Article(id=1236699943910568611, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236699937195479441, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202405111, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1715443200000, receivedDateStr=2024-05-12, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1772781843402, onlineDateStr=2026-03-06, pubDate=1727193600000, pubDateStr=2024-09-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772781843402, onlineIssueDateStr=2026-03-06, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772781843402, creator=13701087609, updateTime=1772781843402, updator=13701087609, issue=Issue{id=1236699937195479441, tenantId=1146029695717560320, journalId=1210938733613449225, year='2024', volume='53', issue='9', pageStart='1', pageEnd='154', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1772781841801, creator=13701087609, updateTime=1772781841801, updator=13701087609, preIssue=null, nextIssue=null, ext=null, issueFiles=null}, startPage=60, endPage=68, ext={EN=ArticleExt(id=1236699944229335728, articleId=1236699943910568611, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Modeling and analysis of novel wind-drove compressed air energy storage system, columnId=1236699940546728377, journalTitle=Thermal Power Generation, columnName=Compressed air energy storage technology, runingTitle=null, highlight=null, articleAbstract=

A wind-drove compressed air energy storage (W-CAES) system is proposed, its main advantage is that it can reduce the waste of wind energy caused by the fluctuation and randomness of wind energy. The direct-driven compressor of wind turbine gets rid of the dependence of compressor on the input electricity, which is more suitable for off-grid power generation system. The model of the W-CAES system is established, the parameters of the wind turbine direct-drive compressed air energy storage system are designed, and the effects of wind speed, ambient temperature, and air humidity on efficiency of the system are analyzed. The results show that, the filling time increases with the decrease of wind speed with the same storage volume, and the filling times are 0.71 h and 1.64 h when the wind speeds are 14 m/s and 6 m/s, respectively. The system efficiency decreases slightly with the increase of ambient temperature and air humidity. When the ambient temperatures are -30 ℃ and 40 ℃, the corresponding system efficiencies are 52.97% and 52.08%, respectively. When the relative humidity of the air is 0 and 1, the corresponding system efficiencies are 52.27% and 52.14%, respectively.

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提出了风力机直接耦合压缩空气储能系统(wind drove compressed air energy storage,W-CAES),其优点是可以减少因风能的波动性和随机性而造成的风能浪费,采用风力机直驱压缩机的工作方式摆脱了压缩机对输入电能的依赖,更适应离网发电系统。建立了W-CAES系统模型,设计了风力机直驱的压缩空气储能系统参数,分析了风速、环境温度以及空气湿度对系统效率的影响。结果表明:在储气体积相同情况下,充气时间随风速的降低而增加,当风速为14、6 m/s时,充气时间分别为0.71、1.64 h;系统效率随环境温度和空气湿度的升高而略有降低;当环境温度分别为-30、40 ℃时,对应的系统效率分别为52.97%和52.08%;当空气的相对湿度分别为0和1时,对应的系统效率分别为52.27%和52.14%。

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何青(1962),男,教授,主要研究方向为储能技术,
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蒋志容(1993),女,工程师,主要研究方向为压缩空气储能系统,

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蒋志容(1993),女,工程师,主要研究方向为压缩空气储能系统,

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蒋志容(1993),女,工程师,主要研究方向为压缩空气储能系统,

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expander output power and system efficiency, figureFileSmall=ABL/YjDSdBbX7KbrtkKRlA==, figureFileBig=jkfxRpdkNVIZXFa2+sn3lA==, tableContent=null), ArticleFig(id=1236699957063905415, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236699943910568611, language=CN, label=图10, caption=空气湿度对膨胀机组输出功率与系统效率的影响, figureFileSmall=ABL/YjDSdBbX7KbrtkKRlA==, figureFileBig=jkfxRpdkNVIZXFa2+sn3lA==, tableContent=null), ArticleFig(id=1236699957143597195, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236699943910568611, language=EN, label=Tab.1, caption=

Parameters of the TICC-500 system

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过程参数级数
12345
储能过程压缩机进口空气压力/MPa0.0990.3420.8942.3446.041
压缩机出口空气压力/MPa0.3510.9132.3926.61511.230
压缩机进口空气温度/℃2545454545
压缩比3.5452.6682.6702.6301.859
压缩机绝热效率/%77.6579.6282.3181.1578.44
释能过程膨胀机进口空气压力/MPa3.001.010.33
膨胀机出口空气压力/MPa1.020.340.10
膨胀机进口空气温度/℃100100100
膨胀比2.942.973.14
膨胀机绝热效率/%87.9087.0083.60
), ArticleFig(id=1236699957223288975, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236699943910568611, language=CN, label=表1, caption=

