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Experimental investigation on model predictive control of radiant floor cooling combined with underfloor ventilation system

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  • Zhang, Dongliang
  • Cai, Ning
  • Cui, Xiaobo
  • Xia, Xueying
  • Shi, Jianzhong
  • Huang, Xiaoqing

Abstract

Energy saving potential of radiant floor cooling combined with underfloor ventilation (RFCUV) system has been restricted by its control problems. Existing conventional control methods of radiant cooling system have several disadvantages, such as control lag, poor control performance, and low economy, etc. The objectives of this study were to: (i) build a dynamic simplified model and validate its precision experimentally; (ii) implement advanced model predictive control (MPC) on RFCUV system; and (iii) demonstrate MPC control performance by comparing with existing conventional proportional-integral-derivative (PID) experimentally. Experimental results indicated that under experimental step setpoint variations, the adjusting time of indoor air temperature or operative temperature was only 12 min with MPC controller, and was 30 min with PID controller; it took only 1 min to reach recommended thermal comfort range with MPC controller, and 17 min with PID controller. During 9:00 to 17:00 in typical design day of Nanjing city, compared with PID controller, MPC controller yielded 17.5% energy saving when maintaining equal or better indoor comfort. Thus, compared with PID, MPC demonstrated the advantages of rapid responses, good stability and excellent energy saving effect in RFCUV system.

Suggested Citation

  • Zhang, Dongliang & Cai, Ning & Cui, Xiaobo & Xia, Xueying & Shi, Jianzhong & Huang, Xiaoqing, 2019. "Experimental investigation on model predictive control of radiant floor cooling combined with underfloor ventilation system," Energy, Elsevier, vol. 176(C), pages 23-33.
    • Handle: RePEc:eee:energy:v:176:y:2019:i:c:p:23-33
    DOI: 10.1016/j.energy.2019.03.102
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    References listed on IDEAS

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    1. Antonopoulos, K.A. & Tzivanidis, C., 1997. "Numerical solution of unsteady three-dimensional heat transfer during space cooling using ceiling-embedded piping," Energy, Elsevier, vol. 22(1), pages 59-67.
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    Cited by:

    1. Brown, Sarah & Beausoleil-Morrison, Ian, 2023. "Long-term implementation of a model predictive controller for a hydronic floor heating and cooling system in a highly glazed house in Canada," Applied Energy, Elsevier, vol. 349(C).
    2. Duan, Mengfan & Sun, Hongli & Wu, Shuangdui & Wu, Yifan & Lin, Borong, 2023. "A simplified model for the evaluation and comparison of the dynamic performance of different heating terminal types," Energy, Elsevier, vol. 263(PD).
    3. Xie, Xing & Xia, Fei & Zhao, Yu-qian & Xu, Bin & Wang, Yang-liang & Pei, Gang, 2022. "Parametric study on the effect of radiant heating system on indoor thermal comfort with/without external thermal disturbance," Energy, Elsevier, vol. 249(C).
    4. María M. Villar-Ramos & Iván Hernández-Pérez & Karla M. Aguilar-Castro & Ivett Zavala-Guillén & Edgar V. Macias-Melo & Irving Hernández-López & Juan Serrano-Arellano, 2022. "A Review of Thermally Activated Building Systems (TABS) as an Alternative for Improving the Indoor Environment of Buildings," Energies, MDPI, vol. 15(17), pages 1-31, August.
    5. Wan, Xin & Luo, Xiong-Lin, 2020. "Economic optimization of chemical processes based on zone predictive control with redundancy variables," Energy, Elsevier, vol. 212(C).
    6. Karl-Villem Võsa & Andrea Ferrantelli & Jarek Kurnitski, 2022. "Cooling Thermal Comfort and Efficiency Parameters of Ceiling Panels, Underfloor Cooling, Fan-Assisted Radiators, and Fan Coil," Energies, MDPI, vol. 15(11), pages 1-19, June.
    7. Hua, Pengmin & Wang, Haichao & Xie, Zichan & Lahdelma, Risto, 2024. "Multi-criteria evaluation of novel multi-objective model predictive control method for indoor thermal comfort," Energy, Elsevier, vol. 289(C).
    8. Dongsu Kim & Jongman Lee & Sunglok Do & Pedro J. Mago & Kwang Ho Lee & Heejin Cho, 2022. "Energy Modeling and Model Predictive Control for HVAC in Buildings: A Review of Current Research Trends," Energies, MDPI, vol. 15(19), pages 1-30, October.

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