Article(id=1215700941966328044, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1215700941538509036, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202312183, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1703433600000, receivedDateStr=2023-12-25, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1767775291196, onlineDateStr=2026-01-07, pubDate=1721836800000, pubDateStr=2024-07-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1767775291196, onlineIssueDateStr=2026-01-07, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1767775291196, creator=13701087609, updateTime=1767775291196, updator=13701087609, issue=Issue{id=1215700941538509036, tenantId=1146029695717560320, journalId=1210938733613449225, year='2024', volume='53', issue='7', pageStart='1', pageEnd='158', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1767775291094, creator=13701087609, updateTime=1767775458121, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1215701642159243949, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1215700941538509036, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1215701642159243950, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1215700941538509036, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=45, endPage=52, ext={EN=ArticleExt(id=1215700942163460333, articleId=1215700941966328044, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Comprehensive analysis and operation optimization of a system integrated with ground-source heat pump and solar photovoltaic/thermal component, columnId=1215700879274070743, journalTitle=Thermal Power Generation, columnName=New energy power generation technology, runingTitle=null, highlight=null, articleAbstract=

The coupling of photovoltaic-thermal utilization and ground source heat pump is expected to use photovoltaic waste heat to avoid performance degradation of the heat pump, and also to use photovoltaic electricity to partially meet the energy demand of the heat pump, which has a broad prospect. A simulation model of the integrated system of low-concentration photovoltaic-thermal and ground source heat pump is constructed, and the operational performance of the system is analyzed. Moreover, the key influence laws of the life cycle cost of the system are also analyzed. The research results show that, the annual solar-to-electrical efficiency of the integrated system reaches 17.73%, which is 9.58% higher than that of the single operation system. The photovoltaic waste heat of the photovoltaic-thermal device can effectively reduce the soil temperature decay, and the long-term operation performance of the heat pump is 16.58% higher than that of the reference system. The operation and maintenance cost of the system decreases with the increase of the scale of the photovoltaic-thermal device and the ground source heat pump, while the investment cost increases accordingly. The total life cycle cost of the system decreases at first and then increases with the increase of the scale. Taking the life cycle cost as the objective function, economic optimization of the system based on the particle swarm algorithm is carried out, and the life cycle cost reduces by 31.52% compared with the design of the maximum scale capacity. The relevant results can provide theoretical reference for optimal design of the photovoltaic-thermal-ground source heat pump integrated system.

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将光伏/光热利用与地源热泵相互耦合,有望利用光伏余热避免热泵性能衰减,还可利用光伏电力部分满足热泵电能需求,前景广阔。构建了低倍聚光光伏/光热与地源热泵的集成系统运行仿真模型,对系统开展了运行性能分析;并进一步研究了系统全生命周期成本的关键影响规律。结果表明:集成系统光伏年均发电效率达17.73%,较单一运行系统提升9.58%,光伏/光热装置的光伏余热可有效减少土壤温度衰减,热泵长时运行性能较参比系统提升16.58%;系统运维成本随光伏/光热装置和地源热泵规模增加而减少,投资成本随之增加,总的全生命周期成本随规模增加先减后增;以全生命周期成本为目标函数,基于粒子群算法开展系统经济性优化,全生命周期成本较最大规模容量设计降低31.52%。相关结论可为光伏/光热与地源热泵集成系统优化设计提供理论参考。

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王瑞林(1993),男,博士,副教授,主要研究方向为多能源系统互补集成、光伏光热综合利用,
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石天庆(1971),男,硕士,正高级工程师,主要研究方向为地热能利用及清洁供暖技术,

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石天庆(1971),男,硕士,正高级工程师,主要研究方向为地热能利用及清洁供暖技术,

