Development of a digital twin of the heating network in various software systems

The concept of implementation of smart thermal grids or 4th generation heat supply systems is a priority for the development of district heating systems in Russia and is to become the best available technology (BAT) for all new and reequipped energy systems. This will help to reduce inappropriate losses of thermal energy, reduce the accident rate of power systems, increase their energy efficiency and reliability, and simplify the integration of modern renewable energy sources (RES) into existing energy systems.

One of the key technologies needed to create such systems is the creation of digital twins of heating networks and simulation models of district heating systems. The paper describes the development of a digital twin for the section under consideration of the heat network. The developed experimental stand — a real physical model — was used as a section of the heating network. It was subjected to tests in order to determine the capabilities of systems for remote monitoring of heat carrier parameters, as well as modeling emergency situations in sections of the heating network. The experimental setup was also used for verification of the digital twin being developed. To create a digital model of the experimental stand authors used Matlab Simulink, ZuluThermo and SimInTech. The ZuluThermo program enables to create a digital twin that simulates stationary modes of the thermal system, Matlab Simulink and SimInTech — both stationary and dynamic processes occurring on sections of heating networks. The dynamic model of the heat supply system was used to simulate the process of mutual influence of heat energy consumers. As scenarios of dynamic processes, situations in Matlab Simulink and SimInTech that arise during the operation of automation at thermal points of consumers were simulated. It was shown the mutual influence of heat consumers on each other when regulating the heat load, as well as their influence on consumers who are unable to independently regulate their heat load.

1. Rafalskaya T. A., Mansurov A. R., Mansurova I. R. Study of variable modes of operation of district heating systems with qualitative and quantitative regulation. Bulletin of Perm National Research Polytechnic University. Construction and architecture 2019; 10 (2): 79 - 91. (In Russ.)

2. Electronic resource // https://www.politerm.com: информ.-справочный портал (In Russ.) [Electronic resource] https://www.politerm.com/products/thermo/zuluthermo/ (Date of application: 15.01.2022).

3. Kislov D. K., Ryabenko M. S., Rafalskaya T. A. Development of an intelligent heat supply system based on the Zulu information network. Energy saving and water treatment 2018; 2 (112): 55 - 59. (In Russ.)

4. Lund H., Werner S., Wiltshire R., Svendsen S., Thorsen J. E., Hvel-plund F., Mathiesen B. V. 4th Generation District Heating (4GDH): Integrating smart thermal grids into future sustainable energy systems. Energy 2014, (68): 1-11. (In Eng.) [Electronic resource] https://doi.org/10.1016/j.energy.2014.02.089 (Date of application: 26.06.2022)

5. Lauenburg P. 11 - Temperature optimization in district heating systems, in: Wiltshire, R. (Ed.), Advanced District Heating and Cooling (DHC) Systems, Woodhead Publishing Series in Energy. Woodhead Publishing, Oxford, 2016: 223 - 240. (In Eng.) [Electronic resource] https://doi.org/10.1016/B978-1-78242-374-4.00011-2 (Date of application: 26.06.2022).

6. Zheng X., Sun Q., Wang Y., Zheng L., Gao X., You S., Zhang H., Shi K. Thermo-hydraulic coupled simulation and analysis of a real large-scale complex district heating network in Tianjin. Energy 2021; 236, 121389. (In Eng.) [Electronic resource] https://doi.org/10.1016/j.energy.2021.121389 (Date of application: 26.06.2022).

7. Zheng J., Zhou Z., Zhao J., Wang J. Function method for dynamic temperature simulation of district heating network. Applied Thermal Engineering 2017; (123): 682 - 688. (In Eng.) [Electronic resource] https://doi.org/10.1016/j.applthermaleng.2017.05.083 (Date of application: 26.06.2022).

8. Falay B., Schweiger G., O'Donovan K., Leusbrock I. Enabling large-scale dynamic simulations and reducing model complexity of district heating and cooling systems by aggregation. Energy 2020; 209, 118410. (In Eng.) [Electronic resource] https://doi.org/10.1016/j.energy.2020.118410 (Date of application: 26.06.2022).

9. Barone G., Buonomano A., Forzano C., Palombo A. A novel dynamic simulation model for the thermo-economic analysis and optimisation of district heating systems. Energy Conversion and Management 2020; 220, 113052. (In Eng.) [Electronic resource] https://doi.org/10.1016/j.enconman.2020.113052 (Date of application: 26.06.2022).

10. Larsen H. V., Palsson H., B0hm B., Ravn H. F. Aggregated dynamic simulation model of district heating networks. Energy Conversion and Management 2002; (43): 995-1019. (In Eng.) [Electronic resource] https://doi.org/10.1016/S0196-8904(01)00093-0 (Date of application: 26.06.2022).

11. Zheng J., Zhou Z., Zhao J., Wang J. Function method for dynamic temperature simulation of district heating network. Applied Thermal Engineering 2017; (123): 682 - 688. (In Eng.) [Electronic resource] https://doi.org/10.1016/j.applthermaleng.2017.05.083 (Date of application: 26.06.2022)

12. - Hussein A., Klein A. Modelling and validation of district heating networks using an urban simulation platform. Applied Thermal Engineering 2021; 187, 116529. (In Eng.) [Electronic resource] https://doi.org/10.1016/j.applthermaleng.2020.116529 Date of application: 26.06.2022).

13. Badami M., Fonti A., Carpignano A., Grosso D. Design of district heating networks through an integrated thermo-fluid dynamics and reliability modelling approach. Energy 2018; (144): 826 - 838. (In Eng.) [Electronic resource] https://doi.org/10.1016/j.energy.2017.12.071 (Date of application: 26.06.2022).

14. Schweiger G., Larsson P.-O., Magnusson F., Lauenburg P., Velut S. District heating and cooling systems - Framework for Modelica-based simulation and dynamic optimization. Energy 2017; (137): 566 - 578. (In Eng.) Electronic resource] https://doi.org/10.1016/j.energy.2017.05.115 (Date of application: 26.06.2022).

15. Electronic resource // help.simintech.ru: информ.-справоч-ный портал (In Russ.) [Electronic resource] https://help.simintech.ru/#spravochnaya_sistema_i_ee_nastrojka/DIR_nachalo_raboty_so_spravochnoj_sistemoj.html (Date of application: 10.01.2022).