Theoretical and applied aspects of using a thermal pump effect in gas pipeline systems

Authors

DOI:

https://doi.org/10.15587/1729-4061.2018.121667

Keywords:

gas transmission system, inter-strand bridge, throttle effect, thermal pump, electrohydraulic analogy, mathematical model of gas transmission in pipelines

Abstract

Based on the classical method for calculating parameters of gas pipelines using electrohydraulic analogy, a mathematical model of the object, the process of gas transmission in an industrial pipeline, has been developed. The study subject was the change of gas temperature after its passing through a throttling device which brings about thermal pump effect in the receiving strand of the gas pipeline. It was proposed to use gas-dynamic thermal pumps to minimize the risk of plug and hydrate formation in the gas pipeline of Kharkivtransgaz Co. It was shown that the change of the ground body temperature by ±10 °C in the 20 km long gas transmission section of the multi-strand pipeline system causes a change of gas pressure by 5−15 %. A theoretical-empirical formula for determining the Joule-Thomson coefficient was derived which allows one to estimate the thermal pump effect on the energy and thermobaric parameters of nonstationary gas transmission processes. It was determined that the integral coefficient of performance (COP) for the network system of multi-strand pipelines including gas-dynamic thermal pumps varies within the range of 1.00‒1.09 depending on the ambient temperature (0−20 oC). The principles of constructing the topology of the diagram of the gas pipeline with bridges and branches which, due to the use of the thermal pump effect, ensures a minimal risk of plugging and hydration consist in activation and regulation of the energy-transforming and heat exchange processes in the sections of the network system. This is achieved by introduction of additional throttling devices in front of the bridges and branches of the pipeline and by checking for proximity and bordering with critical temperatures of plug and hydrate formation.

Author Biographies

Mykhailo Fyk, National Technical University "Kharkiv Polytechnic Institute" Kyrpychova str., 2, Kharkiv, Ukraine, 61002

PhD, Associate Professor

Department of oil, gas and condensate extraction 

Ilya Fyk, National Technical University "Kharkiv Polytechnic Institute" Kyrpychova str., 2, Kharkiv, Ukraine, 61002

Doctor of Technical Sciences, Professo

Department of oil, gas and condensate extraction 

Volodymyr Biletsky, National Technical University "Kharkiv Polytechnic Institute" Kyrpychova str., 2, Kharkiv, Ukraine, 61002

Doctor of Technical Sciences, Professor

Department of oil, gas and condensate extraction

Max Oliynyk, Kryvyi Rih National University Vitaliya Matusevycha str., 11, Kryvyi Rih, Ukraine, 50027

PhD, Senior Lecturer

Department of mineral processing and chemistry

Yulia Kovalchuk, Kyiv National University of Construction and Architecture Povitroflotsky ave., 31, Kyiv, Ukraine, 03037

PhD, Associate Professor

Department of Chemistry

Volodymyr Hnieushev, National University of Water and Environmental Engineering Soborna str., 11, Rivne, Ukraine, 33028

PhD, Associate Professor

Department of Occupational Safety and Security of Life

Yevhen Shapchenko, UMG "Kharkivstransgaz" Kultury str., 20A, Kharkiv, Ukraine, 61001

Specialist in heat and gas supply, ventilation and air conditioning, Chief Dispatcher

