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Numerical investigation of a joint approach to thermal energy storage and compressed air energy storage in aquifers

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  • Guo, Chaobin
  • Zhang, Keni
  • Pan, Lehua
  • Cai, Zuansi
  • Li, Cai
  • Li, Yi

Abstract

Different from conventional compressed air energy storage (CAES) systems, the advanced adiabatic compressed air energy storage (AA-CAES) system can store the compression heat which can be used to reheat air during the electricity generation stage. Thus, AA-CAES system can achieve a higher energy storage efficiency. Similar to the AA-CAES system, a compressed air energy storage in aquifers (CAESA) system, which is integrated with an aquifer thermal energy storage (ATES) could possibly achieve the same objective. In order to investigate the impact of ATES on the performance of CAESA, different injection air temperature schemes are designed and analyzed by using numerical simulations. Key parameters relative to energy recovery efficiencies of the different injection schemes, such as pressure distribution and temperature variation within the aquifers as well as energy flow rate in the injection well, are also investigated in this study. The simulations show that, although different injection schemes have a similar overall energy recovery efficiency (∼97%) as well as a thermal energy recovery efficiency (∼79.2%), the higher injection air temperature has a higher energy storage capability. Our results show the total energy storage for the injection air temperature at 80°C is about 10% greater than the base model scheme at 40°C. Sensitivity analysis reveal that permeability of the reservoir boundary could have significant impact on the system performance. However, other hydrodynamic and thermodynamic properties, such as the storage reservoir permeability, thermal conductivity, rock grain specific heat and rock grain density, have little impact on storage capability and the energy flow rate. Overall, our study suggests that the combination of ATES and CAESA can help keep the high efficiency of energy storage so as to make CAESA system more efficiency.

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  • Guo, Chaobin & Zhang, Keni & Pan, Lehua & Cai, Zuansi & Li, Cai & Li, Yi, 2017. "Numerical investigation of a joint approach to thermal energy storage and compressed air energy storage in aquifers," Applied Energy, Elsevier, vol. 203(C), pages 948-958.
    • Handle: RePEc:eee:appene:v:203:y:2017:i:c:p:948-958
    DOI: 10.1016/j.apenergy.2017.06.030
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    References listed on IDEAS

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    Cited by:

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    2. Wu, Shaohua & Yu, Ziwang & Kang, Jianguo & Zhang, Yanjun & Gao, Ping, 2021. "Research on the anisotropy of thermal conductivity of rocks in Songliao basin, China," Renewable Energy, Elsevier, vol. 179(C), pages 593-603.
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    5. Bao Jia & Jianzheng Su, 2024. "Exploring Porous Media for Compressed Air Energy Storage: Benefits, Challenges, and Technological Insights," Energies, MDPI, vol. 17(17), pages 1-20, September.
    6. Lyden, A. & Brown, C.S. & Kolo, I. & Falcone, G. & Friedrich, D., 2022. "Seasonal thermal energy storage in smart energy systems: District-level applications and modelling approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
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    8. Yang, Lichao & Cai, Zuansi & Li, Cai & He, Qingcheng & Ma, Yan & Guo, Chaobin, 2020. "Numerical investigation of cycle performance in compressed air energy storage in aquifers," Applied Energy, Elsevier, vol. 269(C).
    9. Li, Yi & Pan, Lehua & Zhang, Keni & Hu, Litang & Wang, Jinsheng & Guo, Chaobin, 2017. "Numerical modeling study of a man-made low-permeability barrier for the compressed air energy storage in high-permeability aquifers," Applied Energy, Elsevier, vol. 208(C), pages 820-833.
    10. Chen, Kecheng & Sun, Xiang & Soga, Kenichi & Nico, Peter S. & Dobson, Patrick F., 2024. "Machine-learning-assisted long-term G functions for bidirectional aquifer thermal energy storage system operation," Energy, Elsevier, vol. 301(C).
    11. Sun, Dongmei & Chu, Zhubin & Chen, Wenyuan & Feng, Ping & Zhang, Jiaxin, 2023. "Comparison of the characteristics of compressed air energy storage in dome-shaped and horizontal aquifers based on the Pittsfield aquifer field test," Applied Energy, Elsevier, vol. 348(C).
    12. Camargos, Tomás P.L. & Pottie, Daniel L.F. & Ferreira, Rafael A.M. & Maia, Thales A.C. & Porto, Matheus P., 2018. "Experimental study of a PH-CAES system: Proof of concept," Energy, Elsevier, vol. 165(PA), pages 630-638.
    13. Li, Yi & Liu, Yaning & Hu, Bin & Li, Yi & Dong, Jiawei, 2020. "Numerical investigation of a novel approach to coupling compressed air energy storage in aquifers with geothermal energy," Applied Energy, Elsevier, vol. 279(C).
    14. Guo, Chaobin & Li, Cai & Zhang, Keni & Cai, Zuansi & Ma, Tianran & Maggi, Federico & Gan, Yixiang & El-Zein, Abbas & Pan, Zhejun & Shen, Luming, 2021. "The promise and challenges of utility-scale compressed air energy storage in aquifers," Applied Energy, Elsevier, vol. 286(C).
    15. Fleuchaus, Paul & Godschalk, Bas & Stober, Ingrid & Blum, Philipp, 2018. "Worldwide application of aquifer thermal energy storage – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 861-876.

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