Methodology and Models of Combined Modeling of Electromagnetic Pro-cesses in Electric Traction Systems

Authors

DOI:

https://doi.org/10.15802/stp2021/237404

Keywords:

subsystem, combined modeling, identification, weight function, model, random process, voltage, electric traction, current

Abstract

Purpose. The main purpose of the work is the development of identification models and a new method of modeling electromagnetic processes in electric traction systems with simultaneous consideration of all its subsystems, as well as several feeder zones of the electrified section. Methodology. To achieve this purpose, the methods of mathematical modelling, the basics of the theory of random processes and the methodology of their probabilistic-statistical processing, the methods for solving integral equations and analysis of electric traction circuits in electric traction systems are used. Findings. The requirements to be met by an adequate, stochastic identification model of electric traction devices are established. The solution of Fredholm’s integral correlation equation of the first kind is performed. The analytical expression of the identification dynamic model of the electric locomotive DE–1 is obtained and its adequacy is checked. The methodology of combined modeling of electromagnetic processes in devices and subsystems of electric traction systems is developed and presented tabularly. Originality. For the first time it is proposed to use the pulse transition function as identification models of traction substation and traction network with electric rolling stock in predictive modeling of electromagnetic and electric power processes in electric traction systems. A new method has been developed, a method of complex modeling of electromagnetic and electric power processes in the system of electric traction with simultaneous consideration of all its subsystems, as well as several inter-substation zones of the electrified section. For the first time, a method of partitioning the correlation functions for solving an integral correlation equation has been proposed, which allows defining a pulse transition function as an identification model of any subsystem of an electric traction system. Practical value. The developed identification models and the method of combined modeling make it possible to predict electromagnetic processes simultaneously in all feeder zones of the electrified section of the electric traction system. The obtained identification model of the electric locomotive DE–1 can be adapted with its subsequent use in modeling processes in the traction circuits of electric locomotives of other types. The method of factorization of correlation functions used in solving the Volterra integral correlation equation of the first kind (convolution type) can be adapted to the solution of other integral equations, which describe the processes in electric traction systems.

References

Bosiy, D. O., & Sichenko V. G. (2009). Matematychne modelyuvannya elektrotyagovogo navantazhennya v zadachax vyvchennya elektromagnitnyx procesiv dlya system elektropostachannya elektrychnogo transportu zminnogo strumu. Texnichna elektrodynamika, 4.3, 86-89. (in Ukrainian)

Zakaryukin, V. P., & Kryukov, A. V. (2010). Metody sovmestnogo modelirovaniya sistem tyagi i vneshnego el-ek-trosnabzheniya zheleznykh dorog peremennogo toka. Irkutsk: IrGUPS. (in Russian)

Kostin, M., & Mishchenko, T. (2019). Stochastic identification model for forecasting of parameters of devices of electric transport systems. Tekhnichna Elektrodynamika, 1, 7-15. DOI: https://doi.org/10.15407/techned2019.01.007 (in Russian)

Krasnov, M. L., Kiselev, A. I., & Makarenko, G. I. (1968). Integralnye uravneniya. Moscow: Nauka. (in Russian)

Mikhalichenko, P. Ye. (2013). Naukove obgruntuvannya ta rozrobka zaxodiv pidvyshhennya efektyvnosti ro-boty systemy elektrychnoyi tyagy postijnogo strumu pry avarijnyx rezhymax (Extended abstract of PhD dissertation). Dnipro National University of Railway Transport named after Academician V. Lazaryan. Dnipro, Ukraine. (in Ukrainian)

Mishchenko, T. M., Mikhalichenko, P. Ye., Kostin, N. A. (2003). Veroyatnostnye kharakteristiki sluchaynoy funktsii napryazheniya na tokopriemnike pervogo ukrainskogo elektrovoza DE 1. Electrical Engineering & Electromechanics, 2, 43-46. (in Russian)

Mishchenko, T. M. (2014). The prospects of the technical solutions and modeling systems of electric traction in high-speed trains. Electrical Engineering & Electromechanics, 1, 19-28. (in Ukrainian)