TICC-500系统参数

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过程参数级数
12345
储能过程压缩机进口空气压力/MPa0.0990.3420.8942.3446.041
压缩机出口空气压力/MPa0.3510.9132.3926.61511.230
压缩机进口空气温度/℃2545454545
压缩比3.5452.6682.6702.6301.859
压缩机绝热效率/%77.6579.6282.3181.1578.44
释能过程膨胀机进口空气压力/MPa3.001.010.33
膨胀机出口空气压力/MPa1.020.340.10
膨胀机进口空气温度/℃100100100
膨胀比2.942.973.14
膨胀机绝热效率/%87.9087.0083.60
), ArticleFig(id=1236699957307175057, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236699943910568611, language=EN, label=Tab.2, caption=

Calculation results of shaft power of the compressor

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级数轴功率/kW误差/%
计算值实际值
177.4476.730.93
259.8459.360.81
357.9757.660.54
457.8957.430.80
536.4836.260.61
合计289.62287.440.76
), ArticleFig(id=1236699957416226967, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236699943910568611, language=CN, label=表2, caption=

压缩机轴功率计算结果

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级数轴功率/kW误差/%
计算值实际值
177.4476.730.93
259.8459.360.81
357.9757.660.54
457.8957.430.80
536.4836.260.61
合计289.62287.440.76
), ArticleFig(id=1236699957504307353, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236699943910568611, language=EN, label=Tab.3, caption=

Calculation results of shaft power of the expander

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级数轴功率/kW误差/%
计算值实际值
1183.16183.520.20
2183.44183.960.28
3184.26184.210.03
合计551.86551.690.15
), ArticleFig(id=1236699957609164958, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236699943910568611, language=CN, label=表3, caption=

膨胀机轴功率计算结果

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级数轴功率/kW误差/%
计算值实际值
1183.16183.520.20
2183.44183.960.28
3184.26184.210.03
合计551.86551.690.15
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Calculation results of the W-CAES system

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过程参数第1级第2级第3级第4级第5级
储能过程压缩机进口空气压力/MPa0.100.350.902.325.97
压缩机出口空气压力/MPa0.350.912.346.0311.34
压缩机进口空气温度/℃25.0045.0045.0045.0045.00
压缩机出口空气温度/℃172.76157.50158.17157.98119.37
压缩比3.502.602.602.601.90
压缩机绝热效率/%87.0089.0088.7089.2087.30
压缩机消耗功率/kW198.56151.02151.72150.6498.78
释能过程膨胀机进口空气压力/MPa3.001.020.35
膨胀机出口空气压力/MPa1.020.350.10
膨胀机进口空气温度/℃120.00120.00120.00
膨胀机出口空气温度/℃24.6325.2914.15
膨胀比2.942.943.43
膨胀机绝热效率/%90.0090.0090.00
膨胀机输出功率/kW125.40125.71140.86
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W-CAES系统计算结果

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过程参数第1级第2级第3级第4级第5级
储能过程压缩机进口空气压力/MPa0.100.350.902.325.97
压缩机出口空气压力/MPa0.350.912.346.0311.34
压缩机进口空气温度/℃25.0045.0045.0045.0045.00
压缩机出口空气温度/℃172.76157.50158.17157.98119.37
压缩比3.502.602.602.601.90
压缩机绝热效率/%87.0089.0088.7089.2087.30
压缩机消耗功率/kW198.56151.02151.72150.6498.78
释能过程膨胀机进口空气压力/MPa3.001.020.35
膨胀机出口空气压力/MPa1.020.350.10
膨胀机进口空气温度/℃120.00120.00120.00
膨胀机出口空气温度/℃24.6325.2914.15
膨胀比2.942.943.43
膨胀机绝热效率/%90.0090.0090.00
膨胀机输出功率/kW125.40125.71140.86
), ArticleFig(id=1236699957881794728, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236699943910568611, language=EN, label=Tab.5, caption=

Main parameters of the wind turbine

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序号参数数值
1额定功率/kW750
2叶轮转速/(r·min–1)22.55
3叶片数3
4风轮直径/m49
5额定风速/(m·s–1)14
6切入风速/(m·s–1)4
7切出风速/(m·s–1)25
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风力机主要参数

