
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高伟 , 刘明, 赵永亮, 王朝阳, 严俊杰
作者信息
  • 西安交通大学动力工程多相流国家重点实验室,陕西 西安 710049
  • 高伟(1994),男,博士研究生,主要研究方向为燃煤机组灵活清洁协同机理与优化研究,

通讯作者:

严俊杰(1967),男,教授,主要研究方向为热力系统节能与控制优化,
Control strategy optimization and energy saving analysis for slurry circulation pumps in fixed-frequency mode of desulfurization system in coal-fired power units
Wei GAO , Ming LIU, Yongliang ZHAO, Chaoyang WANG, Junjie YAN
Affiliations
  • State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
出版时间: 2024-10-25 doi: 10.19666/j.rlfd.202403056
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为消纳可再生能源大规模并网发电,燃煤发电机组的调峰调频任务剧增,长时间处于深度调峰和变负荷过程,导致湿法烟气脱硫系统的性能下降、厂用电率大幅上升。为此,建立了超超临界660 MW燃煤发电机组的动态模型及基于双膜理论的湿法脱硫系统动态模型;模拟了变负荷过程中不同工况点切换浆液循环泵时脱硫系统的性能,发现变负荷过程中浆液和烟气流量的精准匹配可使脱硫系统在满足SO2排放的前提下实现最小的电能消耗;进一步,获得了变负荷过程中浆液循环流量阶跃变化时SO2出口质量浓度的预测模型,提出了浆液循环泵定频运行优化控制策略,可实现变负荷过程中浆液与烟气流量的最佳匹配;最后,分析了优化控制策略的节能潜力。研究结果表明:75%THA~50%THA降负荷过程中,变负荷速率为1.0%、1.5%和2.0%Pe/min,分别可节能20.12%、21.52%和22.82%;而在升负荷过程中,分别可节能10.04%、9.90%和8.66%,变负荷过程中烟气流速变化的差异是造成降负荷和升负荷过程中节能潜力不同的根本原因。

湿法脱硫  /  浆液循环泵  /  燃煤机组  /  控制策略优化  /  节能分析

To accommodate grid-connected large-scale renewable power, coal-fired power plants need to undertake more peak shaving and frequency regulation tasks, so it will engage in the processes of deep peak shaving and load cycling for a long time. In this situation, the performance of wet flue gas desulfurization system (WFGD) will degradation and the auxiliary power consumption will increase significantly. To solve this problem, the dynamic model of an ultra-supercritical 660 MW coal-fired power unit and the dynamic model of the WFGD system based on the double-membrane theory are established. The performance of the desulfurization system is simulated when the slurry circulation pumps are switched under different operating conditions during the load cycling processes. It is found that the precise matching of slurry and flue gas during load cycling processes can achieve the minimum power consumption of the desulfurization system while meeting the SO2 emission standard. Furthermore, when the slurry circulation flowrate changes stepwise during load cycling processes, the prediction model of changes in SO2 mass concentration at the WFGD system outlet is obtained. An optimization control strategy for the slurry circulation pumps in fixed-frequency mode is proposed, which can achieve the best match between the slurry and flue gas during load cycling processes. Finally, the energy saving potential for the proposed control strategy is analyzed. When the load cycling rates are 1.0%, 1.5% and 2.0% Pe/min, the energy saving potential is 20.12%, 21.52% and 22.82% during loading down processes from 75% THA to 50% THA conditions, and that value will be 10.04%, 9.90% and 8.66% during loading up processes, respectively. The difference in flue gas flowrate during load cycling processes is found as a key factor causing the disparate of energy saving potential during loading down and loading up processes.

