IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v391y2025ics0306261925006695.html

Dynamic Assessment and Optimization of Thermal Energy Storage Integration with Nuclear Power Plants Using Machine Learning and Computational Fluid Dynamics

Author

Listed:
  • Faizan, Muhammad
  • Afgan, Imran

Abstract

This study integrates thermal energy storage (TES) systems with nuclear power plants (NPPs) utilizing phase change materials (PCMs). It employs computational fluid dynamics (CFD) simulations and machine learning techniques to improve the overall efficiency and profitability of NPPs. The novelty of this research extends beyond merely analyzing the influence of PCM thermophysical properties, design parameters, and input conditions on system performance. The objective is to develop a TES system that can be effectively integrated with NPPs by addressing critical challenges, including the dynamic assessment of input parameters and the utilization of available excess energy in response to real-time demand fluctuations. For the analysis, 2,500 CFD simulations were performed to assess the phase change behavior within a vertical annular channel. Key design factors, such as heat transfer fluid injection conditions and various PCM properties, were systematically analyzed. The extensive dataset from numerical simulations was utilized to employ an artificial neural network (ANN) and a multi-objective genetic algorithm (MOGA) for optimizing the TES system, with an emphasis on minimizing injection velocity, reducing charging duration, and maximizing stored energy. The numerical and machine learning models were also explicitly evaluated against experimental data under different conditions. The findings indicate that design parameters have a substantial effect on the performance of the TES system, with the ANN model effectively predicting PCM melting time and energy storage capacity. This study presents a complete framework for an optimized thermal energy storage integration strategy specifically designed for NPPS, offering a scalable and efficient method for improving energy storage and utilization of excess energy during off-peak hours.

