International Scientific Journal

Thermal Science - Online First

Authors of this Paper

External Links

online first only

Application and effect analysis of heating system based on tri-network joint regulation and control technology

In recent years, the state promotes intelligent heating and clean heating, which aims to achieve energy saving, emission reduction, cost reduction and efficiency, and improve the social and economic benefits of heating enterprises on the premise of ensuring the heat demand of the terminal heat users of the heating system. This paper first introduces the current situation of the heating system, analyzes the main problems and causes of the current heating system, and then analyzes the practical application and operation data of the three-network joint control technology of the heating system independently developed by Jilin Yuheng Industrial Electric Co., Ltd in Changchun Lianhuashan Thermal Power Co., Ltd., and finally comes to the conclusion that the application of this technology makes the heating system energy-saving effect is remarkable. It can adapt to all kinds of complex heating systems and has good market prospect and application value.
PAPER REVISED: 2020-09-17
PAPER ACCEPTED: 2020-09-29
  1. Wang, Z. et al., Study on thermal adaptability of human body in severe cold areas (4): field study on thermal environment and thermal adaptation of different buildings. HVAC, 47 (2017), 08, pp. 103-108
  2. Wong, L. T. et al., An open acceptance model for indoor environmental quality (IEQ). Building and Environment, 142(2018), 9, pp.371-378.
  3. Cadau, N. et al., A Model-in-the-Loop application of a Predictive Controller to a District Heating system. Energy Procedia, 148 (2018), pp.352-359.
  4. Feng, H. et al., Energy-saving analysis of central heating of existing non-energy-saving residential buildings in typical cities in northern China. Journal of Shenyang Architectural University (Natural Science Edition), 34(2018), 02, pp. 323-332
  5. Li L. et al. Optimal control strategy and simulation of central heating secondary network. Heating and Refrigeration, 01(2019), pp. 23-26
  6. Yu, D. et al., Application of energy efficiency evaluation system for heat exchange stations in cold areas. Heating, ventilation and Air conditioning, 49(2019), 3, pp. 78-79
  7. Han, F. et al., Test and Analysis of Indoor Thermal Environment of Central heating Residential buildings in Qingdao. Journal of Qingdao University of Technology, 38(2017), 03, pp. 64-69
  8. Wang, Y. et al., Accurate model reduction and control of radiator for performance enhancement of room heating system. Energy and Buildings, 138(2017), 3, pp.415-431.
  9. He, K. et al., Dynamic simulation of steam-water heat exchanger station in heating network. Journal of Tsinghua University (Natural Science Edition), 43(2003), 12, pp. 1679-1683
  10. Samuel, P. et al., Model predictive control of a building heating system: The first experience. Energy & Buildings, 43(2011), 2-3, pp.564-572.
  11. De, Dear, and Richard, J. A global database of thermal comfort field experiments." ASHRAE transactions, 104 (1998), pp. 1141.
  12. Hedegaard, R., et al., Towards practical model predictive control of residential space heating: Eliminating the need for weather measurements." Energy and Buildings 170 (2018): 206-216.
  13. Li, B. et al., Investigation and comprehensive evaluation of heating model in some rural areas of northern China. HVAC, 47 (2017),04, pp. 46-51
  14. Yu, X. Combustion optimization control system of chain furnace based on BCS technology. Chlor-alkali industry, (2015) 4, pp. 39-43.
  15. Han, X. Effect of excess air coefficient on thermal efficiency of boiler. Journal of Shaanxi Institute of Technology, 18 (2002), 4, pp. 56-58.
  16. CJJ34-2010 (2010 Edition), Code for Design of Urban heating Network. Beijing: China Construction Industry Press, 2010.