wet flue gas desulfurization  /  slurry circulation pumps  /  coal-fired power unit  /  control strategy optimization  /  energy saving analysis
高伟, 刘明, 赵永亮, 王朝阳, 严俊杰. 燃煤机组脱硫浆液循环泵定频运行控制策略优化及节能分析. 热力发电, 2024 , 53 (10) : 134 -143 . DOI: 10.19666/j.rlfd.202403056
Wei GAO, Ming LIU, Yongliang ZHAO, Chaoyang WANG, Junjie YAN. Control strategy optimization and energy saving analysis for slurry circulation pumps in fixed-frequency mode of desulfurization system in coal-fired power units[J]. Thermal Power Generation, 2024 , 53 (10) : 134 -143 . DOI: 10.19666/j.rlfd.202403056
为建设“清洁低碳,安全高效”的现代能源体系,我国亟需不断加强煤炭清洁高效利用[1-2],开发清洁高效的燃煤发电技术。但是,随着可再生能源的快速发展,而风电、太阳能发电具有间歇性和波动性,燃煤发电机组的调峰调频任务剧增,长时间处于深度调峰和变负荷过程[3-4]。燃煤机组负荷的频繁变化会造成烟气温度、流速等参数的波动,这将导致变负荷过程中烟气与氨气、浆液等物质的流量不匹配,从而对布置于锅炉尾部烟道的脱硝、除尘及脱硫系统的运行效率产生较大的影响[5-6]。因此,负荷的频繁波动势必会影响燃煤机组的清洁高效运行。
SO2是燃煤电站常见的污染物之一,对人类和环境均会产生较大的危害。我国制定了严格的燃煤电站SO2排放标准[7],要求SO2排放质量浓度不高于35 mg/m3。燃煤机组控制SO2排放的技术主要包括燃烧优化与烟气脱除技术。神经网络等先进智能算法被广泛应用于预测燃煤机组SO2的生成质量浓度[8-9],为锅炉燃烧优化提供研究基础。湿法烟气脱硫系统因其高效性和稳定性被广泛应用于燃煤电站,以控制SO2的排放[10]。在湿法脱硫系统中,石灰石浆液在浆液循环泵的作用下与烟气中的SO2接触并发生化学反应以脱除烟气中的SO2[11]。当前,研究工作者针对湿法脱硫的系统设计与运行优化[12-14]、脱硫废水[15-16]等展开了研究。
脱硫效率是评估湿法烟气脱硫系统运行状态的重要参数,陈雷等[17]采用钙基脱硫剂调控石灰石湿法脱硫系统的浆液pH值,以提高脱硫效率,结果表明该方法可大幅降低燃煤机组厂用电率。徐鹏等[18]以某电厂700 MW燃煤机组湿法烟气脱硫系统为研究对象,分析了影响其厂用电率的主要因素,提出通过改变配煤方式、优化浆液循环泵运行方式等降低湿法脱硫系统的厂用电率,全厂脱硫系统厂用电率可从1.038%降至0.733%。姜龙等[19]构建了湿法脱硫系统浆液品质、喷淋层堵塞的量化模型,并应用于某1 000 MW燃煤机组,结果表明该模型可较好预测浆液品质、喷淋层堵塞等重要信息。谈智玲等[20]通过在600 MW燃煤机组脱硫系统上进行不同负荷下的实验,获得了浆液pH值对脱硫效率、石膏品质的影响规律。刘云等[21]针对某电厂脱硫系统运行异常,产出石膏含水率达40%的现象,分析了燃煤机组湿法脱硫系统石膏含水率高的原因并提出相应的解决方案。