References

  1. Fesenko, Y. L., Kryvulia, S. V., Syniuk, B. B., Fyk, M. I. (2013). Applied aspects of maintaining gas production in a gas condensate production field at a late stage of operation. NAFTA-GAZ, 69 (10), 751–760.
  2. Kutia, M., Fyk, M., Kravchenko, O., Palis, S., Fyk, I. (2016). Improvement of technological-mathematical model for the medium-term prediction of the work of a gas condensate field. Eastern-European Journal of Enterprise Technologies, 5 (8 (83)), 40–48. doi: 10.15587/1729-4061.2016.80073
  3. Domschke, P., Kolb, O., Lang, J. (2015). Adjoint-based error control for the simulation and optimization of gas and water supply networks. Applied Mathematics and Computation, 259, 1003–1018. doi: 10.1016/j.amc.2015.03.029
  4. Denisova, A. E., Troitskiy, A. N. (2011). Algoritm rascheta teplofizicheskih parametrov gruntovogo teploobmennika dlya teplovogo nasosa. Energotekhnologii i resursosberezhenie, 1, 8–12.
  5. Midttømme, K., Banks, D., Ramstad, R., Sæther, O., Skarphagen, H. (2008). Ground-Source Heat Pumps and Underground Thermal Energy Storage. Energy for the future, 11, 93–98.
  6. Bertani, R. (2015). Geothermal Power Generation in the World 2010–2014 Update Report. Proceedings World Geothermal Congress 2015.
  7. Chwieduk, D. A. (2012). Solar-Assisted Heat Pumps. Comprehensive Renewable Energy, 495–528. doi: 10.1016/b978-0-08-087872-0.00321-8
  8. Chaczykowski, M. (2010). Transient flow in natural gas pipeline – The effect of pipeline thermal model. Applied Mathematical Modelling, 34 (4), 1051–1067. doi: 10.1016/j.apm.2009.07.017
  9. Oosterkamp, A., Ytrehus, T., Galtung, S. T. (2016). Effect of the choice of boundary conditions on modelling ambient to soil heat transfer near a buried pipeline. Applied Thermal Engineering, 100, 367–377. doi: 10.1016/j.applthermaleng.2016.01.057
  10. Ghajar, A. J. (2005). Non-boiling heat transfer in gas-liquid flow in pipes: a tutorial. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 27 (1), 46–73. doi: 10.1590/s1678-58782005000100004
  11. Pistun, Y., Matiko, F., Masnyak, O. (2015). Simplified Method for Calculation of the Joule-Thomson Coefficient at Natural Gas Flowrate Measurement. Energy Engineering and Control Systems, 1 (2), 127–132. doi: 10.23939/jeecs2015.02.127
  12. Maric, I., Ivek, I. (2010). Compensation for Joule–Thomson effect in flowrate measurements by GMDH polynomial. Flow Measurement and Instrumentation, 21 (2), 134–142. doi: 10.1016/j.flowmeasinst.2010.01.009
  13. Syed A. (2013). Preventing Hydrate Formation in Gas Transporting Pipelines with Synthetic Inhibitors. International Journal of Chemistry.
  14. Shanbi, P. (2013). The Simulation of Natural Gas Gathering Pipeline Network. The Open Fuels & Energy Science Journal, 6 (1), 18–22. doi: 10.2174/1876973x20130827002
  15. Ebrahimi, M., Torshizi, S. E. M. (2012). Optimization of power generation from a set of low-temperature abandoned gas wells, using organic Rankine cycle. Journal of Renewable and Sustainable Energy, 4 (6), 063133. doi: 10.1063/1.4768812
  16. Liu, E., Li, C., Yang, Y. (2014). Optimal Energy Consumption Analysis of Natural Gas Pipeline. The Scientific World Journal, 2014, 1–8. doi: 10.1155/2014/506138
  17. Domschkea, P., Duac, A., Stolwijkc, J. J., Langa, J., Mehrmannc, V. (2017). Adaptive Refinement Strategies for the Simulation of Gas Flow in Networks using a Model Hierarchy. arXiv.org. Available at: https://arxiv.org/pdf/1701.09031.pdf
  18. Liu, S., Dai, S., Ding, Q., Hu, L., Wang, Q. (2017). Fast Calculation Method of Energy Flow for Combined Electro-Thermal System and Its Application. Energy and Power Engineering, 09 (04), 376–389. doi: 10.4236/epe.2017.94b043
  19. Sarbu, I., Sebarchievici, C. (2014). General review of ground-source heat pump systems for heating and cooling of buildings. Energy and Buildings, 70, 441–454. doi: 10.1016/j.enbuild.2013.11.068
  20. Orga, A. C., Obibuenyi, J. I., Nwozuzu, M. (2017). An Offshore Natural Gas Transmission Pipeline Model and Analysis for the Prediction and Detection of Condensate/Hydrate Formation Conditions. IOSR Journal of Applied Chemistry, 10 (03), 33–39. doi: 10.9790/5736-1003013339
  21. Pouladi, N., Heitmann, H. (2017). Simulation of steady flow of natural gas in a subsea flexible riser with heat exchange. Journal of Natural Gas Science and Engineering, 46, 533–543. doi: 10.1016/j.jngse.2017.08.012
  22. Mikolajková, M., Haikarainen, C., Saxén, H., Pettersson, F. (2017). Optimization of a natural gas distribution network with potential future extensions. Energy, 125, 848–859. doi: 10.1016/j.energy.2016.11.090
  23. Fyk, M. I. (2008). Do pytannia rozrakhuvannia hazodynamichnykh parametriv potoku hazu v mizhnytkovii peremychtsi mahistralnoho hazoprovodu. Rozvidka ta rozrobka naftovykh i hazovykh rodovyshch, 4 (29), 80–82.
  24. Mikolajková, M., Pettersson, F., Saxen, H. (2017). Linearized model of pipeline distribution of gas to a local market. Conference: ECOS 2017 International conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, At San Diego, Vol. 1. San Diego, 1–12.
  25. Rotov, A. A., Istomin, V. A., Mitnitsky, R. A., Kolinchenko, I. V. (2016). Features of thermal modes of gas gathering systems at a late stage of Development of the cenomanian deposits in the Urengoyskoye field. Transport and storage of oil products and hydrocarbons, 3, 46–52.
  26. Seleznev, V. E., Aleshin, V. V., Pryalov, S. N. (2009). Osnovy chislennogo modelirovaniya magistral'nyh truboprovodov. Moscow: MAKS Press, 436.
  27. Biletsky, V., Sergeyev, P., Krut, O. (2013). Fundamentals of highly loaded coal-water slurries. Mining of Mineral Deposits. CRC Press Taylor & Francis Group, London, 105–113. doi: 10.1201/b16354-20

Downloads

Published

2018-01-24

How to Cite

Fyk, M., Fyk, I., Biletsky, V., Oliynyk, M., Kovalchuk, Y., Hnieushev, V., & Shapchenko, Y. (2018). Theoretical and applied aspects of using a thermal pump effect in gas pipeline systems. Eastern-European Journal of Enterprise Technologies, 1(8 (91), 39–48. https://doi.org/10.15587/1729-4061.2018.121667

Issue

Section

Energy-saving technologies and equipment