Investigation of an efficient and green system based on liquid air energy storage (LAES) for district cooling and peak shaving: Energy and exergy analyses

被引:24
|
作者
Kandezi, Morteza Saleh [1 ]
Naeenian, Seyed Mojtaba Mousavi [1 ]
机构
[1] Islamic Azad Univ, West Tehran Branch, Dept Mech Engn, Tehran, Iran
关键词
Liquid air energy storage; Absorption chiller; Kalina cycle; Energy storage; District heating; Energy and exergy analysis; COMPRESSED-AIR; THERMODYNAMIC ANALYSIS; HEAT; PERFORMANCE; OPTIMIZATION; SOLAR; PLANT; COLD; ORC;
D O I
10.1016/j.seta.2021.101396
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Liquid air energy storage is a very new energy storage technology for large-scale applications with brilliant advantages over the other available grid-scale storage concepts such as higher energy density and no topographical restriction. In the present study, to assist more development of this technology, an efficient and green multi-generation system based on the liquid air energy storage, absorption cycle, and Kalina system is proposed and deeply investigated from the first and second laws of thermodynamics and economic. Moreover, a sensitivity analysis is conducted to scrutinize the effect of critical parameters on system performance. The proposed system can be efficiently used for power and cooling capacity production during peak demand periods, both of which can assist peak shaving and grid stability. Thermodynamic analysis indicates that during peak demand periods, a power of 5300 kW is generated by the air turbine during 3 h and with round trip energy and exergy efficiencies of 65.7% and 49.7%, respectively. The economic analysis shows that the investment cost of the system is around 3.68 $M and the referenced system has a payback time of 3.6 years and a total turnover of 11.3 $M can be achieved at the end of 25th year.
引用
收藏
页数:16
相关论文
共 50 条
  • [21] Energy and exergy analysis of a micro-compressed air energy storage and air cycle heating and cooling system
    Kim, Y. M.
    Favrat, D.
    ENERGY, 2010, 35 (01) : 213 - 220
  • [22] Conventional and advanced exergy analyses of an underwater compressed air energy storage system
    Wang, Zhiwen
    Xiong, Wei
    Ting, David S. -K.
    Carriveau, Rupp
    Wang, Zuwen
    APPLIED ENERGY, 2016, 180 : 810 - 822
  • [23] Energy, exergy, and economic analyses of a new liquid air energy storage system coupled with solar heat and organic Rankine cycle
    Ding, Xingqi
    Duan, Liqiang
    Zhou, Yufei
    Gao, Chao
    Bao, Yongsheng
    ENERGY CONVERSION AND MANAGEMENT, 2022, 266
  • [24] Techno-economic assessment of an efficient liquid air energy storage with ejector refrigeration cycle for peak shaving of renewable energies
    Mousavi, Shadi Bashiri
    Ahmadi, Pouria
    Adib, Mahdieh
    Izadi, Ali
    RENEWABLE ENERGY, 2023, 214 : 96 - 113
  • [25] Compressed Air Energy Storage (CAES) and Liquid Air Energy Storage (LAES) Technologies-A Comparison Review of Technology Possibilities
    Burian, Ondrej
    Dancova, Petra
    PROCESSES, 2023, 11 (11)
  • [26] Performance evaluation and exergy analysis of a novel combined cooling, heating and power (CCHP) system based on liquid air energy storage
    Xue, Xiao-Dai
    Zhang, Tong
    Zhang, Xue-Lin
    Ma, Lin-Rui
    He, Ya-Ling
    Li, Ming-Jia
    Mei, Sheng-Wei
    ENERGY, 2021, 222
  • [27] Thermodynamic and economic analyses of a novel liquid air energy storage (LAES) coupled with thermoelectric generator and Kalina cycle
    Nabat, Mohammad Hossein
    Sharifi, Shakiba
    Razmi, Amir Reza
    JOURNAL OF ENERGY STORAGE, 2022, 45
  • [28] Performance improvement of air liquefaction processes for liquid air energy storage (LAES) using magnetic refrigeration system
    Ansarinasab, Hojat
    Fatimah, Manal
    Khojasteh-Salkuyeh, Yaser
    JOURNAL OF ENERGY STORAGE, 2023, 65
  • [29] Energy and exergy analyses of a residential cold thermal energy storage system
    Acar, Canan
    Dincer, Ibrahim
    INTERNATIONAL JOURNAL OF EXERGY, 2016, 19 (04) : 441 - 458
  • [30] Optimization of Liquid Air Energy Storage (LAES) using a Genetic Algorithm (GA)
    Liu, Zhongxuan
    Yu, Haoshui
    Gundersen, Truls
    30TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PTS A-C, 2020, 48 : 967 - 972