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Mathematical model of flow distribution in an individual heating station

https://doi.org/10.24223/1999-5555-2026-19-2-127-134

Abstract

Mathematical modeling of thermal and hydraulic conditions in individual heating substations (IHS) is a priority task for the design, adjustment, and dispatching of heat supply systems as a whole. IHSs serve as the link between heating networks and building engineering systems, so their reliability and safety largely depend on correct design decisions, which are impossible without the development of adequate mathematical models. Solutions are needed that will significantly improve the quality of heat supply regulation at IHSs. The use of a mathematical model of IHSs will also enable planning of measures for the rational use of energy resources. The reliability of IHS pipeline networks requires closer attention to design decisions. Thus, refined mathematical models of heating substations allow for both capital savings and reliable transportation of heat energy.

Objective: To develop a mathematical model of flow distribution in an individual heating substation to ensure the reliability and safety of district heating systems in real time. Methods: Computer modeling of flow distribution at individual heating substations (IHSs) with various characteristics and connection schemes to district heating networks. Results: A mathematical model of an IHS is proposed, enabling the assessment of its operational reliability through the use of computer and software technologies. Software was developed for taking measurements in real time. It is shown that regulation of heat flows does not always correspond to the actual needs of buildings, which can lead to an incorrect assessment of specific heat losses. Conclusions: The constructed mathematical model of a heating substation allows a sufficiently complete picture of the flow distribution state in an IHS to be obtained and an assessment of the reliability of heat supply to buildings and structures.

About the Authors

M. V. Kolosov
Siberian Federal University Russia
Russian Federation

660041, Krasnoyarsk, Svobodny Ave., 79



U. L. Lipovka
Siberian Federal University Russia
Russian Federation

660041, Krasnoyarsk, Svobodny Ave., 79



V. I. Panfilov
Siberian Federal University Russia
Russian Federation

660041, Krasnoyarsk, Svobodny Ave., 79



References

1. Current status, trends, and challenges of heat supply systems intellectualization (review). N. N. Novitsky, Z. I. Shalaginova, A. V. Alekseev [et al.]. Thermal Power Engineering 2022; (5): 65 – 83. DOI 10.1134/S0040363622040051. EDN LJDTZX.

2. Digitalization and digital transformation of thermal power engineering as a factor in increasing the efficiency of thermal infrastructure (review). E. Yu. Golovina, E. V. Samarkina, N. E. Buynov, M. V. Evloeva. Thermal Power Engineering 2022; (6): 3 – 16. DOI 10.1134/S0040363622060042. EDN FJUVAB.

3. Bingwen Zhao, Hanyu Zheng, Ruxue Yan. Heat Distribution by a Heating Substation of a District Heating System Based on Load Forecasting. Thermal Power Engineering 2024; (4): 89 – 100. DOI 10.56304/S0040363624040088. EDN FTGZME.

4. Kolosov M. V., Lipovka A. Yu., Lipovka Yu. L. Heat Consumption Monitoring System for Buildings. Bulletin of Tomsk Polytechnic University. Georesources Engineering 2024; 335(7): 206 – 220. DOI 10.18799/24131830/2024/7/4443. EDN ZKPPUO.

5. Petrushchenkov V. A. Calculation of Operating Modes of District Heating Systems under Non-Design Conditions. Thermal Power Engineering 2022; (5): 84–94. DOI 10.1134/S0040363622050046. EDN VXNYVF.

6. Calculation of the Price Field for Thermal Energy Based on the Extremum Problem of Finding the Optimal Flow Distribution in Heat Supply Systems. V. A. Stennikov, O. V. Khamisov, A. V. Penkovsky, A. A. Kravets. Thermal Power Engineering 2024; (1): 41 – 49. DOI 10.56304/S0040363624010077. EDN HBZTLR.

7. Forecasting Energy Efficiency in the Fuel and Energy Complex Based on the MLP Model. I. U. Rakhmonov, Z. M. Shayumova, V. Ya. Ushakov, N. N. Niyozov, D. A. Zhalilova. Bulletin of the Tomsk Polytechnic University. Georesources Engineering. 2026; 337 (1): 213 – 227.

8. Zhuan S., Mamonova T. E., Khudonogova L. I. Modeling a hardware and software system for monitoring the rate of change of liquid or gas pressure in a pipeline. Bulletin of Tomsk Polytechnic University. Georesources Engineering 2025; 336 (9): 124 – 151.

9. Dan Wang, Wanfu Zheng, Zhe Wang, Zhifu Wu, Baiqiang Shen, Shiming Tian, Quantifying the potential of load flexibility for a building HVAC system using a model predictive control strategy, Energy and Buildings, Volume 323, 2024, 114819, ISSN 0378-7788, https://doi.org/10.1016/j.enbuild.2024.114819

10. Saman Taheri, Alireza Jafarian Amiri, Ali Razban, Real-world implementation of a cloud-based MPC for HVAC control in educational buildings, Energy Conversion and Management, Volume 305, 2024, 118270, ISSN 0196-8904, https://doi.org/10.1016/j.enconman.2024.118270


Review

For citations:


Kolosov M.V., Lipovka U.L., Panfilov V.I. Mathematical model of flow distribution in an individual heating station. Safety and Reliability of Power Industry. 2026;19(2):127-134. (In Russ.) https://doi.org/10.24223/1999-5555-2026-19-2-127-134

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ISSN 1999-5555 (Print)
ISSN 2542-2057 (Online)