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A novel optimization strategy for designing cryogenic energy storage systems

Author

Listed:
  • Manassaldi, Juan I.
  • Incer-Valverde, Jimena
  • Morosuk, Tatiana
  • Mussati, Miguel C.
  • Mussati, Sergio F.

Abstract

Liquid Air Energy Storage offers several advantages over other energy storage systems, including high energy density, scalability, cost-competitiveness, and non-geographical constraints. This study develops a computational tool for optimizing such systems. A deterministic, non-linear mathematical model was implemented in an object-oriented, equation-based programming language and solved using a derivative-based optimization algorithm.

Suggested Citation

  • Manassaldi, Juan I. & Incer-Valverde, Jimena & Morosuk, Tatiana & Mussati, Miguel C. & Mussati, Sergio F., 2025. "A novel optimization strategy for designing cryogenic energy storage systems," Energy, Elsevier, vol. 332(C).
    • Handle: RePEc:eee:energy:v:332:y:2025:i:c:s0360544225021322
    DOI: 10.1016/j.energy.2025.136490
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    References listed on IDEAS

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    1. Hamdy, Sarah & Morosuk, Tatiana & Tsatsaronis, George, 2019. "Exergoeconomic optimization of an adiabatic cryogenics-based energy storage system," Energy, Elsevier, vol. 183(C), pages 812-824.
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    4. Sarah Hamdy & Francisco Moser & Tatiana Morosuk & George Tsatsaronis, 2019. "Exergy-Based and Economic Evaluation of Liquefaction Processes for Cryogenics Energy Storage," Energies, MDPI, vol. 12(3), pages 1-19, February.
    5. Sciacovelli, A. & Vecchi, A. & Ding, Y., 2017. "Liquid air energy storage (LAES) with packed bed cold thermal storage – From component to system level performance through dynamic modelling," Applied Energy, Elsevier, vol. 190(C), pages 84-98.
    6. Lukasz Szablowski & Piotr Krawczyk & Marcin Wolowicz, 2021. "Exergy Analysis of Adiabatic Liquid Air Energy Storage (A-LAES) System Based on Linde–Hampson Cycle," Energies, MDPI, vol. 14(4), pages 1-16, February.
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    8. Chreim, Bashar & Esseghir, Moez & Merghem-Boulahia, Leila, 2022. "LOSISH—LOad Scheduling In Smart Homes based on demand response: Application to smart grids," Applied Energy, Elsevier, vol. 323(C).
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