Improving the Efficiency of the Design Stage of the Life Cycle of the Heat Supply System of a Construction Facility

Introduction. The heat supply system is one of the most important infrastructural components of the engineering support of the construction site. However, the process of modeling its life cycle, particularly in terms of information support, has not been sufficiently researched in the academia.

One of the main stages of the life cycle of any engineering system is design. The need to increase energy efficiency, reduce the cost of designing and, thereby, building central heating systems, and improve the environmental situation highlights the special urgency of introducing innovative technologies, in particular, artificial intelligence that can become an effective tool for solving the existing problems. The aim of the study is to increase the efficiency of the design stage of district heating systems based on the use of artificial intelligence and to assess the prospects for such an approach.

Materials and Methods. The research methodology includes comparative analysis, modeling, statistical data processing and expert assessment. The research results can be used in the development of new approaches to the design of heat supply systems using modern digital technologies.

Research Results. The proposed concept of life cycle management of heat supply systems, which includes the sequential implementation of five key stages (from pre-design preparation to disposal) allows for an integrated approach to optimizing all of the processes. At the same time, the design stage, which determines the basic parameters of energy efficiency, efficiency and reliability of heat supply, is of critical importance. In the context of digitalization of thermal power engineering, the integration of intelligent automated systems implementing multifactorial algorithmic modeling and optimization calculations is becoming particularly relevant. Modern artificial intelligence-based solutions provide comprehensive automation of design and engineering work, including creating detailed information models of facilities, high-precision forecasting of heat consumption, hydraulic control and optimization of the energy balance of the system. The introduction of such technologies not only compensates for the lack of qualified specialists and improves the quality of project documentation, but also contributes to significant optimization of operational performance: reducing fuel costs and minimizing the carbon footprint through rational allocation of energy resources and reduction in greenhouse gas emissions.

Discussion and Conclusion. The article discusses modern approaches to automated design of district heating systems using artificial intelligence technologies. A technique based on the use of machine learning, neural networks, and optimization algorithms is proposed to improve design efficiency, minimize energy loss, and reduce operating costs.

1. Zhdanov VYu A New Look at the Stages of the Organization's Life Cycle. Moscow Economic Journal. 2021;6:378–388. (In Russ.) URL: https://gclnk.com/W9hQ7Iaa (accessed: 12.09.2025)

2. Agibalova VG, Basha IV, Subbota AV, Wassuf FS Features of Organization Management Taking into Account the Stages of the Life Cycle. Natural Sciences and Humanities Research. 2023;5(49):367-370. (In Russ.) URL: https://academiyadt.ru/online-zhurnal-estestvenno-gumanitarnye-issledovaniya-egi-49/ (accessed: 12.09.2025).

3. Fedosov SV, Fedoseev VN, Zayceva IA, Voronov VA Life Сycle Management of the Steady State of the Construction Object. Expert: Theory and Practice. 2023;3(22):131–137. (In Russ.) http://doi.org/10.51608/26867818_2023_3_131

4. Topchiy DV Organizational and Technical Solutions to Ensure the Quality of Construction and Installation Works at Various Stages of the Life Cycle of a Construction Project. Bulletin of MGSU. 2023;18(2):283–292. (In Russ.) http://doi.org/10.22227/1997-0935.2023.2.283-292

5. Bespalov VI, Gurova OS, Lysova EP, Grishin GS Life Cycle of Analysis of Steam and Gas Turbine CHP Plants. Modern Trends in Construction, Urban and Territorial Planning. 2022;1(4):32–43. (In Russ.) https://doi.org/10.23947/2949-1835-2022-1-4-32-43

6. Tikhomirov AL, Pirozhnikova AP Creating Quantitative Regulation Principles of the Heating Networks’ Parameters Based on the Life Cycle Analysis. Modern Trends in Construction, Urban and Territorial Planning. 2023;2(2):29–35. (In Russ.) https://doi.org/10.23947/2949-1835-2023-2-2-29-35

7. Tikhomirov AL, Pirozhnikova AP Development of an Information Model of a Heat Supply System at Various Stages of the Life Cycle. Modern Trends in Construction, Urban and Territorial Planning. 2022;1(3):35–42. (In Russ.) https://doi.org/10.23947/2949-1835-2022-1-3-35-42

8. Novitsky NN Methodological Problems of Intellectualization of Pipeline Systems and Directions of Development of the Hydraulic Circuit Theory for their Solution. Proceedings of the 14th All-Russian Scientific Seminar. Melentiev Energy Systems Research Institute SB RAS "Mathematical Models and Methods of Analysis and Optimal Synthesis of Developing Pipeline and Hydraulic Systems". Irkutsk: Publishing House of the Melentiev Energy Systems Research Institute SB RAS; 2014. pp. 301–318. (In Russ.)

9. Stennikov V.A., Barakhtenko E.A., Sokolov D.V. Determination of optimal parameters of heating systems based on advanced information technologies. Energy Systems Research. 2018;1(1):84–93. https://doi.org/10.25729/esr.2018.01.0010

10. Vesterlund M., Toffolo A., Dahl J. Optimization of multi-source complex district heating network, a case study. Energy. 2017;126:53–63. https://doi.org/10.1016/j.energy.2017.03.018

11. Guelpa E., Sciacovelli A., Verda V. Thermo-fluid dynamic model of large district heating networks for the analysis of primary energy savings. Energy. 2019;184:34–44. https://doi.org/10.1016/j.energy.2017.07.177

12. Novitsky NN Development of the Hydraulic Circuit Theory for Solving the Problems of Controlling the Functioning of Heat Supply Systems. Thermal Power Engineering. 2009;12:38–43. (In Russ.)

13. Vesterlund M., Dahl J. A method for the simulation and optimization of district heating systems with meshed networks. Energy conversion and management. 2015;89:555–567. https://doi.org/10.1016/j.enconman.2014.10.002

14. Jie P., Tian Z., Yuan S., Zhu N. Modeling the dynamic characteristics of a district heating network. Energy. 2012;39(1):126–134. https://doi.org/10.1016/j.energy.2012.01.055

15. Chertkov M., Novitsky N. N. Thermal transients in district heating systems. Energy. 2019;184:22–33. https://doi.org/10.1016/j.energy.2018.01.049

16. Lazzaretto A., Toffolo A., Morandin M., von Spakovsky M.R. Criteria for the decomposition of energy systems in local/global optimizations. Energy. 2010;35(2):1157–1163. https://doi.org/10.1016/j.energy.2009.06.009

17. Nardo A.D., Cavallo A., Natale M.D., Greco R., Santonastaso G.F. Dynamic control of water distribution system based on network partitioning. Procedia engineering. 2016;154:1275–1282. https://doi.org/10.1016/j.proeng.2016.07.460