IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i19p6849-d1249314.html
   My bibliography  Save this article

Simple and Accurate Model of Thermal Storage with Phase Change Material Tailored for Model Predictive Control

Author

Listed:
  • Filip Vrbanc

    (Laboratory for Renewable Energy Systems, Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia)

  • Mario Vašak

    (Laboratory for Renewable Energy Systems, Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia)

  • Vinko Lešić

    (Laboratory for Renewable Energy Systems, Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia)

Abstract

Thermal heat storage is becoming important in systems with renewable energy sources. Their largest benefit is smoothing the intermittent production and reduction in the site peak demand. The advantages of thermal energy storage with phase-change material are storing energy at a lower temperature for reduction in thermal losses, and enabling energy transfer at a constant temperature, which reduces the risk of equipment damage. In this paper, a low-order model of latent thermal energy storage, derived in a state-space form by using the mixed logical dynamical approach, is proposed. The model is compared to a stratified model and shows significant improvements of physical accuracy and execution time. Finally, a model predictive control algorithm suited for the real case study is designed, implemented and compared to classical rule-based control. The obtained results show significant energy savings of 8.43%, and improvements in user comfort and equipment duration.

Suggested Citation

  • Filip Vrbanc & Mario Vašak & Vinko Lešić, 2023. "Simple and Accurate Model of Thermal Storage with Phase Change Material Tailored for Model Predictive Control," Energies, MDPI, vol. 16(19), pages 1-18, September.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:19:p:6849-:d:1249314
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/19/6849/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/19/6849/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sanghoon Baek & Sangchul Kim, 2019. "Analysis of Thermal Performance and Energy Saving Potential by PCM Radiant Floor Heating System based on Wet Construction Method and Hot Water," Energies, MDPI, vol. 12(5), pages 1-17, March.
    2. Lu, Yuehong & Wang, Shengwei & Sun, Yongjun & Yan, Chengchu, 2015. "Optimal scheduling of buildings with energy generation and thermal energy storage under dynamic electricity pricing using mixed-integer nonlinear programming," Applied Energy, Elsevier, vol. 147(C), pages 49-58.
    3. Gholamibozanjani, Gohar & Farid, Mohammed, 2020. "Application of an active PCM storage system into a building for heating/cooling load reduction," Energy, Elsevier, vol. 210(C).
    4. Bürger, Adrian & Bohlayer, Markus & Hoffmann, Sarah & Altmann-Dieses, Angelika & Braun, Marco & Diehl, Moritz, 2020. "A whole-year simulation study on nonlinear mixed-integer model predictive control for a thermal energy supply system with multi-use components," Applied Energy, Elsevier, vol. 258(C).
    5. Mazzoni, Stefano & Sze, Jia Yin & Nastasi, Benedetto & Ooi, Sean & Desideri, Umberto & Romagnoli, Alessandro, 2021. "A techno-economic assessment on the adoption of latent heat thermal energy storage systems for district cooling optimal dispatch & operations," Applied Energy, Elsevier, vol. 289(C).
    6. Heine, Karl & Tabares-Velasco, Paulo Cesar & Deru, Michael, 2021. "Design and dispatch optimization of packaged ice storage systems within a connected community," Applied Energy, Elsevier, vol. 298(C).
    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. Xiaoyu Xu & Chun Chang & Xinxin Guo & Mingzhi Zhao, 2023. "Experimental and Numerical Study of the Ice Storage Process and Material Properties of Ice Storage Coils," Energies, MDPI, vol. 16(14), pages 1-18, July.
    2. 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).
    3. Najafi, Arsalan & Falaghi, Hamid & Contreras, Javier & Ramezani, Maryam, 2016. "Medium-term energy hub management subject to electricity price and wind uncertainty," Applied Energy, Elsevier, vol. 168(C), pages 418-433.
