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Study on the optimal heat supply control algorithm for district heating distribution network in response to outdoor air temperature

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Listed:
  • Byun, Sun-Joon
  • Park, Hyun-Sik
  • Yi, Sung-Jae
  • Song, Chul-Hwa
  • Choi, Young-Don
  • Lee, So-Hyeon
  • Shin, Jong-Keun

Abstract

In the present study, a heat supply control algorithm was developed that minimizes the rate of heat loss in the heat distribution lines of district heating community buildings. This algorithm simultaneously controlled the supply water temperature and flow rate in response to the outdoor air temperature to minimize the heat loss rate in a distribution line. The total heat supply through the distribution lines of community buildings in Hwaseong, Gyeonggi, South Korea, was compared with the total heat consumption of all households. It was revealed that 24.1% of the heat supply to the community buildings was lost in the distribution lines. By simultaneously controlling the supply water temperature and flow rate in response to the outdoor air temperature, the developed algorithm could reduce the heat loss by 11.5%.

Suggested Citation

  • Byun, Sun-Joon & Park, Hyun-Sik & Yi, Sung-Jae & Song, Chul-Hwa & Choi, Young-Don & Lee, So-Hyeon & Shin, Jong-Keun, 2015. "Study on the optimal heat supply control algorithm for district heating distribution network in response to outdoor air temperature," Energy, Elsevier, vol. 86(C), pages 247-256.
    • Handle: RePEc:eee:energy:v:86:y:2015:i:c:p:247-256
    DOI: 10.1016/j.energy.2015.04.029
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    References listed on IDEAS

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    1. Knutsson, David & Sahlin, Jenny & Werner, Sven & Ekvall, Tomas & Ahlgren, Erik O., 2006. "HEATSPOT—a simulation tool for national district heating analyses," Energy, Elsevier, vol. 31(2), pages 278-293.
    2. Jae-Ki Byun & Dong-Hwa Jeong & Young-Don Choi & Jong-Keun Shin, 2013. "Analysis of Fuel Cell Driven Ground Source Heat Pump Systems in Community Buildings," Energies, MDPI, vol. 6(5), pages 1-18, May.
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    Citations

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    Cited by:

    1. Kim, Ryunhee & Hong, Yejin & Choi, Youngwoong & Yoon, Sungmin, 2021. "System-level fouling detection of district heating substations using virtual-sensor-assisted building automation system," Energy, Elsevier, vol. 227(C).
    2. Wang, Hai & Meng, Hua, 2018. "Improved thermal transient modeling with new 3-order numerical solution for a district heating network with consideration of the pipe wall's thermal inertia," Energy, Elsevier, vol. 160(C), pages 171-183.
    3. Li, Yu & Rezgui, Yacine & Zhu, Hanxing, 2017. "District heating and cooling optimization and enhancement – Towards integration of renewables, storage and smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 281-294.
    4. Heng Chen & Jidong Xu & Yao Xiao & Zhen Qi & Gang Xu & Yongping Yang, 2018. "An Improved Heating System with Waste Pressure Utilization in a Combined Heat and Power Unit," Energies, MDPI, vol. 11(6), pages 1-20, June.
    5. Zhihua Ge & Fuxiang Zhang & Shimeng Sun & Jie He & Xiaoze Du, 2018. "Energy Analysis of Cascade Heating with High Back-Pressure Large-Scale Steam Turbine," Energies, MDPI, vol. 11(1), pages 1-15, January.
    6. Wang, Hai & Wang, Haiying & Haijian, Zhou & Zhu, Tong, 2017. "Optimization modeling for smart operation of multi-source district heating with distributed variable-speed pumps," Energy, Elsevier, vol. 138(C), pages 1247-1262.
    7. Nigitz, Thomas & Gölles, Markus, 2019. "A generally applicable, simple and adaptive forecasting method for the short-term heat load of consumers," Applied Energy, Elsevier, vol. 241(C), pages 73-81.

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