当燃煤机组处于变负荷过程时,石灰石浆液总是大幅高于所需值,造成大量的电能消耗。因此,湿法脱硫系统的运行经济性引起了广大学者的关注。范海东等[22]研究了燃煤机组变负荷过程中烟气和浆液的参数对湿法脱硫系统氧化过程的影响规律,提出了湿法脱硫系统氧化风机的优化运行方法,可有效降低氧化风机的电能消耗。王洁等[23]建立了湿法脱硫系统经济性分析模型,研究了煤种掺烧对湿法脱硫系统经济性的影响,可为燃煤机组掺烧硫量不同的煤提供一定的指导。李兆北等[24]基于非支配排序遗传和粒子群算法提出了湿法脱硫系统优化控制策略,可有效降低脱硫系统的度电成本。Zhao等人[25]建立了湿法脱硫系统的混合预测模型,研究了不同的浆液循环泵组合方式对脱硫系统经济性的影响规律。Shao等人[26]开展了燃煤机组变负荷过程浆液循环泵的频繁启停与脱硫系统经济性的权衡研究。Liu等人[27]基于经济模型预测控制方法,提出了兼顾SO2排放和系统运行经济性的湿法脱硫系统控制策略。
通过调整脱硫浆液循环泵的运行数量可有效应对燃煤机组的负荷变化。然而,变负荷过程中浆液循环泵的频繁启动与停止会造成浆液与烟气流量的不匹配。因此,亟需揭示变负荷过程中浆液循环流量阶跃变化对SO2出口质量浓度的影响机理,进而优化变负荷过程中浆液循环泵定频运行控制。本文建立了湿法脱硫系统动态模型,并与超超临界660 MW燃煤机组动态模型耦合。模拟了变负荷过程中浆液循环泵的启动与停止过程,建立了浆液循环流量阶跃变化对SO2出口质量浓度影响的预测模型,提出了浆液循环泵定频运行优化控制策略。与原有控制策略相比,该优化控制策略可实现较大的节能,具有良好的应用前景。
为开展变负荷过程中脱硫浆液循环泵控制策略优化研究,建立准确的燃煤机组和湿法脱硫系统动态模型是必需的。本节采用GSE仿真软件建立了超超临界660 MW燃煤机组动态模型,基于双膜理论建立了湿法脱硫系统动态模型,为研究浆液循环泵控制策略提供了基础。
本文基于质量、能量和动量守恒方程,采用GSE仿真软件建立了超超临界660 MW燃煤机组动态模型。
1)质量守恒方程
A(αρ)ft+FfZ=SfZ+ΓfZ
式中:t为时间,s;A为通流面积,m2αf为流动份额;ρf为流体的密度,kg/m3Ff为液体的质量流量,kg/s;Sf为工质流动源项,kg/s;Γf为工质相变项,kg/s。
2)能量守恒方程
A(αρh)ft=(hF)fZ+A(Γhsat+Q˙W)f+δSfhsrc
式中:hf为工质焓,kJ/kg;hsat为饱和状态的工质焓,kJ/kg;hsrc为源流体的焓,kJ/kg;Q˙为单位时间传热量,kW;W为功率,kW;δ为单位长度的流体源,kg/s。
3)动量守恒方程
dFfdt=αfAKu(dpdZ+ff-f+ff-w+Kuρfgδppump)+δSfvsrc
式中:Ku为单位换算系数,(MPa·m·s2)/kg;p压力,MPa;ff-f为流体与流体的流动摩擦因数;ff-w为液体与壁面的流动摩擦因数;g为重力加速度,m/s2δpump为泵的压力,MPa;vsrc流体的速度,m/s。
锅炉为一次中间再热四角切圆燃烧Π型炉。汽轮机系统为三缸四排汽,加热器系统包括4个高压加热器、4个低压加热器和1个除氧器。该动态模型已在之前的研究工作[28]中进行了验证。
图1展示了75%THA~50%THA降负荷和升负荷过程中机组功率的变化规律,变负荷速率分别为1.0%Pe/min、1.5%Pe/min和2.0%Pe/min。机组功率开始变化的时间为100 s,当达到目标负荷后,机组功率会快速达到稳定值。
SO2的生成与锅炉给煤量和燃料中硫元素的质量分数密切相关,文献[29]提出了燃煤机组SO2生成的机理模型,如式(4)所示。
CSO2=BFSt,ar(1q4)Vg(1ηSO3)×106
式中:Cso2为湿法脱硫系统入口SO2质量浓度,mg/m3B为燃煤机组给煤量,t/h;F为煤中硫元素转化为SO2的转化率;ηSO2为SO2转化为SO3的百分比,%;St,ar为煤中硫元素质量分数,%;Vg为烟气体积流量,m3/h;q4为机械不完全燃烧损失,%。
为验证SO2生成的机理模型,选取燃煤电站变负荷过程中的实际运行数据与模型计算的数据进行对比,具体如图2所示。结果表明,在升负荷和降负荷过程中,模拟值和实际运行数据的相对误差在10%之内,因此建立的SO2生成模型是可靠的。
