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Model Predictive Control with Adaptive Building Model for Heating Using the Hybrid Air-Conditioning System in a Railway Station

Author

Listed:
  • Ruixin Lv

    (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

  • Zhongyuan Yuan

    (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

  • Bo Lei

    (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

  • Jiacheng Zheng

    (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

  • Xiujing Luo

    (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

Abstract

A model predictive control (MPC) system with an adaptive building model based on thermal-electrical analogy for the hybrid air conditioning system using the radiant floor and all-air system for heating is proposed in this paper to solve the heating supply control difficulties of the railway station on Tibetan Plateau. The MPC controller applies an off-line method of updating the building model to improve the accuracy of predicting indoor conditions. The control performance of the adaptive MPC is compared with the proportional-integral-derivative (PID) control, as well as an MPC without adaptive model through simulation constructed based on a TRNSYS-MATLAB co-simulation testbed. The results show that the implementation of the adaptive MPC can improve indoor thermal comfort and reduce 22.2% energy consumption compared to the PID control. Compared to the MPC without adaptive model, the adaptive MPC achieves fewer violations of constraints and reduces energy consumption by 11.5% through periodic model updating. This study focuses on the design of a control system to maintain indoor thermal comfort and improve system efficiency. The proposed method could also be applied in other public buildings.

Suggested Citation

  • Ruixin Lv & Zhongyuan Yuan & Bo Lei & Jiacheng Zheng & Xiujing Luo, 2021. "Model Predictive Control with Adaptive Building Model for Heating Using the Hybrid Air-Conditioning System in a Railway Station," Energies, MDPI, vol. 14(7), pages 1-22, April.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:7:p:1996-:d:530228
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    References listed on IDEAS

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    1. Wang, Zhe & Luo, Maohui & Geng, Yang & Lin, Borong & Zhu, Yingxin, 2018. "A model to compare convective and radiant heating systems for intermittent space heating," Applied Energy, Elsevier, vol. 215(C), pages 211-226.
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    4. Yang, Shiyu & Wan, Man Pun & Chen, Wanyu & Ng, Bing Feng & Dubey, Swapnil, 2020. "Model predictive control with adaptive machine-learning-based model for building energy efficiency and comfort optimization," Applied Energy, Elsevier, vol. 271(C).
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    Cited by:

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