Novitskyi, I., Sliesarev, V., & Maliienkо, A. V. (2020). Method of identification of nonlinear dynamic control objects of preparatory processes before ore dressing. Naukovyi Visnyk Natsionalnoho Hirnychoho Univer-sytetu, 2, 42-46. DOI: https://doi.org/10.33271/nvngu/2020-2/042 (in Ukrainian)

Pugachev, V. S. Teoriya sluchaynykh funktsiy i ee primenenie k zadacham avtomaticheskogo upravleniya. Moscow: Fizmatgiz. (in Russian)

Sichenko, V. G., Riabokon, B. A., & Slovak, A. D. (2011). Simulation of electromagnetic processes of conversion of electric power at the DC traction substation. Tekhnichna elektrodynamіka, 245-250. (in Ukrainian)

Eykhoff, P. (Ed.). (1983). Sovremennye metody identifikatsii sistem. Moscow: Mir. (in Russian)

Solodovnikov, V. V. (1960). Statisticheskaya dinamika sistem avtomaticheskogo upravleniya. Moscow: Fizmatgiz. (in Russian)

Alnuman, H., Gladwin, D., & Foster, M. (2018). Electrical Modelling of a DC Railway System with Multiple Trains. Energies, 11(11), 3211-3231. DOI: https://doi.org/10.3390/en11113211 (in English)

Jabr, R. A., & Dzafic, I. (2018). Solution of DC Railway Traction Power Flow Systems Including Limited Net-work Receptivity. IEEE Transactions on Power Systems, 33(1), 962-969. DOI: https://doi.org/10.1109/tpwrs.2017.2688338 (in English)

Kocaarslan, İ., Akçay, M. T., Ulusoy, S. E., Bal, E., & Tiryaki, H. (2017). Creation of a dynamic model of the electrification and traction power system of a 25 kV AC feed railway line together with analysis of differ-ent operation scenarios using MATLAB/Simulink. Turkish Journal of Electrical Engineering & Computer Sciences, 25, 4254-4267. DOI: https://doi.org/10.3906/elk-1612-84 (in English)

Kostin, M., Mishchenko, T., & Hoholyuk, O. (2020). Fryze Reactive Power in Electric Transport Systems with Stochastic Voltages and Currents. In 2020 IEEE 21st International Conference on Computational Prob-lems of Electrical Engineering (CPEE) (pp. 1-4). Pinczow, Poland. DOI: https://doi.org/10.1109/cpee50798.2020.9238672 (in English)

Mao, F., Mao, Z., & Yu, K. (2018). The Modeling and Simulation of DC Traction Power Supply Network for Urban Rail Transit Based on Simulink. Journal of Physics: Conference Series, 1087(4), 1-7. DOI: https://doi.org/10.1088/1742-6596/1087/4/042058 (in English)

Minucci, S., Pagano, M., & Proto, D. (2018). Model of the 2 × 25 kV high speed railway supply system taking into account the soil-air interface. International Journal of Electrical Power & Energy Systems, 95, 644-652. DOI: https://doi.org/10.1016/j.ijepes.2017.09.017 (in English)

Shang, J., Zhang, J., & Zhang, Z. (2018). Optimizational Mathematical Modeling Methods of DC Traction Pow-er Supply System for Urban Mass Transit. Mathematical Problems in Engineering, 2018, 1-9. DOI: https://doi.org/10.1155/2018/3084184 (in English)

Sisay, M. (2017). Modeling and Simulation of Traction Power Supply System. Retrieved from http://etd.aau.edu.et/bitstream/handle/123456789/15217/Molalegn%20Sisay.pdf?sequence=1&isAllowed=y (in English)

Published

2021-04-15

How to Cite

Mishchenko, T. M. (2021). Methodology and Models of Combined Modeling of Electromagnetic Pro-cesses in Electric Traction Systems. Science and Transport Progress, (2(92), 40–49. https://doi.org/10.15802/stp2021/237404

Issue

Section

ELECTRIC TRANSPORT, POWER SYSTEMS AND COMPLEXES