脱硫塔是湿法烟气脱硫系统的核心设备,烟气中的SO2与石灰石浆液在脱硫塔内逆向流动并发生化学反应[30],从而脱除烟气中的SO2。本文基于双膜理论,依据文献[31]建立了SO2脱除的动态模型,其主要方程如下:
dvd,i(t)dt=g(ρsρg)ρs3ρg(vd,i(t)vg)ω4ρsRd
式中:t为时间,s;i为浆液循环泵的序号;g为重力加速度,m/s2ρsρg分别为石灰石浆液和烟气的密度,kg/m3vg为湿法脱硫系统入口烟气流速,m/s;vd,i(t)为t时刻浆液循环泵序号为i时的浆液液滴的流速,m/s;Rd为浆液液滴的半径,m;ω为阻力系数。
NODi(h,t)t=NODi(h,t)vd,i(t)h
式中:h为脱硫塔的高度,m;NODi(h,t)为t时刻高度为h时,序号为i的浆液循环泵单位体积的浆液液滴数量。
Cso2,g(h,t)t=vgCso2,g(h,t)hi=1N(NODi(h,t)Jso2(h,t)Sd)
式中:Cso2,g(h,t)为脱硫塔内气相中的SO2的浓度,mol/m3Jso2(h,t)为浆液液滴的SO2吸收速率,mol/(m2 s);N为浆液循环泵的个数;Sd为浆液液滴的表面积,m2
vd,i(t)NODi(Hi,t)=3Qslurry,i4πRd3Stower
式中:Stower为脱硫塔的横截面积,m2Hi为序号为i的浆液循环泵的喷淋高度,m;Qslurry,i为浆液循环泵的流量,m3/h。
Jso2(h,t)=klkg(h,t)kl+kg(h,t)Hso2/βpso2(h,t)
式中:k1kg分别为液侧和气侧的传质系数,mol/(s·Pa·m2);Hso2为SO2的亨利系数,mol/(m3·Pa);pSO2(h,t)为烟气中SO2的分压力,Pa;β为增强因子。
kg(h,t)=ShDso2,g(h,t)pso2(h,t)R(T+273.15)Rd
式中:Sh为舍伍德数;R为气体常数,J/(mol·℃);T为脱硫塔入口烟气温度,℃;Dso2,g(h,t)为气相中SO2的分子扩散系数,m2/s。
kl=λ1SpH+λ2
式中:SpH为浆液的pH值;λ1λ2为常量。
将模拟值与燃煤电站实际运行数据进行对比,以验证湿法脱硫系统动态模型的可靠性。图3对比了400~500 MW变负荷过程中SO2出口质量浓度的实际运行数据与模拟值,SO2出口质量浓度的最大相对误差在10%之内,因此建立的湿法脱硫系统动态模型是可靠的。
1)脱硫效率
ηSO2=CSO2,g-inCSO2,g-outCSO2,g-in×100%
式中:ηSO2为脱硫效率,%;CSO2,g-in为变负荷过程中湿法脱硫系统SO2的入口质量浓度,mg/m3CSO2,g-out为变负荷过程中湿法脱硫系统SO2的出口质量浓度,mg/m3
2)SO2出口浓度最大值
ΨSO2=max(CSO2,g-out)
式中:ΨSO2为燃煤机组变负荷过程中SO2出口质量浓度的最大值,mg/m3
3)浆液循环泵累计电量消耗
Φpumps=t1t2(Wpumps/3 600)dt
式中:t1为负荷开始变化的时间,s;t2为负荷达到稳定的时间,s;Wpumps为湿法脱硫系统浆液循环泵的耗功,kW;Φpumps为变负荷过程中浆液循环泵的累计电量消耗,kW·h。
本文研究的超超临界660 MW燃煤机组,浆液循环泵的负荷切换点分别为75%THA、50%THA和30%THA工况,不同工况下所需的浆液循环流量见表1。在100%THA、75%THA、50%THA和30%THA工况下,总的浆液循环流量分别为46 726、36 404、25 724、13 058 m3/h。不同喷淋高度的浆液循环泵分别记为A、B、C和D,其喷淋高度分别为21.8、23.3、24.8、26.8 m,设计流量分别为13 058、12 666、10 680、10 322 m3/h。