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序号参数数值
1额定功率/kW750
2叶轮转速/(r·min–1)22.55
3叶片数3
4风轮直径/m49
5额定风速/(m·s–1)14
6切入风速/(m·s–1)4
7切出风速/(m·s–1)25
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Variation of expansion unit output power with wind speed

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风速/
(m·s–1)
膨胀机输出功率/kW
第1级第2级第3级合计
662.963.170.7202.7
883.783.994.0269.6
1099.399.6111.6320.5
12111.8112.1125.6361.5
14125.4125.7140.9406.0
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膨胀机组输出功率随风速变化

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风速/
(m·s–1)
膨胀机输出功率/kW
第1级第2级第3级合计
662.963.170.7202.7
883.783.994.0269.6
1099.399.6111.6320.5
12111.8112.1125.6361.5
14125.4125.7140.9406.0
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Temperatures in January and July in Dabancheng

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月份风电场气温
平均极值
1–14.6–26.6(最低)
727.836.8(最高)
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达坂城1月和7月气温

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月份风电场气温
平均极值
1–14.6–26.6(最低)
727.836.8(最高)
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风力机直接耦合压缩空气储能系统及其建模分析
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蒋志容 1 , 胡中波 1 , 尉倥 1 , 李育斌 1 , 刘超 2 , 李红 2 , 何青 2
热力发电 | 压缩空气储能技术 2024,53(9): 60-68
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热力发电 | 压缩空气储能技术 2024, 53(9): 60-68
风力机直接耦合压缩空气储能系统及其建模分析
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蒋志容1 , 胡中波1, 尉倥1, 李育斌1, 刘超2, 李红2, 何青2
作者信息
  • 1.中国电建集团成都勘测设计研究院有限公司,成都 611100
  • 2.华北电力大学能源动力与机械工程学院,北京 102206
  • 蒋志容(1993),女,工程师,主要研究方向为压缩空气储能系统,

通讯作者:

何青(1962),男,教授,主要研究方向为储能技术,
Modeling and analysis of novel wind-drove compressed air energy storage system
Zhirong JIANG1 , Zhongbo HU1, Kong YU1, Yubin LI1, Chao LIU2, Hong LI2, Qing HE2
Affiliations
  • 1.POWERCHINA Chengdu Engineering Corporation Limited, Chengdu 611100, China
  • 2.School of Energy, Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China
出版时间: 2024-09-25 doi: 10.19666/j.rlfd.202405111
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提出了风力机直接耦合压缩空气储能系统(wind drove compressed air energy storage,W-CAES),其优点是可以减少因风能的波动性和随机性而造成的风能浪费,采用风力机直驱压缩机的工作方式摆脱了压缩机对输入电能的依赖,更适应离网发电系统。建立了W-CAES系统模型,设计了风力机直驱的压缩空气储能系统参数,分析了风速、环境温度以及空气湿度对系统效率的影响。结果表明:在储气体积相同情况下,充气时间随风速的降低而增加,当风速为14、6 m/s时,充气时间分别为0.71、1.64 h;系统效率随环境温度和空气湿度的升高而略有降低;当环境温度分别为-30、40 ℃时,对应的系统效率分别为52.97%和52.08%;当空气的相对湿度分别为0和1时,对应的系统效率分别为52.27%和52.14%。

压缩空气储能  /  风力机  /  建模  /  压缩机  /  风速

A wind-drove compressed air energy storage (W-CAES) system is proposed, its main advantage is that it can reduce the waste of wind energy caused by the fluctuation and randomness of wind energy. The direct-driven compressor of wind turbine gets rid of the dependence of compressor on the input electricity, which is more suitable for off-grid power generation system. The model of the W-CAES system is established, the parameters of the wind turbine direct-drive compressed air energy storage system are designed, and the effects of wind speed, ambient temperature, and air humidity on efficiency of the system are analyzed. The results show that, the filling time increases with the decrease of wind speed with the same storage volume, and the filling times are 0.71 h and 1.64 h when the wind speeds are 14 m/s and 6 m/s, respectively. The system efficiency decreases slightly with the increase of ambient temperature and air humidity. When the ambient temperatures are -30 ℃ and 40 ℃, the corresponding system efficiencies are 52.97% and 52.08%, respectively. When the relative humidity of the air is 0 and 1, the corresponding system efficiencies are 52.27% and 52.14%, respectively.