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Nanjing: Nanjing University, 2021: 1., articleTitle=Study on characteristics and development suitability of shallow geothermal energy in Danyang, refAbstract=null)], funds=[Fund(id=1215700951931994697, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1215700941966328044, awardId=CHDKJ22-01-23, language=EN, fundingSource=Key Science and Technology Program of China Huadian Corporation(CHDKJ22-01-23), fundOrder=null, country=null), Fund(id=1215700952036852303, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1215700941966328044, awardId=CHDKJ22-01-23, language=CN, fundingSource=中国华电集团重点科技项目(CHDKJ22-01-23), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1215700944147366159, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1215700941966328044, xref=1., ext=[AuthorCompanyExt(id=1215700944151560465, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1215700941966328044, 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低倍聚光光伏/光热与地源热泵集成系统综合分析及优化
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石天庆 1 , 商永强 1 , 刘媛媛 1 , 仲焕文 2 , 王瑞林 2 , 李文甲 3 , 卢勇宽 1
热力发电 | 新能源发电技术专题 2024,53(7): 45-52
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热力发电 | 新能源发电技术专题 2024, 53(7): 45-52
低倍聚光光伏/光热与地源热泵集成系统综合分析及优化
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石天庆1 , 商永强1, 刘媛媛1, 仲焕文2, 王瑞林2 , 李文甲3, 卢勇宽1
作者信息
  • 1.华电郑州机械设计研究院有限公司,河南 郑州 450046
  • 2.南京师范大学能源与机械工程学院,南京 210023
  • 3.天津大学机械工程学院,天津 300350
  • 石天庆(1971),男,硕士,正高级工程师,主要研究方向为地热能利用及清洁供暖技术,

通讯作者:

王瑞林(1993),男,博士,副教授,主要研究方向为多能源系统互补集成、光伏光热综合利用,
Comprehensive analysis and operation optimization of a system integrated with ground-source heat pump and solar photovoltaic/thermal component
Tianqing SHI1 , Yongqiang SHANG1, Yuanyuan LIU1, Huanwen ZHONG2, Ruilin WANG2 , Wenjia LI3, Yongkuan LU1
Affiliations
  • 1.Huadian Zhengzhou Mechanical Design Institute Company Limited, Zhengzhou 450046, China
  • 2.School of Energy and Mechanical Engineering, Nanjing Normal University, Nanjing 210023, China
  • 3.School of Mechanical Engineering, Tianjin University, Tianjin 300350, China
出版时间: 2024-07-25 doi: 10.19666/j.rlfd.202312183
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将光伏/光热利用与地源热泵相互耦合,有望利用光伏余热避免热泵性能衰减,还可利用光伏电力部分满足热泵电能需求,前景广阔。构建了低倍聚光光伏/光热与地源热泵的集成系统运行仿真模型,对系统开展了运行性能分析;并进一步研究了系统全生命周期成本的关键影响规律。结果表明:集成系统光伏年均发电效率达17.73%,较单一运行系统提升9.58%,光伏/光热装置的光伏余热可有效减少土壤温度衰减,热泵长时运行性能较参比系统提升16.58%;系统运维成本随光伏/光热装置和地源热泵规模增加而减少,投资成本随之增加,总的全生命周期成本随规模增加先减后增;以全生命周期成本为目标函数,基于粒子群算法开展系统经济性优化,全生命周期成本较最大规模容量设计降低31.52%。相关结论可为光伏/光热与地源热泵集成系统优化设计提供理论参考。

光伏/光热  /  地源热泵  /  联合供暖系统  /  全生命周期  /  成本分析

The coupling of photovoltaic-thermal utilization and ground source heat pump is expected to use photovoltaic waste heat to avoid performance degradation of the heat pump, and also to use photovoltaic electricity to partially meet the energy demand of the heat pump, which has a broad prospect. A simulation model of the integrated system of low-concentration photovoltaic-thermal and ground source heat pump is constructed, and the operational performance of the system is analyzed. Moreover, the key influence laws of the life cycle cost of the system are also analyzed. The research results show that, the annual solar-to-electrical efficiency of the integrated system reaches 17.73%, which is 9.58% higher than that of the single operation system. The photovoltaic waste heat of the photovoltaic-thermal device can effectively reduce the soil temperature decay, and the long-term operation performance of the heat pump is 16.58% higher than that of the reference system. The operation and maintenance cost of the system decreases with the increase of the scale of the photovoltaic-thermal device and the ground source heat pump, while the investment cost increases accordingly. The total life cycle cost of the system decreases at first and then increases with the increase of the scale. Taking the life cycle cost as the objective function, economic optimization of the system based on the particle swarm algorithm is carried out, and the life cycle cost reduces by 31.52% compared with the design of the maximum scale capacity. The relevant results can provide theoretical reference for optimal design of the photovoltaic-thermal-ground source heat pump integrated system.

