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Development of a micro-compressed air energy storage system model based on experiments

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  • Chen, Shang
  • Arabkoohsar, Ahmad
  • Zhu, Tong
  • Nielsen, Mads Pagh

Abstract

Compressed air energy storage system is a promising electricity storage technology. There are several simplified thermodynamic models for performance assessment of compressed air energy storage systems that do not provide an exact picture of the system performance. In this work, a modeling methodology is proposed for developing the model of a compressed air energy storage system. The models of individual components are gathered to constitute the system overall model. Reliable models of the components in different configurations ranging from single-to multi-stage designs are presented. These created models are validated with a sort of tests on a lab-scale setup, observing mean-absolute-percentage-errors of smaller than 8% in the worst case. The experimental results and models show that the output performance of the expander and the overall efficiency of the system vary from different configurations. With the development of the model derived from the experiment, the optimal condition is suggested. The increase in the number of stages of the expanders leads to a significant jump in the overall efficiency of the system. The efficiency of the designed experimental setup in different conditions ranges from 13% to 25%, and the optimal system efficiency will increase to 60% for a triple-stage system.

Suggested Citation

  • Chen, Shang & Arabkoohsar, Ahmad & Zhu, Tong & Nielsen, Mads Pagh, 2020. "Development of a micro-compressed air energy storage system model based on experiments," Energy, Elsevier, vol. 197(C).
    • Handle: RePEc:eee:energy:v:197:y:2020:i:c:s0360544220302590
    DOI: 10.1016/j.energy.2020.117152
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    References listed on IDEAS

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    6. Bai, Hao & Luo, ShiHao & Zhao, Xijie & Zhao, Gen & Gao, Yang, 2022. "Comprehensive assessment of a green cogeneration system based on compressed air energy storage (CAES) and zeotropic mixtures," Energy, Elsevier, vol. 254(PA).
    7. 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).
    8. Huang, Shucheng & Khajepour, Amir, 2022. "A new adiabatic compressed air energy storage system based on a novel compression strategy," Energy, Elsevier, vol. 242(C).
    9. Calautit, Katrina & Nasir, Diana S.N.M. & Hughes, Ben Richard, 2021. "Low power energy harvesting systems: State of the art and future challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    10. Shang Chen & Ahmad Arabkoohsar & Guodong Chen & Mads Pagh Nielsen, 2022. "Optimization of a Hybrid Energy System with District Heating and Cooling Considering Off-Design Characteristics of Components, an Effort on Optimal Compressed Air Energy Storage Integration," Energies, MDPI, vol. 15(13), pages 1-21, June.
    11. 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).

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