    4. Liu, Liu & Niu, Jianlei & Wu, Jian-Yong, 2023. "Improving energy efficiency of photovoltaic/thermal systems by cooling with PCM nano-emulsions: An indoor experimental study," Renewable Energy, Elsevier, vol. 203(C), pages 568-582.
    5. Gianluca Serale & Massimo Fiorentini & Alfonso Capozzoli & Daniele Bernardini & Alberto Bemporad, 2018. "Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities," Energies, MDPI, vol. 11(3), pages 1-35, March.
    6. Kong, Xiangfei & Jiang, Lina & Yuan, Ye & Qiao, Xu, 2022. "Experimental study on the performance of an active novel vertical partition thermal storage wallboard based on composite phase change material with porous silica and microencapsulation," Energy, Elsevier, vol. 239(PE).
    7. Huang, Pei & Wu, Hunjun & Huang, Gongsheng & Sun, Yongjun, 2018. "A top-down control method of nZEBs for performance optimization at nZEB-cluster-level," Energy, Elsevier, vol. 159(C), pages 891-904.
    8. Zhao, Yaohua & Liu, Zichu & Quan, Zhenhua & Jing, Heran & Yang, Mingguang, 2022. "Experimental investigation and multi-objective optimization of ice thermal storage device with multichannel flat tube," Renewable Energy, Elsevier, vol. 195(C), pages 28-46.
    9. Golpîra, Hêriş & Khan, Syed Abdul Rehman, 2019. "A multi-objective risk-based robust optimization approach to energy management in smart residential buildings under combined demand and supply uncertainty," Energy, Elsevier, vol. 170(C), pages 1113-1129.
    10. Chai, Jiale & Huang, Pei & Sun, Yongjun, 2019. "Investigations of climate change impacts on net-zero energy building lifecycle performance in typical Chinese climate regions," Energy, Elsevier, vol. 185(C), pages 176-189.
    11. Fabio Magrassi & Adriana Del Borghi & Michela Gallo & Carlo Strazza & Michela Robba, 2016. "Optimal Planning of Sustainable Buildings: Integration of Life Cycle Assessment and Optimization in a Decision Support System (DSS)," Energies, MDPI, vol. 9(7), pages 1-15, June.
    12. Castilla Manuel V. & Martin Francisco, 2021. "A Powerful Tool for Optimal Control of Energy Systems in Sustainable Buildings: Distortion Power Bivector," Energies, MDPI, vol. 14(8), pages 1-17, April.
    13. Wang, Chengshan & Jiao, Bingqi & Guo, Li & Tian, Zhe & Niu, Jide & Li, Siwei, 2016. "Robust scheduling of building energy system under uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 366-376.
    14. Huang, Pei & Sun, Yongjun, 2019. "A collaborative demand control of nearly zero energy buildings in response to dynamic pricing for performance improvements at cluster level," Energy, Elsevier, vol. 174(C), pages 911-921.
    15. Parhizkar, Tarannom & Mosleh, Ali & Roshandel, Ramin, 2017. "Aging based optimal scheduling framework for power plants using equivalent operating hour approach," Applied Energy, Elsevier, vol. 205(C), pages 1345-1363.
    16. Zheng, Nan & Zhang, Hanfei & Duan, Liqiang & Wang, Qiushi & Bischi, Aldo & Desideri, Umberto, 2023. "Techno-economic analysis of a novel solar-driven PEMEC-SOFC-based multi-generation system coupled parabolic trough photovoltaic thermal collector and thermal energy storage," Applied Energy, Elsevier, vol. 331(C).
    17. Lu, Yuehong & Wang, Shengwei & Yan, Chengchu & Shan, Kui, 2015. "Impacts of renewable energy system design inputs on the performance robustness of net zero energy buildings," Energy, Elsevier, vol. 93(P2), pages 1595-1606.
    18. Parantapa Sawant & Oscar Villegas Mier & Michael Schmidt & Jens Pfafferott, 2021. "Demonstration of Optimal Scheduling for a Building Heat Pump System Using Economic-MPC," Energies, MDPI, vol. 14(23), pages 1-15, November.
    19. Hlanze, Philani & Jiang, Zhimin & Cai, Jie & Shen, Bo, 2023. "Model-based predictive control of multi-stage air-source heat pumps integrated with phase change material-embedded ceilings," Applied Energy, Elsevier, vol. 336(C).
    20. Thomas, Dimitrios & Deblecker, Olivier & Ioakimidis, Christos S., 2018. "Optimal operation of an energy management system for a grid-connected smart building considering photovoltaics’ uncertainty and stochastic electric vehicles’ driving schedule," Applied Energy, Elsevier, vol. 210(C), pages 1188-1206.

    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:gam:jeners:v:16:y:2023:i:19:p:6849-:d:1249314. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.