compressed air energy storage  /  wind turbine  /  modeling  /  compressor  /  wind speed
蒋志容, 胡中波, 尉倥, 李育斌, 刘超, 李红, 何青. 风力机直接耦合压缩空气储能系统及其建模分析. 热力发电, 2024 , 53 (9) : 60 -68 . DOI: 10.19666/j.rlfd.202405111
Zhirong JIANG, Zhongbo HU, Kong YU, Yubin LI, Chao LIU, Hong LI, Qing HE. Modeling and analysis of novel wind-drove compressed air energy storage system[J]. Thermal Power Generation, 2024 , 53 (9) : 60 -68 . DOI: 10.19666/j.rlfd.202405111
近年来随着碳中和概念的提出,对可再生能源的需求,特别是风能在发电中的份额正在显著增加[1]。根据全球风能理事会2024年发布的全球风能报告,2023年全球风能行业新增装机容量达117 GW,较2022年同比增长50%[2]。风能的消纳依赖于电网的传输能力,而离网型工业园区则能够减轻电网建设负担,实现风能资源的本地消纳[3]。然而,由于风能本身的间歇性和波动性,每年有大量风电被浪费[4],因此未来有必要探索以不同形式利用风能的新技术。
压缩空气储能系统(compressed air energy storage,CAES)是一种利用电能与空气介质内能之间能量相互转换,从而实现能量储备与利用的系统。CAES系统具有运行寿命长、涉网性能好、安全风险小等优点[5]
Ouyang等人[6]为解决偏远地区电力供应问题,提出了一种具有移峰功能的新型离网系统,该系统由固体氧化物燃料电池、布雷顿循环、有机朗肯循环、CAES系统组成。研究发现CAES系统不仅具有储能和调峰功能,而且可以提高系统的经济性。Farshad等人[7]模拟了一个可以同时提供电能与热能的离网孤岛系统,并将CAES系统应用于该系统中,研究表明加入CAES系统后的混合系统相比于电池储能系统,其预计成本可降低7.7%。
Mahdieh等人[8]针对偏远地区提出了一种包含CAES系统、风力机与柴油发电机能源系统的设计方法,并建立了该系统计算模型。研究结果表明,与仅采用柴油发电机的能源预计系统相比,该系统能够显著降低平均每日总成本与二氧化碳排放量。Mahdieh等人[9]认为CAES系统与风能整合时应重点研究风能波动对CAES系统运行的影响,指出集成后系统运行方案的设计及设备运行都将面对巨大的挑战。
在风力机驱动压缩机技术方面,Chen等人[10]成功研制了风力强制制冷机,该制冷机采用风力机直接驱动压缩机进行制冷,取代了传统的电能与机械能间的转换,提高了制冷系统工作效率。文献[11]提出了一种直接采用风力驱动热泵的新技术,并完成了实验验证,结果表明采用该技术的系统在冷却和加热过程中效率均提高10%以上。
Sun等人[11]提出了一种利用风力机直接驱动压缩机的新型风热系统,并对该系统进行了实验研究,结果表明该系统具有良好的加热性能。此外,该团队利用实验数据对该系统进行了常规和先进㶲分析研究,评估了各部分组件的改进潜力,结果表明系统中压缩机与冷凝器是最需被优化的[4]
本文针对离网系统提出一种与风力机直接耦合的压缩空气储能(wind drove CAES,W-CAES)系统,建立系统的计算模型,对系统进行设计,并计算分析风资源和环境因素对系统效率的影响。
W-CAES系统原理如图1所示。W-CAES系统运行主要包括储能过程与释能过程,其中储能过程为气体压缩过程,释能过程为气体膨胀过程。在储能过程中,压缩机组通过风力机组的同轴驱动将空气压缩至高温高压状态,高温高压空气经冷却器冷却后储存在储气库中。冷却器中的换热工质在吸收了高温高压空气的热量后储存在高温储罐中。在释能过程中,储气库中高压空气被再热器中的高温换热工质加热成高温高压空气进入膨胀机组,驱动膨胀机组做功,进而带动发电机发电,而高温换热工质经换热后储存在低温储罐。