图4给出了变负荷过程中湿法脱硫系统的原有控制策略,其中浆液循环泵的运行数量依据燃煤机组的负荷指令进行调节,以应对机组负荷的频繁变化。在100%THA工况时,浆液循环泵D、C、B和A均处于运行状态。当机组负荷从100%THA降低到30%THA时,浆液循环泵D、C和B依次停运,可保证在SO2排放满足要求的前提下降低浆液循环泵的电量消耗。当燃煤机组在75%THA工况运行时,脱硫浆液循环泵A、B和C保持运行。当燃煤机组在50%THA负荷运行时,浆液循环泵A和B处于运行状态即可满足SO2排放的要求,停止浆液循环泵C可降低湿法脱硫系统的电量消耗。因此,在75%THA~50%THA变负荷过程中需要对浆液循环泵进行切换,即启动或停止浆液循环泵C。
在浆液循环泵采用定频运行原有控制策略时,75%THA~50%THA变负荷过程中SO2出口质量浓度的变化如图5所示。在该变负荷过程中,燃煤机组的功率变化如图1所示。当燃煤机组从75%THA降低到50%THA工况,机组负荷达到稳定值时,停止浆液循环泵C运行。因此,SO2出口质量浓度随着负荷的降低不断降低,直到机组负荷达到稳定值后,SO2出口质量浓度迅速提高,然后逐渐降低为稳态值。在50%THA到75%THA升负荷过程中,当负荷开始变化时,浆液循环泵C启动运行。因此SO2出口质量浓度在负荷开始变化时迅速降低,之后随着负荷的升高逐渐升高。
在不同工况点切换浆液循环泵会对脱硫系统的性能产生不同的影响。本节以变负荷速率为1.5%Pe/min为例,模拟了变负荷过程中不同工况点切换浆液循环泵时脱硫系统的性能。图6a)展示了75%THA~50%THA降负荷过程,分别在70%THA、65%THA、60%THA和55%THA工况点停止浆液循环泵C时SO2出口质量浓度的变化。当浆液循环泵C在70%THA工况停止运行时,SO2出口质量浓度最大值超过了燃煤电站要求的排放标准,这是因为在70%THA工况时SO2入口质量浓度较高,因此当浆液循环泵C停止运行时SO2出口质量浓度增加量较大,且70%THA工况时SO2出口质量浓度值相对较高。在65%THA、60%THA和55%THA工况停止浆液循环泵C时,均可满足燃煤电站的要求。
图6b)展示了50%THA~75%THA升负荷过程,分别在55%THA、60%THA、65%THA和70%THA工况启动浆液循环泵C时SO2出口质量浓度的变化。在55%THA工况启动浆液循环泵C时,SO2出口质量浓度最大值低于35 mg/m3。当浆液循环泵C在60%THA、65%THA和70%THA工况启动时,由于浆液循环泵C没有及时启动运行,浆液循环流量和烟气流量无法匹配,使得SO2排放超过35 mg/m3,无法满足燃煤电站的要求。
图7图8分别展示了75%THA~50%THA变负荷过程,在不同工况点切换浆液循环泵时SO2出口质量浓度的最大值和浆液循环泵的累计电量消耗。降负荷过程中:在70%THA、65%THA、60%THA和55%THA工况停止浆液循环泵C时,SO2出口质量浓度的最大值分别为39.69、26.17、17.86、15.70 mg/m3,浆液循环泵的累计电量消耗分别为548.28、593.88、638.14、681.06 kW·h;随着浆液循环泵C停止运行的工况点推迟,SO2出口质量浓度的最大值降低,但是浆液循环泵的累计电量消耗增加;当浆液循环泵C在65%THA工况停运时,SO2出口质量浓度不会出现瞬态超标的现象,而浆液循环泵的累计电量消耗比在55%THA工况切换浆液循环泵时减少了87.18 kW·h。
升负荷过程中:在55%THA、60%THA、65%THA和70%THA工况启动浆液循环泵C时,SO2出口质量浓度的最大值分别为32.12、42.32、61.19、79.53 mg/m3,浆液循环泵的累计电量消耗分别为694.04、649.41、607.01、564.51 kW·h;随着浆液循环泵C启动运行的工况点推迟,SO2出口质量浓度最大值提高,但是浆液循环泵的累计电量消耗减小;当浆液循环泵的启动工况为55%THA时,尽管与浆液循环泵C启动工况为70%THA相比,浆液循环泵的累计电量消耗增加了129.53 kW·h,但是SO2出口质量浓度可以控制在35 mg/m3以下。
