Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon openaccess Impact analysis of traction loads on power grid based on probabilistic three-phases load flow

  • Author(s): Yulong Che 1, 2, 3 ; Xiaoru Wang 1 ; Xiaoqin Lv 1 ; Yi Hu 1 ; Longyuan Li 1 ; Haoyue Chen 1
    • View affiliations
  • Source: Volume 2019, Issue 16, March 2019, p. 2306 – 2311
    DOI:  10.1049/joe.2018.8532 , Online ISSN 2051-3305
This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 23/08/2018, Accepted 19/09/2018, Published 26/10/2018

Electrified railway traction power supply system is directly powered by 110 kV or 220 kV (some 330 kV) high-voltage power grid. The uncertainty, non-linearity, and asymmetry of traction loads like the electric locomotives and electric multiple units (EMUs) exert the negative sequence and harmonics impact on the high-voltage transmission network. In order to evaluate the impact of the uncertainty and asymmetry of traction loads on the high-voltage transmission grid, a probabilistic three-phase power flow model of transmission network considering the probability model of traction loads is proposed. First, the power probability model of traction loads is established according to the running characteristics of traction loads. Second, the Monte Carlo simulation method is applied for the probabilistic three-phase power flow model calculation considering the traction loads. Finally, the simulation calculation is carried out on the balanced IEEE-14 bus three-phase test system. The results show that the asymmetric traction loads cause the unbalance of the grid nearby to deteriorate. The further away from the traction substation, the smaller impact of the traction loads.

Inspec keywords: traction power supplies; transmission networks; probability; traction; electric locomotives; railway electrification; power grids; Monte Carlo methods; substations; load flow; railways

Other keywords: voltage 330.0 kV; kV high-voltage power grid; three-phase power flow model calculation; high-voltage transmission grid; voltage 220.0 kV; voltage 110.0 kV; electrified railway traction power supply system; three-phases load flow; asymmetric traction loads

Subjects: Control of electric power systems; Power system control; Reliability; Power engineering computing; Monte Carlo methods; Transportation; Optimisation techniques

References

    1. 1)
      • 2. Minucci, S., Pagano, M., Proto, D.: ‘Model of the 2 × 25 kV high speed railway supply system taking into account the soil-air interface’, Int. J. Electr. Power Energy Syst., 2018, 95, pp. 644–652.
    2. 2)
      • 6. Mongkoldee, K., Kulworawanichpong, T.: ‘Current-based newton-raphson power flow calculation for AT-fed railway power supply systems’, Int. J. Electr. Power Energy Syst., 2018, 98, pp. 11–22.
    3. 3)
      • 13. Satoshi, S., Jumpei, B., Katsuhiko, S., et al: ‘Effective application of superconducting magnetic energy storage (SMES) to load levelling for high speed transportation system’, IEEE Trans. Appl. Supercond., 2004, 14, (2), pp. 713–716.
    4. 4)
      • 5. Raygani, S.V., Tahavorgar, A., Fazel, S.S., et al: ‘Load flow analysis and future development study for an AC electric railway’, IET Electr. Syst. Transp., 2012, 2, (3), pp. 139–147.
    5. 5)
      • 8. Van Casteren, J., Groeman, F.: ‘Harmonic analysis of rail transportation systems with probabilistic techniques’. Proc. Int. Conf. on Probabilistic Methods Applied to Power Systems, PMAPS, Stockholm, Sweden, June, 2006, pp. 1–6.
    6. 6)
      • 7. Ho, T.K., Chi, Y.L., Siu, L.K., et al: ‘Probabilistic load flow in AC electrified railways’, IEE Proc-Electric Power Appl., 2005, 152, (4), pp. 1003–1013.
    7. 7)
      • 10. Caramia, P., Carpinelli, G., Varilone, P., et al: ‘Probabilistic three-phase load flow’, Int. J. Electr. Power Energy Syst., 1999, 21, (1), pp. 55–69.
    8. 8)
      • 1. Li, Q.Z.: ‘New generation traction power supply system and its key technologies for electrified railways’, J. Mod. Transp., 2015, 23, (1), pp. 1–11.
    9. 9)
      • 4. Hu, H.T., He, Z.Y., Wang, J.F., et al: ‘Power flow calculation of high-speed railway traction network based on train-network coupling systems’, Proc. CSEE, 2012, 32, (19), pp. 101–108.
    10. 10)
      • 12. Li, Q.Z.: ‘Traction substation power supply analysis and comprehensive compensation technology’ (China Railway Press, Peking, 2006).
    11. 11)
      • 11. Gupta, N., Daratha, N.: ‘Probabilistic three-phase load flow for unbalanced electrical systems with wind farms’, Int. J. Electr. Power Energy Syst., 2017, 87, pp. 154–165.
    12. 12)
      • 3. 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. Southwest Jiaotong Univ., 2008, 43, (1), pp. 1–7.
    13. 13)
      • 14. Yang, S.B., Wu, M.L.: ‘Power load modelling and parameter identification based on improved ant colony algorithm for passenger lines’, Proc. CSEE, 2015, 35, (7), pp. 1578–1585.
    14. 14)
      • 15. ‘Power systems test case archive’. https://www2.ee.washington.edu/research/pstca/, accessed 18 January 2018.
    15. 15)
      • 9. Liu, W., Li, Q.Z., Tang, B., et al: ‘Probabilistic load flow for urban rail traction power supply based on monte carlo simulation’, J. Southwest Jiaotong Univ., 2010, 45, (4), pp. 561–567.
http://iet.metastore.ingenta.com/content/journals/10.1049/joe.2018.8532
Loading

Related content

content/journals/10.1049/joe.2018.8532
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address