Balancing traction resources based on fluctuations in train speeds and required traction reserves

Introduction. The rational operation of the locomotive fleet is based on coordination of the locomotive turnover schedule with the train traffic schedule that assume unconditional fulfillment of standard transportation jobs and no less strict compliance with technical and technological standards for locomotive and train operations at locomotive turnover and re-coupling stations. Coordination is intended to set up balance of locomotives at traction interchange points. However, in the course of transportation, the intra-day dislocation of the operating fleet reaches significant unevenness and leads to imbalance. This requires a system for dispatching traction resources to their turnover and recoupling stations which will help to preserve traction balance at the interchange points to compensate for uneven intraday dislocation of the operating fleet, rationalise the locomotive fleet operations, and improve line capacity.

Materials and methods. The balance of traction resources at locomotive turnover and re-coupling stations in intra-day intervals is achieved by interval regulation of traction resources.

Results. The paper proposes an approach to establishing a balance of traction resources at current interlocking stations as the simplest type of turnover and recoupling stations (as a rule, they do not have additional adjacencies, using a one-to-one traction exchange). The approach applies the correlation between fluctuations in train traffic speeds and the amount of required traction reserves within daily three-hour intervals.

Discussion and conclusion. This approach helps to improve the traction resource balancing technology at the current junction stations, and create a basis for building a mechanism for dispatching regulation reserves.

1. Nekrashevich V. I. Use of train locomotives in freight traffic. Gomel: BelGUT; 2001 269 p. (In Russ.).

2. Kotenko A., Kotenko O. Locomotive Team Productivity as a Criterion for Optimal Locomotive Fleet Management. In: Manakov A., Edigarian A. (eds) International Scientific Siberian Transport Forum TransSiberia – 2021. Cham: Springer; 2022. p. 512–520. (Lecture Notes in Networks and Systems; vol 402). https://doi.org/10.1007/978-3-030-96380-4_56.

3. Mehedov M. I., Muginshteyn L. A. Site throughput and carrying capacity as a function of traction resources. In: Management of commodity flows and carriage processes on railway transport on the basis of customer orientation and logistics technologies: a joint monograph by members and scientific partners of the Joint Scientific Council of the Russian Railways. St. Petersburg; 2019. p. 225–238. (Bulletin of the Joint Scientific Council of the Russian Railways). (In Russ.).

4. Morgunov A. I. Methodological approaches to locomotive turnaround schedule forecasting. In: Development of Railway Transport during Reforms: Collection of scientific articles. Moscow: Intext Publ.; 2003. p. 81–87. (In Russ.).

5. Gordon M. A. Peculiarities of train traffic control systems at docking stations in Russia. Transport Automation Research. 2019;5(1):62-77. (In Russ.). https://doi.org/10.20295/2412-9186-2019-1-62-77.

6. Bodrikov D. I., Vorobyov A. A., Smirnov V. P., Fadeikin T. N. Simulation model of current change station operation. Science and Technology in Transport. 2021;(2):45-49. (In Russ.). EDN: https://www.elibrary.ru/vunook.

7. Dmitriyev E. O., Sukhov A. A., Petrov A. S., Alekseyevnin E. A. Traction support of train operation during changes in operational situation. Vestnik transporta Povolzhya. 2021;(2):58-66. (In Russ.) EDN: https://www.elibrary.ru/kynndt.

8. Osipov N. I. Simulation modelling to estimate the influence of the trains arrival interval on the work of traction current junction stations. Fundamental'nyye i prikladnyye voprosy transporta. 2022;(4):16- 22. (In Russ.). https://doi.org/10.52170/2712-9195_2022_4_16.

9. Sotnikov E. A., Gonik M. M., Khomyakov S. V., Mikhaylov S. V. Simulation model for determining the rational dimensions of the irreducible reserve of locomotives at the stations of its turnover. Russian Railway Science Journal. 2018;77(3):157-164. (In Russ.). https://doi.org/10.21780/2223-9731-2018-77-3-157-164.

10. Sotnikov E. A., Gonik M. M., Khomyakov S. V., Mikhaylov S. V. Rationing the size of the irreducible reserve of locomotives at the turnover stations. Russian Railway Science Journal. 2020;79(1):3-8. (In Russ.). https://doi.org/10.21780/2223-9731-2020-79-1-3-8.

11. Kuvondikov J. O., Tsaplin A. E. Method of analysis and simulation model of locomotive fleet availability function accounting for cold standby reserve. Proceedings of Petersburg Transport University. 2019;16(4):631-641. (In Russ.). https://doi.org/10.20295/1815-588Х-2019-4-631-641.

12. Macheret D. A. Analysis of long-term trends of speeds in freight traffic. Zheleznodorozhnyy transport. 2012;(5):66-71. (In Russ.). EDN: https://www.elibrary.ru/nlbijm.

13. Korobeynikov A. P., Starodubtseva V. A. Analysis of the efficiency of docking stations. Сientific Horizons. 2022;(4):55-59. (In Russ.). EDN: https://www.elibrary.ru/vtcldj.

14. Seregin I. V., Nemtsov Yu. V. Determination of optimal routes of weighted and lengthened trains with limiting sections of the railway network. Vestnik transporta Povolzhya. 2023;(4):88-94. (In Russ.). EDN: https://www.elibrary.ru/efypll.

15. Mekhedov M. I., Kornienko N. V. Influence of technical and technological equipment of a locomotive maintenance point on the capacity of a railway line. Russian Railway Science Journal. 2021;80(4):225-232. (In Russ.). https://doi.org/10.21780/2223-9731-2021-80-4-225-232.

16. Maksimov D. V. Automation of locomotives turnaround scheduling. Proceedings of the Railway Research Institute. Moscow; 1980. Issue. 633. p. 86–96. (In Russ.).

17. Kozlov P. A., Vakulenko S. P. Train locomotive turnaround optimisation issue. Vestnik Rostovskogo gosudarstvennogo universiteta putey soobshcheniya (Vestnik RGUPS). 2016;(3):80-89. (In Russ.). EDN: https://www.elibrary.ru/wvpnpd.

18. Kozlov P. A., Vakulenko S. P. Calculation of agreed locomotive turnaround and maintenance modes. Science and Technology in Transport. 2016;(3):90-95. (In Russ.). EDN: https://www.elibrary.ru/wmvaxl.

19. Kozlov P. A., Vakulenko S. P. Simulation Model to Optimize Turnover Schedule for Train Locomotives. Russian Railway Science Journal. 2015;(2):15-20. (In Russ.). https://doi.org/10.21780/2223-9731-2015-0-2-15-20.