photovoltaic/photothermal  /  ground source heap pump  /  hybrid heating system  /  whole life cycle  /  cost analysis
石天庆, 商永强, 刘媛媛, 仲焕文, 王瑞林, 李文甲, 卢勇宽. 低倍聚光光伏/光热与地源热泵集成系统综合分析及优化. 热力发电, 2024 , 53 (7) : 45 -52 . DOI: 10.19666/j.rlfd.202312183
Tianqing SHI, Yongqiang SHANG, Yuanyuan LIU, Huanwen ZHONG, Ruilin WANG, Wenjia LI, Yongkuan LU. Comprehensive analysis and operation optimization of a system integrated with ground-source heat pump and solar photovoltaic/thermal component[J]. Thermal Power Generation, 2024 , 53 (7) : 45 -52 . DOI: 10.19666/j.rlfd.202312183
据国际能源署(IEA)2022年发布的数据,建筑运行所需能耗已占全球总能耗的30%,相应的碳排放则占全球总排放量的27%[1]。据IEA预测,建筑运行所需能耗的绝对数值仍会快速增加,2050年将会增长至160×109 GJ[2]。地源热泵能效高、污染少,节能潜力大,被认为是满足建筑冷热需求的一种重要途径[3],在世界范围内得到了广泛应用。实际运行中,地源热泵供暖时从土壤中抽取热量;而在供冷季时,则向土壤中释放热能。对于大多数区域,热泵从土壤中抽取和向土壤中释放的热能并不平衡。尤其是供暖需求较为旺盛的地区,长时间运行土壤温度逐渐降低,地源热泵性能也因此下降[4]。这种“热不平衡”引发的长时运行性能衰减,阻碍了土壤源热泵技术的广泛应用[5]
近年来,太阳热能辅助地源热泵受到越来越多关注,相较于传统单一运行地源热泵系统,太阳能的引入可以避免“热能不平衡”,提高热泵长期运行性能,减少化石能源消耗。Kjellsson等人[6]对比了平板太阳能集热器耦合土壤源热泵系统的不同运行方式。Rad等人[7]以加拿大多伦多某典型建筑为供能对象,研究发现引入太阳能可减少地热换热器用量,减少投资成本。Calise等人[8]研究发现,太阳能辅助地源热泵耦合系统的热效率和电效率可分别高达40%和10%。需说明的是,引入太阳热能可以有效提升地源热泵系统性能。但是在该系统中,太阳能仅以低温热能形式被利用,从品位角度分析,存在较大的可用能损失;另一方面,太阳能平板集热仅能提供部分热能,地源热泵所需电能全由外界供给,会产生额外的碳排放和化石能源消耗。
在太阳能光伏/光热(PV/T)利用形式中,光伏将太阳辐照的短波波段能量转化为电能,剩余的辐照能量则被转化为热能并被光伏背板的流体吸收[9]。这部分热能可用于提供生活热水[10],并带动发电循环[11],可有效提升装置对于太阳能的综合利用率和经济性[12]。将PV/T技术与地源热泵相耦合,PV/T面板产生的电能可部分满足热泵用电需求,其余热也可用于缓解“热不平衡”引起的热泵性能衰退。相较于太阳热能与地源热泵直接耦合,PV/T技术与地源热泵在能量的互补性上优势明显。金满等[13]研究表明,PV/T耦合地源热泵系统的热泵性能系数较单一热泵可提升10.3%,长时运行土壤温度降幅仅为8.0%。刘仙萍等[14]研究表明,相较于平板集热器-地源热泵联合系统,PV/T耦合地源热泵系统的全年运行能耗可降低约50%,而不同PV/T组件面积下,热泵机组季节能效比均随地埋管长度增加而小幅度上升,但增幅并不显著[15]
现有研究已较好地揭示了光伏/光热—地源热泵集成系统的性能优势,但是在其容量配置和经济性优化方面涉及较少。本文构建了光伏/光热-地源热泵集成系统土壤源热泵的集成系统运行仿真模型,分析了集成系统中光伏/光热和地源热泵的全年运行性能,对比参比系统揭示了系统性能优势;进一步构建系统全生命周期成本分析模型,分析了系统关键变量对成本的影响规律,并基于粒子群智能算法,完成了系统容量配置的经济性优化。本研究结论可为光伏/光热-地源热泵集成系统优化设计提供一定参考。
