摘要
微型绝热压缩空气储能(A-CAES)系统布置灵活,适用于典型分布式能源系统。通过对基于气动马达的微型A-CAES系统典型设备精确建模,构建了能够反映其系统性能的热力学模型。搭建了A-CAES系统的实验台,仿真模型与实验的平均误差在5.38%左右,验证了模型的可靠性。该系统的往返效率与综合效率分别为4.81%、27.23%,验证了热能存储装置在A-CAES系统存在的必要性。利用该模型研究分析了压缩级数、压缩比对系统性能的影响,结果表明:随压缩级数的增加,系统的往返效率和综合效率均随之增加,系统最优效率可分别达到6.10%和35.81%;以2、3和5的压缩比组合为例,其压缩比的合理分布可使得系统往返效率和综合效率分别提高1.27%和4.38%。
The arrangement of micro adiabatic compressed air energy storage(A-CAES)system is flexible and suitable for typical distributed energy systems.By accurately modelling a typical device of the miniature A-CAES system based on pneumatic motors,a thermodynamic model that can reflect its system performance is constructed.The experimental bench of the A-CAES system is built,and the average error rate between the simulation model and the experiment is around 5.38%,which verifies the reliability of the model.The round-trip efficiency and comprehensive efficiency of the system are 4.81%and 27.23%,respectively,verifying the necessity of the existence of thermal energy storage devices in the A-CAES system.The effects of compression level and compression ratio on the system performance are analyzed by using this model.The results show that,as the compression level increases,the round-trip efficiency and comprehensive efficiency of the system both increase,and the optimal efficiency of the system can reach 6.10%and 35.81%,respectively.Taking the combination of compression ratios of 2,3,and 5 as an example,reasonable distribution of compression ratios can improve the round-trip efficiency and overall efficiency of the system by 1.27%and 4.38%,respectively.
作者
张梦洁
刘强
张彤赫
宋永兴
张林华
ZHANG Mengjie;LIU Qiang;ZHANG Tonghe;SONG Yongxing;ZHANG Linhua(School of Thermal Energy Engineering,Shandong Jianzhu University,Jinan 250000,China;Jinan Special Equipment Inspection and Research Institute,Jinan 250101,China)
出处
《热力发电》
CAS
CSCD
北大核心
2024年第9期39-47,共9页
Thermal Power Generation
基金
压缩机技术国家重点实验室(压缩机技术安徽省实验室)开放基金项目(SKL-YSJ202108)
山东省自然科学基金(ZR2021QE157)。
关键词
微型
绝热压缩空气储能
热力学建模
效率
micro
adiabatic compressed air energy storage
thermodynamic modeling
efficiency