Suggested Citation

  • Faizan, Muhammad & Afgan, Imran, 2025. "Dynamic Assessment and Optimization of Thermal Energy Storage Integration with Nuclear Power Plants Using Machine Learning and Computational Fluid Dynamics," Applied Energy, Elsevier, vol. 391(C).
    • Handle: RePEc:eee:appene:v:391:y:2025:i:c:s0306261925006695
    DOI: 10.1016/j.apenergy.2025.125939
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261925006695
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2025.125939?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Wenwen Ye & Dourna Jamshideasli & Jay M. Khodadadi, 2023. "Improved Performance of Latent Heat Energy Storage Systems in Response to Utilization of High Thermal Conductivity Fins," Energies, MDPI, vol. 16(3), pages 1-83, January.
    2. Pereira da Cunha, Jose & Eames, Philip, 2016. "Thermal energy storage for low and medium temperature applications using phase change materials – A review," Applied Energy, Elsevier, vol. 177(C), pages 227-238.
    3. Prieto, Cristina & Cabeza, Luisa F., 2019. "Thermal energy storage (TES) with phase change materials (PCM) in solar power plants (CSP). Concept and plant performance," Applied Energy, Elsevier, vol. 254(C).
    4. Nithyanandam, K. & Pitchumani, R., 2014. "Cost and performance analysis of concentrating solar power systems with integrated latent thermal energy storage," Energy, Elsevier, vol. 64(C), pages 793-810.
    5. Longeon, Martin & Soupart, Adèle & Fourmigué, Jean-François & Bruch, Arnaud & Marty, Philippe, 2013. "Experimental and numerical study of annular PCM storage in the presence of natural convection," Applied Energy, Elsevier, vol. 112(C), pages 175-184.
    6. Kassianne Tofani & Saeed Tiari, 2021. "Nano-Enhanced Phase Change Materials in Latent Heat Thermal Energy Storage Systems: A Review," Energies, MDPI, vol. 14(13), pages 1-34, June.
    7. Fei Ma & Tianji Zhu & Yalin Zhang & Xinli Lu & Wei Zhang & Feng Ma, 2023. "A Review on Heat Transfer Enhancement of Phase Change Materials Using Fin Tubes," Energies, MDPI, vol. 16(1), pages 1-25, January.
    8. -, 2025. "United States economic outlook: third quarter of 2024," Oficina de la CEPAL en Washington (Estudios e Investigaciones) 81191, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    9. Anna Kluba & Robert Field, 2019. "Optimization and Exergy Analysis of Nuclear Heat Storage and Recovery," Energies, MDPI, vol. 12(21), pages 1-18, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rostami, Sara & Afrand, Masoud & Shahsavar, Amin & Sheikholeslami, M. & Kalbasi, Rasool & Aghakhani, Saeed & Shadloo, Mostafa Safdari & Oztop, Hakan F., 2020. "A review of melting and freezing processes of PCM/nano-PCM and their application in energy storage," Energy, Elsevier, vol. 211(C).
    2. Luu, Minh Tri & Milani, Dia & Nomvar, Mobin & Abbas, Ali, 2020. "A design protocol for enhanced discharge exergy in phase change material heat battery," Applied Energy, Elsevier, vol. 265(C).
    3. Kasper, Lukas & Pernsteiner, Dominik & Schirrer, Alexander & Jakubek, Stefan & Hofmann, René, 2023. "Experimental characterization, parameter identification and numerical sensitivity analysis of a novel hybrid sensible/latent thermal energy storage prototype for industrial retrofit applications," Applied Energy, Elsevier, vol. 344(C).
    4. Chen, C.Q. & Diao, Y.H. & Zhao, Y.H. & Ji, W.H. & Wang, Z.Y. & Liang, L., 2019. "Thermal performance of a thermal-storage unit by using a multichannel flat tube and rectangular fins," Applied Energy, Elsevier, vol. 250(C), pages 1280-1291.
    5. Mostafavi Tehrani, S. Saeed & Shoraka, Yashar & Diarce, Gonzalo & Taylor, Robert A., 2019. "An improved, generalized effective thermal conductivity method for rapid design of high temperature shell-and-tube latent heat thermal energy storage systems," Renewable Energy, Elsevier, vol. 132(C), pages 694-708.
    6. Zauner, Christoph & Hengstberger, Florian & Mörzinger, Benjamin & Hofmann, Rene & Walter, Heimo, 2017. "Experimental characterization and simulation of a hybrid sensible-latent heat storage," Applied Energy, Elsevier, vol. 189(C), pages 506-519.
    7. Liu, Yang & Zheng, Ruowei & Li, Ji, 2022. "High latent heat phase change materials (PCMs) with low melting temperature for thermal management and storage of electronic devices and power batteries: Critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    8. González-Portillo, Luis F. & Muñoz-Antón, Javier & Martínez-Val, José M., 2017. "An analytical optimization of thermal energy storage for electricity cost reduction in solar thermal electric plants," Applied Energy, Elsevier, vol. 185(P1), pages 531-546.
    9. Yu, Kunyang & Liu, Yushi & Yang, Yingzi, 2021. "Review on form-stable inorganic hydrated salt phase change materials: Preparation, characterization and effect on the thermophysical properties," Applied Energy, Elsevier, vol. 292(C).
    10. Nithyanandam, K. & Barde, A. & Lakeh, R. Baghaei & Wirz, R.E., 2018. "Charge and discharge behavior of elemental sulfur in isochoric high temperature thermal energy storage systems," Applied Energy, Elsevier, vol. 214(C), pages 166-177.
    11. Sharif, M.K. Anuar & Al-Abidi, A.A. & Mat, S. & Sopian, K. & Ruslan, M.H. & Sulaiman, M.Y. & Rosli, M.A.M., 2015. "Review of the application of phase change material for heating and domestic hot water systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 557-568.
    12. Raud, Ralf & Cholette, Michael E. & Riahi, Soheila & Bruno, Frank & Saman, Wasim & Will, Geoffrey & Steinberg, Theodore A., 2017. "Design optimization method for tube and fin latent heat thermal energy storage systems," Energy, Elsevier, vol. 134(C), pages 585-594.
    13. Du, Kun & Calautit, John & Eames, Philip & Wu, Yupeng, 2021. "A state-of-the-art review of the application of phase change materials (PCM) in Mobilized-Thermal Energy Storage (M-TES) for recovering low-temperature industrial waste heat (IWH) for distributed heat," Renewable Energy, Elsevier, vol. 168(C), pages 1040-1057.
    14. Lukas Hegner & Stefan Krimmel & Rebecca Ravotti & Dominic Festini & Jörg Worlitschek & Anastasia Stamatiou, 2021. "Experimental Feasibility Study of a Direct Contact Latent Heat Storage Using an Ester as a Bio-Based Storage Material," Energies, MDPI, vol. 14(2), pages 1-26, January.
    15. Mohammad, Mehedi Bin & Brooks, Geoffrey Alan & Rhamdhani, M. Akbar, 2017. "Thermal analysis of molten ternary lithium-sodium-potassium nitrates," Renewable Energy, Elsevier, vol. 104(C), pages 76-87.
    16. Yang, Haiyue & Wang, Yazhou & Yu, Qianqian & Cao, Guoliang & Yang, Rue & Ke, Jiaona & Di, Xin & Liu, Feng & Zhang, Wenbo & Wang, Chengyu, 2018. "Composite phase change materials with good reversible thermochromic ability in delignified wood substrate for thermal energy storage," Applied Energy, Elsevier, vol. 212(C), pages 455-464.
    17. Kumar, Ashish & Saha, Sandip K., 2021. "Performance study of a novel funnel shaped shell and tube latent heat thermal energy storage system," Renewable Energy, Elsevier, vol. 165(P1), pages 731-747.
    18. Tafone, Alessio & Borri, Emiliano & Cabeza, Luisa F. & Romagnoli, Alessandro, 2021. "Innovative cryogenic Phase Change Material (PCM) based cold thermal energy storage for Liquid Air Energy Storage (LAES) – Numerical dynamic modelling and experimental study of a packed bed unit," Applied Energy, Elsevier, vol. 301(C).
    19. Bailera, Manuel & Pascual, Sara & Lisbona, Pilar & Romeo, Luis M., 2021. "Modelling calcium looping at industrial scale for energy storage in concentrating solar power plants," Energy, Elsevier, vol. 225(C).
    20. Shahsavar, Amin & Al-Rashed, Abdullah A.A.A. & Entezari, Sajad & Sardari, Pouyan Talebizadeh, 2019. "Melting and solidification characteristics of a double-pipe latent heat storage system with sinusoidal wavy channels embedded in a porous medium," Energy, Elsevier, vol. 171(C), pages 751-769.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:391:y:2025:i:c:s0306261925006695. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.