图1为低倍聚光光伏/光热(LCPV/T)-地源热泵集成系统示意。LCPV/T装置中的聚光器聚焦太阳辐射于光伏电池板之上,光伏电池板吸收太阳能转化为电力,用于满足热泵或者住宅的用电需求。源自地埋管的换热工质吸收光伏电池板余热并将之蓄存于土壤之中。受益于工质冷却,光伏电池板温度降低,其发电效率也因之提升。地源热泵在供热季和制冷季的运行模式不同:供热季时,图1中换热器HEX1和HEX2分别作为蒸发器和冷凝器运行,吸收土壤中的热量并供给建筑物;制冷季时,土壤源热泵以制冷模式运行,热泵吸收建筑中的热量并储存于土壤中,HEX1和HEX2则分别发挥冷凝器和蒸发器的功能。需说明的是,本文暂不考虑流体输运、聚光跟踪等其他的伴生耗能影响。
LCPV/T的能量平衡式为:
IDNIcosθKendAa=Qopt,loss+EPV+Qdis, heat
式中:IDNIAa分别为直射辐射强度和LCPV/T装置的有效开口面积;θ为太阳辐射的入射角;Kend为端部损失影响系数;Qopt,lossEPVQdis,heat分别为LCPV/T的光学损失、发电量和热量损失。入射角θ可根据LCPV/T装置朝向、具体地理位置和当地时间等关键参数获得,计算方法参考文献[16]。Kend具体数值随辐照入射角变动而变动,具体计算方法参考文献[17]。
聚光过程中的光学损失计算公式为:
Qopt,loss=IDNIcosθAa(1ηopt)
式中:ηopt为光学效率,考虑洁净度、镜面反射损失等因素,取值90%[11]
发电量EPV和散热损失Qdis,heat计算公式为:
EPV=IDNIcosθAaηoptηPV
Qdis,heat=IDNIcosθAaηopt(1ηPV)
ηpv=JscVocFFF/QPV
式中:ηpv为光伏电池的发电效率;Jsc为短路电流;Voc为开路电压;FFF为填充因子。
短路电流Jsc的计算公式为:
Jsc=APVCpvηoptλLλHqλI(λ)EEQEhcdλ
式中:APVCPV分别为光伏电池的面积和聚光比;q=1.63×10–19 C为电子电荷;h=6.63×10–43 J·s和c=3.0×108 m/s分别为普朗克常数和光速;EEQE为光伏电池的量子效率。单晶硅光伏电池的量子效率和波长之间的关系参考文献[18]。
开路电压Voc的计算公式为[19]
Voc=nkBTpvqln(JscJo+1)
式中:kB=1.38×10-23 J/K为玻尔兹曼常数;TPV为光伏电池工作温度;Jo为光伏电池的饱和电流;n为理想系数。
饱和电流Jo的计算公式为[19]
Jo=1.5×105APVexp(EgnkBTpv)
式中:Eg为光伏电池的带隙能,计算公式为[20]
Eg=Eg0αTpv2/(Tpv+β)
式中:Eg0为0 K下的带隙能;αβ为温度系数。对于单晶硅光伏电池,Eg0=1.155 7 eV,αβ的值分别为7.021×10-4和1 108[20]
填充因子FFF的计算方法为[21]
FFF=[ζocln(ζoc+0.72)]/(ζoc+1)
ζoc=Vocq/(nkBTPV)
根据式(8)—式(11)发现,光伏电池板的温度TPVηPV值至关重要。稳定状态下的TPV值可从光伏电池板的散热量Qdis,heat与光伏电池板向环境或工作流体的热量损失Qpv,heatloss之间的能量平衡中获得。当光伏电池板有流体工质冷却时,TPV值可视为光伏板中工作流体的平均温度。当光伏电池板在没有冷却流体的情况下运行时,其数值可通过计算为[22]
QPV,heatloss=[α1(TPVTamb)+α2(TPVTamb)4]Aa
地源热泵在制热和制冷模式下的能量平衡式分别为:
Qbuildingcool=QgroundcoolEheatpump=(CCOPcool1)Eheatpump
Qbuildingheat=Qgroundheat+Eheatpump=(CCOPheat+1)Eheatpump
