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Suppression Research Regarding Low-Frequency Oscillation in the Vehicle-Grid Coupling System Using Model-Based Predictive Current Control

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  • Yaqi Wang

    (School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

  • Zhigang Liu

    (School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China)

Abstract

Recently, low-frequency oscillation (LFO) has occurred many times in high-speed railways and has led to traction blockades. Some of the literature has found that the stability of the vehicle-grid coupling system could be improved by optimizing the control strategy of the traction line-side converter (LSC) to some extent. In this paper, a model-based predictive current control (MBPCC) approach based on continuous control set in the dq reference frame for the traction LSC for electric multiple units (EMUs) is proposed. First, the mathematical predictive model of one traction LSC is deduced by discretizing the state equation on the alternating current (AC) side. Then, the optimal control variables are calculated by solving the performance function, which involves the difference between the predicted and reference value of the current, as well as the variations of the control voltage. Finally, combined with bipolar sinusoidal pulse width modulation (SPWM), the whole control algorithm based on MBPCC is formed. The simulation models of EMUs’ dual traction LSCs are built in MATLAB/SIMULINK to verify the superior dynamic and static performance, by comparing them with traditional transient direct current control (TDCC). A whole dSPACE semi-physical platform is established to demonstrate the feasibility and effectiveness of MBPCC in real applications. In addition, the simulations of multi-EMUs accessed in the vehicle-grid coupling system are carried out to verify the suppressing effect on LFO. Finally, to find the impact of external parameters (the equivalent leakage inductance of vehicle transformer, the distance to the power supply, and load resistance) on MBPCC’s performance, the sensitivity analysis of these parameters is performed. Results indicate that these three parameters have a tiny impact on the proposed method but a significant influence on the performance of TDCC. Both oscillation pattern and oscillation peak under TDCC can be easily influenced when these parameters change.

Suggested Citation

  • Yaqi Wang & Zhigang Liu, 2018. "Suppression Research Regarding Low-Frequency Oscillation in the Vehicle-Grid Coupling System Using Model-Based Predictive Current Control," Energies, MDPI, vol. 11(7), pages 1-21, July.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1803-:d:157173
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    References listed on IDEAS

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    1. Roh Chan & Sangshin Kwak, 2018. "Improved Finite-Control-Set Model Predictive Control for Cascaded H-Bridge Inverters," Energies, MDPI, vol. 11(2), pages 1-27, February.
    2. Jiefeng Hu & Ka Wai Eric Cheng, 2017. "Predictive Control of Power Electronics Converters in Renewable Energy Systems," Energies, MDPI, vol. 10(4), pages 1-14, April.
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