Abstract
This paper presents an analysis of the fully parallel AT traction network using a six conductor transmission line. An equivalent model is derived and simulation models for traction substations, section posts, AT posts, traction networks, and electric locomotives are comprehensively built using RT-plus/Simulink to enhance the practicality of the simulation. Based on these models, a simulation software for electrified railway traction power supply system is developed using vehicle network coupling power flow calculation. The results of the example calculation demonstrate that this method effectively considers the interaction between the train and the traction power supply network, leading to a more accurate reflection of power flow distribution in the traction power supply system. So, the proposed method has significant application value in electrified railway engineering.
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References
He, Z.Y., Fang, L., Guo, D., et al.: Algorithm for power flow of electric traction network based on equivalent circuit of AT-fed system [J]. J. Southwest Jiao Tong Univ. 43(2), 1–6 (2008)
Wan, Q., Wu, M., Chen, J., et al.: Simulating calculation of traction substation’s feeder current based on traction calculation [J]. Trans. China Electrotechn. Soc. 22(6), 108–113 (2007)
Cai, Y., Irning, M.R., Case, S.H.: Compound matrix portioning and modification for the solution of branched autotransformer traction feeds. IEE Proceedings; Electric (2003) Prediction of dissolved gas content in transformer oil by grey model. J. Chinese Electric. Eng. 20(3), 65–69 (2003)
Sun, C.X.: A new model of grey prediction parameter model and its application in electrical insulation fault prediction [J]. Control Theory Appl. 20(5), 797–801 (2003)
Sergejs, Z., Poiss, G.: Power transformer mechanical condition assessment with a vibration-based diagnostic method. In: International Scientific Conference on Power and Electrical Engineering of Riga Technical University IEEE, pp. 1–4, (2015)
Sica, F.C., Guimaraes, F.G., Duarte, R.D.O., et al.: A cognitive system for fault prognosis in power transformers [J]. Electr. Power Syst. Res. 127, 109–117 (2015)
Sima, L.P., Shu, N.P., Zuo, J., et al.: Prediction of dissolved gas concentration in transformer oil based on grey correlation and fuzzy support vector machine [J]. Power Syst. Protect. Control 40(19), 41–46 (2012)
Wan, F., Yang, M.L., He, P., et al.: Gas Raman spectrum detection and signal processing method in transformer oil [J]. Chinese J. Sci. Instr. 37(11), 2482–2488 (2016)
Li, Y., Cheng, H.B., Xin, J.B., et al.: GM (1, n) prediction of dissolved gas concentration in transformer oil [J]. J. East China Jiao Tong Univ. 34(3), 131–136 (2017)
Tang, Y.B., Gui, W.H., Peng, T.: Multinuclear principal component regression prediction model for gas in transformer oil [J]. Electr. Mach. Control 16(11), 92–98 (2012)
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Li, C.B., Liu, L.P., Liu, Y., Tian, X.J., Song, W., Cao, S. (2024). Power Flow Calculation of Vehicle Network Coupling in Traction Power Supply System. In: Gong, M., Jia, L., Qin, Y., Yang, J., Liu, Z., An, M. (eds) Proceedings of the 6th International Conference on Electrical Engineering and Information Technologies for Rail Transportation (EITRT) 2023. EITRT 2023. Lecture Notes in Electrical Engineering, vol 1138. Springer, Singapore. https://doi.org/10.1007/978-981-99-9319-2_40
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DOI: https://doi.org/10.1007/978-981-99-9319-2_40
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