式中:下标“heat”和“cool”分别表示供暖和制冷模式;Qbuilding为建筑物的制冷或供暖负荷;Wheatpump为热泵的耗电量;Qground为从地面提取(供暖模式)或注入(制冷模式)的热能;CCOP为热泵在不同模式下的性能系数。
本研究将制冷和制热模式下的额定CCOPCCOPcool,0CCOPheat,0)分别设定为3.92和4.96。根据Gorden等人[23]及刘媛媛[24]相关研究,变工况条件下,地源热泵的CCOP计算公式为:
CCOP1=(L+0.667)Tin,condTout,eva1.001L0.651
式中:L为热泵的负载率,即实际负荷和核定负荷的比值;Tin,condTout,eva则分别为冷凝器入口流体和蒸发器出口流体的温度,单位为绝对温标。
铺设在地下的地埋管换热器用于实现流体工质与土壤之间的热量交换。工作流体与土壤之间交换的热能Qground可据下式计算:
Qground=LHEX(TgroundTmean,fluid)/RHEX
式中:LHEX为地热交换器的管子总长度;TgroundTmean,fluid分别为地表温度和地热交换器内工作流体的平均温度;RHEX为地埋管换热器单位长度的等效热阻,取值0.646 9 K/(W·m)[25]
LHEX值可根据Qground值和Tground与额定条件下的Tmean,fluid温差确定。土壤温度Tground可通过下式计算:
Tground=T0,ground+Qgrounddt/(ρgroundVgroundcpground)
式中:T0,ground为初始土壤温度;ρground=2 200 kg/m3[26]cpground=2.0 kJ/(kg·K)[25]分别为土壤的平均密度和热容量;Vground为计算过程中选定的土壤体积。选定土壤体积即假定存在热量传递的远端边界,边界外土壤温度不受影响[27]。土壤远端边界随时间推移变动,具体计算方法参考文献[4]。
本研究选择位于中国北部(北纬:40.1oN;西经:117.4oW)的一栋酒店建筑作为能源供应对象。酒店为南北朝向双层建筑,总建筑面积为1 300 m2,实际供暖/供冷计算面积为1 208 m2;建筑南北向窗墙比分别为0.32和0.24,东西向窗墙比分别为0.10和0.08;外墙、窗户及屋顶的传热系数分别取为0.27、2.50、0.80 W/(m2·K)。
基于该酒店各项参数,于Energy Plus软件内构建其用能模型,并进行全年逐时冷热负荷需求计算(图2)。结果显示,该酒店全年最大的供冷负荷和供热负荷功率需求分布为123.98、128.77 kW。为满足建筑物用能最大负荷,地源热泵采暖和制冷额定功率均设为130 kW,LCPV/T装置有效开口面积设为100 m2。根据所选的额定负荷、地埋管换热器换热系数以及供暖、供冷季节的额定性能系数CCOP,设定地埋管换热器总长度为3 455.06 m,地埋管换热器深度为100 m,确定地埋管换热器钻孔数量为35个。
在LCPV/T-地源热泵集成系统(简称集成系统)中,LCPV/T装置与地源热泵紧密结合,协同运行。为展示该系统优势,选取平板光伏和地源热泵各自独立运行系统作为参比系统。参比系统各装置选型参数与集成系统一致,平板光伏装置的光伏余热不输送至土壤。
基于所编制模型,开展系统全年运行模拟,结果表明:考虑光伏直流转交流电过程中的能量损耗(逆变器效率取值92.3%[28]),集成系统LCPV/T装置年发电量为31.36 MW·h,可满足热泵运行电力需求的61.27%,此外,年太阳能发电效率达到17.73%;而参比系统的光伏年发电量和相应发电效率分别为28.32 MW·h和16.11%,较集成系统低9.58 %。造成这一差异的主要原因有2个:1)低倍聚光光伏电池聚光比较高,光伏发电效率更高;2)低倍聚光光伏电池得到了较好的冷却,电池板工作温度较低,所以光伏余热的负面效应得以避免。