与传统CAES系统不同,W-CAES系统利用风力机转子将风能直接转化为压缩机机械能,然后由压缩机将工质空气压缩并储存。W-CAES系统的特点是在风力机产生电能之前,直接将风力机的输出机械能作为压缩机的输入能量,并通过压缩机压缩空气进行能量存储,减少了能量转换次数,可以避免传统风电存储系统中因发电机和电动机等导致的能量损失。
为研究分析W-CAES系统工作特性,本文建立W-CAES系统各组成部分的计算模型。为简化分析流程,系统建模时作如下假设:
1)系统工作在稳定状态;
2)空气的压缩和膨胀过程均为绝热过程;
3)忽略管道压损;
4)忽略部件间的摩擦损失和热量损失。
风力机作为捕获和传动风能的装置,其组成结构主要包括叶片和轮毂、齿轮箱、联轴器等中间传动装置。风力机主要作用是将风能转换为轮毂机械能,风力机机械输出功率为[12-13]
Pm=12πCpρR2v3
式中:ρ为空气密度,kg/m3R为风力机叶片长度,m;v为风速,m/s;Cp为风能利用系数。
风能利用系数Cp为:
Cp=0.5176(116λi0.4β5)e21λi+0.0068λT
式中:λT为叶尖速比;β为叶片桨距角,°;λi为与λTβ相关的系数[13]
1λi=1λT+0.08β0.035β3+1
λT=RωTv
式中:ωT为风力机机械角速度,rad/s。
压缩机作为W-CAES系统储能过程中的核心设备,主要作用是将工质空气压缩至高压,将机械能转化为内能。往复式压缩机适用于中小流量、高压力的场合,因此往复式压缩机更适用于小规模的W-CAES系统[14-15]
压缩机的主要作用为提升WT-CAES系统中空气的压力。压缩机出口空气温度为[16]
Tco=(1+βcκ1κ1ηc)Tci
式中:Tco为压缩机出口空气温度,K;βc为压缩机的压缩比;ηc为压缩机的绝热效率,%;κ为空气的绝热指数;Tci为压缩机进口空气温度,K。
βc=pcopci
式中:Pco为压缩机出口空气压力,Pa;pci为压缩机进口空气压力,Pa。
压缩机组总耗功率pc[16]
Pc=mccaTci(βcκ1κ1)ηc
式中:ca为空气比热容,J/(kg·K);mc为压缩机排出空气的质量流量,kg/s。
膨胀机中空气的出口温度为[16]
Teo=βeκ1κTei
式中:Teo为膨胀机出口空气温度,K;βe为膨胀机的膨胀比;Tei为膨胀机进口空气温度,K。
膨胀机的膨胀比定义为:
βe=peopei
式中:peo为膨胀机出口空气压力,Pa;pei为膨胀机进口空气压力,Pa。
膨胀机的输出功率Pe[16]
Pe=meηecaTei(1βeκ1κ)
式中:ηe为膨胀机的绝热效率,%;me为膨胀机排出空气的质量流量,kg/s。
W-CAES系统中换热器包括冷却器与再热器2类。冷却器与再热器工作原理相同,即2种不同温度的流体通过热传导和对流的方式进行热量交换。
换热器出口的空气温度为[17]
Tho=ηhTfi+(1ηh)Thi
式中:ηh为换热器换热效率,%;Thi为进口空气温度,K;Tho为出口空气温度,K;Tfi为换热工质进口温度,K。
换热工质出口温度为:
Tfo=ηhThi+(1ηh)Tei
式中:Tfo为换热工质出口温度,K。
换热器内空气压降为[17]
Δp=λpphi
式中:Δp为换热器内空气压降,Pa;λp为压力损失系数;phi为进口空气压力,Pa。
CAES系统的储气库通常可分为地下储气库和地上储罐2种类型。对于小型CAES系统,由于存储容量较小,可以采用地上储罐。本文系统采用圆柱形压力容器作为空气储气罐(图2)。该储气罐由1个圆柱形主体和2个椭圆形封头组成。该储气罐的体积和表面积分别为[18]
V=14πD2L+112πD3
A=πDL+0.69πD2
式中:V为储气罐的体积,m3A为储气罐的表面积,m2D为圆柱体的直径,m;L为圆柱体的长度,m。
描述储存动态行为的控制方程主要包括理想气体状态方程、质量守恒方程和能量守恒方程。
质量守恒方程为[18]
dm1dt=m˙inm˙out
式中:m1为压力容器内气体质量,kg;min为进入气体质量,kg;mout为排出气体质量,kg。
能量守恒方程为[18]
d(m1uc)dt=m˙inhinm˙outhoutQ˙c
式中:hin为进口空气比焓,J/kg;hout为出口空气比焓,J/kg;Qc为储罐传递的热量,J。
传热速率Q˙c为:
Q˙c=αA1(TcTa)
式中:α为储罐与环境间的换热系数;Tc为储罐内气体温度,K;Ta为环境温度,K。
根据自然对流换热理论确定储罐与环境之间的换热系数α[19]
