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Thermo-hydraulic condition optimization of large-scale complex district heating network: A case study of Tianjin

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  • Zheng, Xuejing
  • Shi, Zhiyuan
  • Wang, Yaran
  • Zhang, Huan
  • Liu, Huzhen

Abstract

District heating (DH) networks are indispensable infrastructure for space and domestic heating with high energy efficiency. As the structures of DH networks are gradually becoming complex, efficient and accurate simulation model for the operational optimization of the DH network is crucial. In this paper, an optimization method for the DH network operation is proposed. The method is based on the thermo-hydraulic coupled dynamic model, sequential quadratic programming (SQP) and particle swarm optimization (PSO), which is applied to a large-scale DH network in Tianjin, China. With the proposed method, 6.7%∼11% energy consumption can be reduced, under the operation condition of 80%∼100% design flow rate. The transmission and distribution cost can be reduced with an average of 6.2% at the outdoor temperature ranging from −5 to 5 °C.

Suggested Citation

  • Zheng, Xuejing & Shi, Zhiyuan & Wang, Yaran & Zhang, Huan & Liu, Huzhen, 2023. "Thermo-hydraulic condition optimization of large-scale complex district heating network: A case study of Tianjin," Energy, Elsevier, vol. 266(C).
    • Handle: RePEc:eee:energy:v:266:y:2023:i:c:s0360544222032923
    DOI: 10.1016/j.energy.2022.126406
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    Cited by:

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    3. Che, Zichang & Sun, Jingchao & Na, Hongming & Yuan, Yuxing & Qiu, Ziyang & Du, Tao, 2023. "A novel method for intelligent heating: On-demand optimized regulation of hydraulic balance for secondary networks," Energy, Elsevier, vol. 282(C).
    4. Liu, Zhikai & Zhang, Huan & Wang, Yaran & Fan, Xianwang & You, Shijun & Jiang, Yan & Gao, Xinlei, 2023. "Optimization of hydraulic distribution using loop adjustment method in meshed district heating system with multiple heat sources," Energy, Elsevier, vol. 284(C).
    5. Zheng, Xuejing & Shi, Zhiyuan & Wang, Yaran & Zhang, Huan & Tang, Zhiyun, 2024. "Digital twin modeling for district heating network based on hydraulic resistance identification and heat load prediction," Energy, Elsevier, vol. 288(C).

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