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A simplified model for the evaluation and comparison of the dynamic performance of different heating terminal types

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  • Duan, Mengfan
  • Sun, Hongli
  • Wu, Shuangdui
  • Wu, Yifan
  • Lin, Borong

Abstract

Continuous space heating may cause the excessive energy utilization. Part-time heating, which aims to being in line with the flexible usage habits of occupants, is widely highlighted for energy conservation. For this purpose, various heating terminals have been developed, and the dynamic heating performance evaluation is urgent for the optimal application. However, conventional analysis methods are complex and difficult for performance comparison between large quantities of terminals. Therefore, in this study, a simplified resistance–capacity model was developed for performance analysis. With the concept of normalization, the model is built in a unified form for different terminal types, based on the heat transfer process of “heat source–terminal–indoor environment”, greatly facilitating the performance comparison. Three thermal parameters that directly reflect the heat transfer characteristics of terminal were excavated as model parameters, conducive to determine the core process limiting the dynamic heating. Compared with the experimental results, the maximum error of thermal node temperature and heat flux was 1.15 °C and 14.4%, respectively, confirming the accuracy content with engineering requirement. In addition, the feasibility of the model for heating performance comparison, and optimization strategy evaluation for various terminal types was explored, to maximize the energy-saving and comfort potential of terminals.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:263:y:2023:i:pd:s0360544222028274
    DOI: 10.1016/j.energy.2022.125941
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    References listed on IDEAS

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    1. Zhang, Chengyu & Ma, Liangdong & Han, Xing & Zhao, Tianyi, 2024. "Reconstituted data-driven air conditioning energy consumption prediction system employing occupant-orientated probability model as input and swarm intelligence optimization algorithms," Energy, Elsevier, vol. 288(C).

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