α=1.12λkls[g(TTa)ls3ρ2cvTμλk]0.246
式中:λk为空气的导热系数,W/(m·K);μ为空气的黏度,Pa·s;cv为空气的比定容热容,J/(kg·K);g为重力加速度,g=9.8 m/s2ls为压力容器的特征长度,通常取为容器直径,m。
系统效率是衡量储能系统的关键指标[20]。W-CAES系统效率可以采用膨胀机组总输出功比风力机组输出功计算:
η=tei=1NPe(i)tcPm
式中:η为系统效率,%;tc为储能时间,h;te为释能时间,h;N为膨胀机组级数。
为了验证系统模型的正确性,本文采用TICC-500系统提供的初始参数[21],对系统储能过程和释能过程分别进行验证。TICC-500系统的初始参数见表1[21],压缩机和膨胀机轴功率计算结果见表2表3。从表2表3可见,储能过程中压缩机轴功率计算结果与文献[21]结果最大误差为0.93%,释能过程中膨胀机轴功率计算结果与文献[21]结果最大相对误差为0.28%。可见,本文建立的系统模型准确、可靠。
W-CAES系统在实际工作运行中会受到许多环境因素的制约,如风速、环境空气的温度、湿度等。风速会影响风力机与压缩机的转速,环境空气的温度、湿度会影响压缩机的性能。本文以750 kW风力机组为例,参考TICC-500,建立相应的W-CAES系统,并分析这些因素对系统部件及系统效率的影响。
考虑到750 kW风力机组作为压缩机的驱动源,W-CAES的规模与500 kW的TICC-500系统比较接近,因此本文W-CAES系统采用与TICC-500系统相同的结构形式,即压缩机组采用5级压缩、膨胀机组采用3级膨胀。系统结构如图3所示。为简化齿轮箱的结构,减少传动过程中的能量损失,简化多级压缩机布置空间提高系统的稳定性,压缩机组采用同轴驱动、级间换热的组合方式。该装置应用本文模型设计计算得到对应的W-CAES系统主要参数见表4。风力机组主要参数见表5。由式(20)计算得到W-CAES系统效率为52.27%,比TICC-500系统41.03%[21]的效率提高了11.24百分点。
表4可知,风力机的切入风速、额定风速、切出风速分别为4、14、25 m/s。图4为风速4~25 m/s时风力机高速轴转速随风速的变化情况。由图4可知:在未经过变桨距角调节时,在切入风速到额定风速范围(4~14 m/s)内,风力机转速随风速的增加而显著增加,直至达到额定风速将稳定在1 500 r/min;在额定风速附近14~16 m/s,风力机转速在额定转速附近变化;在风速为16~25 m/s时,风力机转速随风速的增加而逐渐增加。由式(1)—式(4)可知,当风速超过额定风速时,可以通过调节风力机叶片桨距角,限制输出功率,调节风力机转速。经变桨距角调节后,当风速超过额定风速时,风力机高速轴转速可以稳定在1 500 r/min。
图5描述了不同风速条件下压缩机消耗的功率、产生的气体质量流量、绝热效率的变化趋势。由图5可见:随着风速的降低,5级压缩机消耗的功率逐渐降低,其中第2、3、4级压缩机消耗功率减小值基本一致;随风速降低,5级压缩机产生的气体质量流量均不断减小,且5级压缩机质量流量减小值相差很小。
图5c)可见,随着风速的逐渐降低,压缩机的绝热效率呈先升高后降低的变化趋势,第1、2、3、4级压缩机绝热效率于风速为8 m/s时达到最大值,绝热效率分别为89.1%、90.7%、90.4%、90.0%,第5级压缩机绝热效率于风速为10 m/s时达到最大值为88.2%。当风速低于8 m/s时气体压力在吸气阶段与排气阶段产生波动,气阀开始产生震颤,导致排出单位质量气体流量的耗功增多,压缩机绝热效率降低。
图6为不同风速条件下,储气罐充气时间与系统效率的变化趋势。从图6可以看出,储能时间随着风速的增加逐渐减小,风速为6、14 m/s时储能时间分别为1.64、0.71 h。表6为膨胀机组输出功率随风速变化结果。由表6可见,随风速逐渐增加,膨胀机组输出的功率逐渐增加。从图6可见,随风速增加,系统效率呈现先增大后减小的趋势,系统效率于风速为8 m/s时达到最大值约为53%。
表7为新疆达坂城风电场最冷月份1月与最热月份7月的温度[21]。从表7可以看出,新疆达坂城风电场1月极端最低温度为-26.6 ℃,7月极端最高温度为36.8 ℃。因此,本文环境温度范围取-30~40 ℃。