集成系统与参比系统逐日的光伏光热装置发电量差异EPV-EPVsep的日发电量差异及光伏的工作温度如图3所示。由图3可见:每日发电量差异在–3.89~44.91 kW·h;大多数时间内,集成系统的LCPV/T发电量高于参比系统,尤其是第144天到第258天电量优势更明显。这主要是因为这段时间集成系统LCPV/T面板由地面热交换器的工作流体冷却,其温度低于工作在高环境温度的平板光伏,再叠加聚光光伏高聚光比的效率优势,发电量明显较高。相反,当环境温度很低时,参比系统平板光伏的工作温度可能会很低,因此其发电效率会相对较高如图3中50天前后。
集成系统和参比系统的地源热泵均可满足大楼的供暖和制冷负荷,2个系统的年耗电量分别为56.11、56.28 MW·h,相应平均CCOP也非常接近,热泵供冷平均CCOP均为3.08,集成系统和参比系统供热平均CCOP分别为4.28、4.26。性能接近的原因是2个系统的热泵工作条件非常接近,供暖季节CCOP的微小差异是由于地面温度差异造成的。2个系统地温年变化如图4所示。由图4可见:集成系统年末的地温与年初的地温非常接近;然而,运行1年后,参比系统的地面温度降低了0.21 K。
全年2个系统热泵净热能流量变化如图5所示。由图5可见:供暖季集成系统的热能净流出量低于参考系统;制冷季节集成系统的热能净流入量明显高于参考系统。这是由于集成系统光伏光热装置的光伏余热通过工质流体输送至土壤。
由上文可见,集成系统光伏/光热装置性能优势明显,但集成系统和参比系统地源热泵性能接近。故进行长时模拟,对比连续运行20年后2个系统地源热能的性能差异。集成系统和参比系统地源热泵在第20年的逐日耗电量如图6所示。由图6可以发现:供冷季节2个系统耗电量非常接近;而在采暖季,参比系统的耗电量比集成系统高8.09 MW·h。参比系统在供暖季平均CCOP仅为3.57,即由于长期运行导致的土壤温度变化,参比系统热泵性能衰减了16.58%。
2个系统在连续运行20年后地源热泵性能出现差异的原因在于土壤温度变化。20年间2个系统的土壤温度的变化情况如图7所示。由图7可以看出,在这段时间中,参比系统土壤温度降低5.48 K,而光伏/光热—地源热泵系统土壤温度基本保持不变(偏差小于0.20 K)。
全生命周期成本CLc是热泵系统常用经济性评价指标[29],本研究亦基于此开展经济性分析。CLc主要包含投资、运维以及回收3部分内容,具体计算公式为:
CLc=kCRFNyearCinvest+CO&MCRe
式中:Cinvest为系统投资成本;Nyear为系统运行年限,取值20;kCRF为考虑资金利率的投资年折合系数,取值0.102[30]CO&M为系统运行费用;CRe为系统设备回收对应的剩余价值。
Cinvest主要考虑热泵、地埋管换热器以及光伏光热装置,具体计算公式为:
Cinvest=PPV/TAa+PpumpQpump,rate+PHEXLHEX
式中:PPV/T为单位开口面积光伏/光热组件投资成本,取值600元/m2[31]Ppump为地源热泵单位功率投资成本,取值600元/kW[32]PHEX为地埋管换热器单位深度投资成本,取值70元/m。
运维成本CO&M主要考虑设备维护费用,供能过程可能消耗的电费以及需补充热泵供冷、供热缺口所需费用。CO&M计算公式为:
CO&M=1Nyear(PEleEnet+PcoolQcool,net+PheatQheat,net)+            Cinvestφ
式中:EnetQcool,netQheat,net分别是系统供能过程中,热泵用电缺口(扣除光伏发电量)以及可能的供冷、供热的能量缺口;电价PEle取工商业平时电价0.75元/(kW·h);PhearPcool分别为补充供热和供冷缺口的热、冷电价,其具体数值参考集中供热和集中供冷电价,分别取值0.33、0.50元/(kW·h)。
由上文可知,光伏/光热装置布置量以及地源热泵容量大小既会影响热泵、地埋管换热器等关键设备的投资成本,同时又会对电费、供冷及供热费用等运维成本造成影响。以2.1节设定的光伏光热装置和地源热泵功率为基础,分析变动光伏光热和地源热泵装置容量对集成系统全生命周期成本的影响规律。
图8为集成系统全生命周期成本随光伏/光热装置和地源热泵相对规模的变动规律。从图8可见,系统全生命周期成本随着两者相对规模先减后增,存在相应最低点,两者变动原因皆是由于运维成本和投资成本的共同作用。