由2.2节可知,在恰当的工况点切换浆液循环泵时可实现浆液与烟气流量的最佳匹配,在满足SO2排放的前提下实现浆液循环泵的最小电能消耗。然而,在不同工况点切换浆液循环泵时,由于浆液与烟气流量在变负荷过程中的不匹配,可能会造成SO2出口质量浓度的瞬态超标。因此,建立变负荷过程中浆液流量阶跃变化对SO2出口质量浓度影响的预测模型是进行浆液循环泵定频运行控制策略优化的关键。
以脱硫效率的定义式为基础,获得了变负荷过程中SO2出口质量浓度的表达式,如式(15)所示。
Cso2,g-out=Cso2,g-in(1ηso2)
进而,假设在变负荷过程中切换浆液循环泵时,SO2入口质量浓度保持不变,脱硫效率的变化与浆液循环流量的变化成正比,而其他影响脱硫效率的因素如浆液pH值、烟气流速等保持不变。据此可获得变负荷过程中浆液循环流量阶跃变化时SO2出口质量浓度变化的预测模型,如式(16)所示。
ΔCso2,g-out=k1Cso2,g-inηso2ΔQslurryQslurry-all
式中:ΔQslurry为变负荷过程中浆液循环流量的阶跃变化量,m3/h;Qslurry-all为浆液循环流量阶跃变化时总的浆液循环流量,m3/h;ΔCso2,g-out为浆液循环流量阶跃变化时SO2出口质量浓度的变化量,mg/m3
基于变负荷过程浆液循环流量阶跃变化对SO2出口质量浓度影响的预测模型,提出了变负荷过程中浆液循环泵定频运行优化控制策略如图9所示。
在变负荷过程中,SO2入口质量浓度、SO2出口质量浓度、脱硫效率、机组负荷指令和总的浆液循环流量均可实时获得。当变负荷过程中浆液循环泵启动或停止运行时,根据SO2入口质量浓度、脱硫效率和总的浆液循环流量,计算出SO2出口质量浓度变化量的预测值,结合当前SO2出口质量浓度值即可获得浆液循环泵切换时SO2出口质量浓度的预测值。燃煤电站要求SO2排放不高于35 mg/m3,因此在优化控制策略中,SO2出口质量浓度的设定值为30 mg/m3,预留5 mg/m3以应对模型的计算误差。降负荷过程中,当浆液循环泵停止运行时,SO2出口质量浓度的预测值为30 mg/m3时即可停运相应的浆液循环泵,使得浆液与烟气流量达到最佳匹配值,在满足SO2排放的前提下实现浆液循环泵累计电量的最低消耗。升负荷过程中,当SO2出口质量浓度达到30 mg/m3时,启动相应的浆液循环泵即可实现浆液与烟气流量的最佳匹配。
在75%THA~50%THA变负荷过程中,采用优化控制策略后,SO2出口质量浓度的变化如图10所示。SO2出口质量浓度的设定值为30 mg/m3。降负荷过程中,可以发现在不同的变负荷速率下均可实现浆液循环泵在最佳工况点切换。当浆液循环泵停止运行时,SO2出口质量浓度的最大值保持在30 mg/m3。在升负荷过程中,采用优化控制策略后也实现了浆液与烟气流量的最佳匹配。
在75%THA~50%THA变负荷过程中,原有控制策略和优化控制策略下浆液循环泵的累计电量消耗如图11所示。由图11可知,在相同的变负荷速率下,采用优化控制策略后浆液循环泵的累计电量消耗明显降低。图12展示了在不同变负荷速率下,采用优化控制策略后浆液循环泵的节能潜力。
图12可知:降负荷过程中,变负荷速率分别为1.0%Pe/min、1.5%Pe/min和2.0%Pe/min时,分别可节能20.12%、21.52%和22.82%;而在升负荷过程中,分别可节能10.04%、9.90%和8.66%。
当变负荷速率相同时,降负荷过程的节能潜力明显高于升负荷过程。降负荷过程的节能潜力随着变负荷速率的增加而增加,而升负荷过程的节能潜力随着变负荷速率的增加而减小。这是因为变负荷过程中锅炉给煤量会出现超调现象,使得降负荷过程中烟气流速低于稳态值,而升负荷过程中烟气流速高于稳态值,其偏差随着变负荷速率的提高而增加。因此在降负荷过程中,随着变负荷速率的提高,浆液循环泵的切换工况点会推迟,使得节能潜力提高;而在升负荷过程中,随着变负荷速率的提高,浆液循环泵需要提前启动运行,节能潜力减小。
