IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v219y2023ip2s096014812301426x.html
   My bibliography  Save this article

Stratified thermal energy storage model with constant layer volume for predictive control — Formulation, comparison, and empirical validation

Author

Listed:
  • Zinsmeister, Daniel
  • Tzscheutschler, Peter
  • Perić, Vedran S.
  • Goebel, Christoph

Abstract

Recent developments in heating systems have witnessed a significant increase of heat pumps with a highly temperature-dependent efficiency. Optimal real-time operation of these heating systems with predictive control requires a thorough understanding and modeling of the internal temperature distribution of the associated thermal energy storage. At the same time, the thermal energy storage models need to be sufficiently simple to ensure computational tractability in real-time predictive control. Therefore, this article presents a stratified thermal energy storage model with constant layer volume and variable temperature suitable for real-time predictive control. The model employs a novel formulation with quadratic or simpler constraints which enable high accuracy at low computation burden. The proposed model is validated experimentally and compared with other models available in literature. The results show that the proposed stratified thermal energy storage model represents the real-world behavior of a thermal energy storage with great accuracy, while reducing the required computational burden as compared to other models for real-time operation and control. A case study further demonstrates that the increased accuracy of the proposed new model leads to cost and energy savings for the operator.

Suggested Citation

  • Zinsmeister, Daniel & Tzscheutschler, Peter & Perić, Vedran S. & Goebel, Christoph, 2023. "Stratified thermal energy storage model with constant layer volume for predictive control — Formulation, comparison, and empirical validation," Renewable Energy, Elsevier, vol. 219(P2).
  • Handle: RePEc:eee:renene:v:219:y:2023:i:p2:s096014812301426x
    DOI: 10.1016/j.renene.2023.119511
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096014812301426X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2023.119511?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Optimal energy management in all-electric residential energy systems with heat and electricity storage," Applied Energy, Elsevier, vol. 254(C).
    2. Atabay, Dennis, 2017. "An open-source model for optimal design and operation of industrial energy systems," Energy, Elsevier, vol. 121(C), pages 803-821.
    3. De la Cruz-Loredo, Iván & Zinsmeister, Daniel & Licklederer, Thomas & Ugalde-Loo, Carlos E. & Morales, Daniel A. & Bastida, Héctor & Perić, Vedran S. & Saleem, Arslan, 2023. "Experimental validation of a hybrid 1-D multi-node model of a hot water thermal energy storage tank," Applied Energy, Elsevier, vol. 332(C).
    4. Han, Y.M. & Wang, R.Z. & Dai, Y.J., 2009. "Thermal stratification within the water tank," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 1014-1026, June.
    5. Renaldi, R. & Kiprakis, A. & Friedrich, D., 2017. "An optimisation framework for thermal energy storage integration in a residential heat pump heating system," Applied Energy, Elsevier, vol. 186(P3), pages 520-529.
    6. Candas, Soner & Reveron Baecker, Beneharo & Mohapatra, Anurag & Hamacher, Thomas, 2023. "Optimization-based framework for low-voltage grid reinforcement assessment under various levels of flexibility and coordination," Applied Energy, Elsevier, vol. 343(C).
    7. Muschick, D. & Zlabinger, S. & Moser, A. & Lichtenegger, K. & Gölles, M., 2022. "A multi-layer model of stratified thermal storage for MILP-based energy management systems," Applied Energy, Elsevier, vol. 314(C).
    8. Steen, David & Stadler, Michael & Cardoso, Gonçalo & Groissböck, Markus & DeForest, Nicholas & Marnay, Chris, 2015. "Modeling of thermal storage systems in MILP distributed energy resource models," Applied Energy, Elsevier, vol. 137(C), pages 782-792.
    9. Hermansen, Rune & Smith, Kevin & Thorsen, Jan Eric & Wang, Jiawei & Zong, Yi, 2022. "Model predictive control for a heat booster substation in ultra low temperature district heating systems," Energy, Elsevier, vol. 238(PA).
    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. Baeten, Brecht & Confrey, Thomas & Pecceu, Sébastien & Rogiers, Frederik & Helsen, Lieve, 2016. "A validated model for mixing and buoyancy in stratified hot water storage tanks for use in building energy simulations," Applied Energy, Elsevier, vol. 172(C), pages 217-229.
    2. Untrau, Alix & Sochard, Sabine & Marias, Frédéric & Reneaume, Jean-Michel & Le Roux, Galo A.C. & Serra, Sylvain, 2023. "A fast and accurate 1-dimensional model for dynamic simulation and optimization of a stratified thermal energy storage," Applied Energy, Elsevier, vol. 333(C).
