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An intelligent control and regulation strategy aiming at building level heating balance in district heating system

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Listed:
  • Sun, Chunhua
  • Yuan, Lingyu
  • Chen, Yun
  • Cao, Shanshan
  • Xia, Guoqiang
  • Qi, Chengying
  • Wu, Xiangdong

Abstract

In district heating system (DHS), hydraulic imbalance has hindered further energy saving, which results in high energy consumption and meaningless heat loss. This issue is particularly serious in the building side whose scale and structure are more complex than that of heat exchange station (HES) side. Focusing on the building side balance, this paper proposed a building level intelligent balancing system and corresponding control strategy. The balancing system featuring smart valves installed at the building entrance, adjust the valves opening according to target return temperature to accommodate the heat distribution among buildings. A dynamic calculation model coupling a linear correction is established to decide the target return temperature of each smart valves considering buildings’ thermal characteristics. The proposed intelligent balance system is applied to a practical district heating system. The unregulated indoor temperature ranges from 20.9 °C–25.2 °C, while a smaller range of 22.6–24.0 °C after regulation. The results indicated that the hydraulic and thermal imbalance among buildings were significantly improved with regulation. Moreover, the heat consumption index was reduced and an energy saving rate of 3.73% was achieved. This study provides a reference for similar building side pipe network balance regulation.

Suggested Citation

  • Sun, Chunhua & Yuan, Lingyu & Chen, Yun & Cao, Shanshan & Xia, Guoqiang & Qi, Chengying & Wu, Xiangdong, 2023. "An intelligent control and regulation strategy aiming at building level heating balance in district heating system," Energy, Elsevier, vol. 278(PB).
    • Handle: RePEc:eee:energy:v:278:y:2023:i:pb:s036054422301335x
    DOI: 10.1016/j.energy.2023.127941
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    References listed on IDEAS

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    1. Sun, Chunhua & Chen, Jiali & Cao, Shanshan & Gao, Xiaoyu & Xia, Guoqiang & Qi, Chengying & Wu, Xiangdong, 2021. "A dynamic control strategy of district heating substations based on online prediction and indoor temperature feedback," Energy, Elsevier, vol. 235(C).
    2. Benakopoulos, Theofanis & Tunzi, Michele & Salenbien, Robbe & Svendsen, Svend, 2021. "Strategy for low-temperature operation of radiator systems using data from existing digital heat cost allocators," Energy, Elsevier, vol. 231(C).
    3. Ashfaq, Asad & Ianakiev, Anton, 2018. "Investigation of hydraulic imbalance for converting existing boiler based buildings to low temperature district heating," Energy, Elsevier, vol. 160(C), pages 200-212.
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    Cited by:

    1. Hiris, Daniel P. & Pop, Octavian G. & Dobrovicescu, Alexandru & Dudescu, Mircea C. & Balan, Mugur C., 2023. "Modelling of solar assisted district heating system with seasonal storage tank by two mathematical methods and with two climatic data as input," Energy, Elsevier, vol. 284(C).
    2. Guo, Chengke & Zhang, Ji & Yuan, Han & Yuan, Yonggong & Wang, Haifeng & Mei, Ning, 2024. "Informer-based model predictive control framework considering group controlled hydraulic balance model to improve the precision of client heat load control in district heating system," Applied Energy, Elsevier, vol. 373(C).
    3. Sun, Chunhua & Yan, Hao & Yuan, Lingyu & Cao, Shanshan & Ma, Weichi & Suo, Chenyu & Qi, Chengying & Wu, Xiangdong, 2024. "A refined classification method of heat customers to improve inter-household thermal balance intelligent control and regulation," Energy, Elsevier, vol. 304(C).

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