本文采用GSE仿真软件建立了超超临界660 MW燃煤机组动态模型,并基于双模理论建立了湿法烟气脱硫系统动态模型。研究了75%THA~ 50%THA变负荷过程中在不同工况点切换浆液循环泵时脱硫系统的性能。获得了变负荷过程浆液循环流量阶跃变化对SO2出口质量浓度影响的预测模型。提出了浆液循环泵定频运行优化控制策略,获得了该优化控制策略的节能潜力,主要结论如下。
1)在75%THA~50%THA变负荷过程中,获得了浆液循环泵采用定频运行原有控制策略时SO2出口质量浓度的变化规律,发现变负荷过程中SO2出口质量浓度最大值远低于燃煤电站要求值,因此,优化浆液循环泵切换的工况点可以在满足SO2排放的前提下实现节能。进一步地,模拟了不同工况点切换浆液循环泵时脱硫系统的性能,获得了在不同工况点切换浆液循环泵时SO2出口质量浓度的最大值和浆液循环泵的累计电量消耗。降负荷过程中,在70%THA、65%THA、60%THA和55%THA工况点停止浆液循环泵C时,SO2出口质量浓度的最大值分别为39.69、26.17、17.86、15.70 mg/m3,浆液循环泵的累计电量消耗分别为548.28、593.88、638.14、681.06 kW·h;升负荷过程中,在55%THA、60%THA、65%THA和70%THA工况启动浆液循环泵C时,SO2出口质量浓度的最大值分别为32.12、42.32、61.19、79.53 mg/m3,浆液循环泵的累计电量消耗分别为694.04、649.41、607.01、564.51 kW·h。
2)建立了变负荷过程中浆液循环流量阶跃变化时SO2出口质量浓度变化的预测模型,提出了浆液循环泵定频运行优化控制策略。浆液循环泵切换时SO2出口质量浓度变化量的预测值,可由脱硫效率、SO2入口质量浓度和总的浆液循环流量实时计算获得。依据SO2出口质量浓度的预测值精准控制浆液循环泵的切换,可实现变负荷过程中浆液和烟气流量的优化匹配,从而实现最小的浆液循环泵电能消耗。进而,分析了75%THA~50%THA变负荷过程中优化控制策略的节能潜力。降负荷过程中,变负荷速率分别为1.0%Pe/min、1.5%Pe/min和2.0%Pe/min,分别可节能20.12%、21.52%和22.82%;升负荷过程中,分别可节能10.04%、9.90%和8.66%。变负荷过程中锅炉给煤量超调引起的烟气流速的变化差异,是造成降负荷和升负荷过程中节能潜力不同的根本原因。
  • 国家重点研发计划(2022YFB4100402)
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2024年第53卷第10期
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doi: 10.19666/j.rlfd.202403056
  • 接收时间:2024-03-23
  • 首发时间:2026-03-05
  • 出版时间:2024-10-25
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  • 收稿日期:2024-03-23
基金
National Key R&D Program of China(2022YFB4100402)
国家重点研发计划(2022YFB4100402)
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    西安交通大学动力工程多相流国家重点实验室,陕西 西安 710049

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严俊杰(1967),男,教授,主要研究方向为热力系统节能与控制优化,
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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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