    3. Lago, Jesus & De Ridder, Fjo & Mazairac, Wiet & De Schutter, Bart, 2019. "A 1-dimensional continuous and smooth model for thermally stratified storage tanks including mixing and buoyancy," Applied Energy, Elsevier, vol. 248(C), pages 640-655.
    4. Maier, Laura & Schönegge, Marius & Henn, Sarah & Hering, Dominik & Müller, Dirk, 2022. "Assessing mixed-integer-based heat pump modeling approaches for model predictive control applications in buildings," Applied Energy, Elsevier, vol. 326(C).
    5. Liu, Fang & Mo, Qiu & Yang, Yongwen & Li, Pai & Wang, Shuai & Xu, Yanping, 2022. "A nonlinear model-based dynamic optimal scheduling of a grid-connected integrated energy system," Energy, Elsevier, vol. 243(C).
    6. Efkarpidis, Nikolaos A. & Vomva, Styliani A. & Christoforidis, Georgios C. & Papagiannis, Grigoris K., 2022. "Optimal day-to-day scheduling of multiple energy assets in residential buildings equipped with variable-speed heat pumps," Applied Energy, Elsevier, vol. 312(C).
    7. Matthias Eydner & Lu Wan & Tobias Henzler & Konstantinos Stergiaropoulos, 2022. "Real-Time Grid Signal-Based Energy Flexibility of Heating Generation: A Methodology for Optimal Scheduling of Stratified Storage Tanks," Energies, MDPI, vol. 15(5), pages 1-31, February.
    8. Launay, S. & Kadoch, B. & Le Métayer, O. & Parrado, C., 2019. "Analysis strategy for multi-criteria optimization: Application to inter-seasonal solar heat storage for residential building needs," Energy, Elsevier, vol. 171(C), pages 419-434.
    9. Firouzmakan, Pouya & Hooshmand, Rahmat-Allah & Bornapour, Mosayeb & Khodabakhshian, Amin, 2019. "A comprehensive stochastic energy management system of micro-CHP units, renewable energy sources and storage systems in microgrids considering demand response programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 355-368.
    10. Osorio, J.D. & Rivera-Alvarez, A. & Swain, M. & Ordonez, J.C., 2015. "Exergy analysis of discharging multi-tank thermal energy storage systems with constant heat extraction," Applied Energy, Elsevier, vol. 154(C), pages 333-343.
    11. Pérez-Iribarren, E. & González-Pino, I. & Azkorra-Larrinaga, Z. & Gómez-Arriarán, I., 2020. "Optimal design and operation of thermal energy storage systems in micro-cogeneration plants," Applied Energy, Elsevier, vol. 265(C).
    12. Nolting, Lars & Praktiknjo, Aaron, 2019. "Techno-economic analysis of flexible heat pump controls," Applied Energy, Elsevier, vol. 238(C), pages 1417-1433.
    13. Saloux, E. & Candanedo, J.A., 2019. "Modelling stratified thermal energy storage tanks using an advanced flowrate distribution of the received flow," Applied Energy, Elsevier, vol. 241(C), pages 34-45.
    14. Behzadi, Amirmohammad & Holmberg, Sture & Duwig, Christophe & Haghighat, Fariborz & Ooka, Ryozo & Sadrizadeh, Sasan, 2022. "Smart design and control of thermal energy storage in low-temperature heating and high-temperature cooling systems: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    15. Porteiro, Jacobo & Míguez, José Luis & Crespo, Bárbara & López González, Luis María & De Lara, José, 2015. "Experimental investigation of the thermal response of a thermal storage tank partially filled with different PCMs (phase change materials) to a steep demand," Energy, Elsevier, vol. 91(C), pages 202-214.
    16. Ángel A. Bayod-Rújula & Juan A. Tejero-Gómez, 2022. "Analysis of the Hybridization of PV Plants with a BESS for Annual Constant Power Operation," Energies, MDPI, vol. 15(23), pages 1-18, November.
    17. Gaucher-Loksts, Erin & Athienitis, Andreas & Ouf, Mohamed, 2022. "Design and energy flexibility analysis for building integrated photovoltaics-heat pump combinations in a house," Renewable Energy, Elsevier, vol. 195(C), pages 872-884.
    18. Shukla, Ruchi & Sumathy, K. & Erickson, Phillip & Gong, Jiawei, 2013. "Recent advances in the solar water heating systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 173-190.
    19. Kicsiny, Richárd, 2018. "Black-box model for solar storage tanks based on multiple linear regression," Renewable Energy, Elsevier, vol. 125(C), pages 857-865.
    20. Luca Urbanucci & Francesco D’Ettorre & Daniele Testi, 2019. "A Comprehensive Methodology for the Integrated Optimal Sizing and Operation of Cogeneration Systems with Thermal Energy Storage," Energies, MDPI, vol. 12(5), pages 1-17, March.

    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:renene:v:219:y:2023:i:p2:s096014812301426x. 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.journals.elsevier.com/renewable-energy .

    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.