图7描述了不同环境温度条件下压缩机消耗的功率、产生气体质量流量、绝热效率的变化情况。由图7可见:随着环境温度逐渐增加压缩机消耗功率与产生气体流量整体呈现降低的趋势;压缩机的绝热效率则是随环境温度升高而逐渐升高。环境温度分别为-30、40 ℃时,压缩机的绝热效率分别为74.9%、90.1%。图8为环境温度对膨胀机组输出功率与系统效率的影响。由图8可知,膨胀机组的输出功率随环境温度的增加逐渐减小,系统效率随环境温度的增加不断降低。环境温度为-30、40 ℃时,系统效率分别为52.97%和52.08%。
图9描述了环境温度为25 ℃时,不同空气湿度条件下压缩机消耗的功率、产生的气体质量流量、绝热效率的变化。由图9可见,随空气湿度的逐渐增加,压缩机消耗功率整体呈现降低趋势。因受空气湿度变化的影响,空气湿度越大压缩机吸入和排出的气体质量越少,因此压缩机排出的气体质量流量越小。压缩机的绝热效率则是随着空气湿度的升高而逐渐降低。
空气湿度对膨胀机组输出功率与系统效率的影响如图10所示。由图10可见,膨胀机组的输出功率随空气湿度的增加而逐渐减小,系统效率也随空气湿度的增加而逐渐减少。当空气相对湿度为0和1时,系统效率分别为52.27%和52.14%。
本文建立了W-CAES系统的计算模型,分析了风速、环境温度、空气湿度等因素对系统模型的影响,得出以下结论。
1)在切入风速到额定风速(4~14 m/s)范围内,风力机转速随风速的增加而快速增加。在额定风速附近(14~16 m/s),风力机转速在额定转速附近变化。在风速为16~25 m/s时,风力机转速随风速的增加而继续缓慢增加。
2)储气罐充气时间随风速的降低而增加,风速为5 m/s时存储时间为1.64 h,风速为额定风速14 m/s时存储时间为0.71 h。随着风速的增加,系统效率呈现先增大后减小的趋势,系统效率于风速为8 m/s时达到最大值,约为53%。
3)随着环境温度的增加,第1级压缩机消耗的功率和产生的气体质量流量逐渐减小,绝热效率随环境温度的增加而增加,最高环境温度与最低环境温度绝热效率约相差15%。此外,系统效率随环境温度的增加而不断降低,环境温度为-30 ℃和40 ℃时,系统效率分别为52.97%和52.08%。
4)空气湿度主要影响产生单位气体质量时压缩机的耗功;随着空气相对湿度的增加,压缩机消耗的功率、产生的气体质量流量、绝热效率,系统效率均逐渐降低。当入口相对湿度为0和1时,系统效率分别为52.27%和52.14%。
为方便比较,本文的W-CAES系统结构方案及各部件参数主要参考了TICC-500系统,并未对系统方案进行优化。未来可以针对系统结构以及各部件参数进行优化,有望进一步提高系统的效率,凸显风力机直驱压缩空气储能系统的优势。
  • 中国电力建设集团核心攻关项目(DJ-HXGG-2023-09)
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2024年第53卷第9期
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doi: 10.19666/j.rlfd.202405111
  • 接收时间:2024-05-12
  • 首发时间:2026-03-06
  • 出版时间:2024-09-25
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  • 收稿日期:2024-05-12
基金
Core Research Projects of Power Construction Corporation of China(DJ-HXGG-2023-09)
中国电力建设集团核心攻关项目(DJ-HXGG-2023-09)
作者信息
    1.中国电建集团成都勘测设计研究院有限公司,成都 611100
    2.华北电力大学能源动力与机械工程学院,北京 102206

通讯作者:

何青(1962),男,教授,主要研究方向为储能技术,
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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
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