图8a)可见:在给定的地源热泵功率下,随着光伏/光热装置规模增加,系统电能缺口越来越少,电价投入减少导致系统的运维成本迅速降低;同时投资成本相对变动较小;成本最低点基本处于光伏/光热装置规模较大处。由图8b)可见:地源热泵相对规模增长初期,由于向外界购热和购冷需求降低,系统的运维成本急剧下降,同时由于地源热泵单体成本较高,所以投资成本也在较快增加;在相对规模超过0.7以后,运维成本基本不变但是投资成本仍稳定增加;两者共同作用,全生命周期成本最低点落于地源热泵相对规模0.4~0.6。
由上节可知,系统全生命周期成本皆会随光伏/光热装置及地源热泵容量先减后增,存在最优值。本节采用收敛速度较快、可实现全局搜索、避免局部最优的粒子群算法,对光伏/光热装置及地源热泵容量进行优化,以寻找系统全生命周期成本最低的配置方案。
基于粒子群的优化,选定种群数量为50,迭代次数设定为20次,具体优化过程如图9所示,系统优化前后各项成本对比如图10所示。从图9可见,在第10次迭代后已得到最优值(全生命周期成本74.96万元),对应的地源热泵容量为92.62 kW,光伏光热装置的总开口面积为147.20 m2。相较于初始选定容量,系统全生命周期成本降低31.52%。
系统优化前后运维及投资成本如图10所示。
图10可知,地源热泵容量减少带来的投资成本降低抵消了增加光伏/光热装置铺设量导致的投资增加,因而优化后的投资成本较原先降低了11.53万。地源热泵容量减少会导致额外的购热、购冷成本,但是此前设计中是以最大热/冷需求值设置的热泵容量,实际过程中大多数时刻难以达到,因此热泵容量减少(优化后)并未增加太多运维费用。同时,光伏/光热装置的增加大幅减少了热泵运行所需的电费,所以优化后的运维成本减少了22.98万元,降幅明显。
本文针对光伏/光热与地源热泵的集成系统展开研究,构建集成系统的仿真运行模型,分析了集成后系统的性能;对集成系统全生命周期成本进行了分析,获得了关键因素影响规律,并利用粒子群算法进行了经济性优化。得到以下结论,可为光伏光热-地源热泵系统优化设计提供理论依据。
1)集成系统光伏年均发电效率达17.73%,较单一运行系统提升9.58%;集成系统光伏余热可有效减少土壤温度下降,热泵长时运行性能较参比系统提升16.58%。
2)光伏光热装置和地源热泵规模增加都会降低系统运维费用,同时抬升投资成本。
3)相较以最大功率进行设计的初始方法,适当提升光伏光热装置规模,减少地源热泵容量可以实现运维成本和投资成本协同优化,全生命周期成本可降低31.52%。
  • 中国华电集团重点科技项目(CHDKJ22-01-23)
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doi: 10.19666/j.rlfd.202312183
  • 接收时间:2023-12-25
  • 首发时间:2026-01-07
  • 出版时间:2024-07-25
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  • 收稿日期:2023-12-25
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Key Science and Technology Program of China Huadian Corporation(CHDKJ22-01-23)
中国华电集团重点科技项目(CHDKJ22-01-23)
作者信息
    1.华电郑州机械设计研究院有限公司,河南 郑州 450046
    2.南京师范大学能源与机械工程学院,南京 210023
    3.天津大学机械工程学院,天津 300350

通讯作者:

王瑞林(1993),男,博士,副教授,主要研究方向为多能源系统互补集成、光伏光热综合利用,
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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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