Real-time control strategy of railway flexible traction power supply system considering source-load prediction error

In the flexible traction power supply system, the source load prediction error will aggravate the "dead time" problem of the energy storage equipment, and also lead to the deviation of the energy storage charge and discharge power from the optimal value. Both of the above problems will have an impact on peak shaving and valley filling and photovoltaic consumption, which will ultimately lead to an increase in the total operating cost of the system. Therefore, this paper first analyses the problem mechanism, and then combines the idea of adaptive correction into the Model Predictive Control (MPC) method from the root cause of the problem, and proposes a Model Predictive Control (DAC-MPC) method based on adaptive correction of energy storage state of charge (SOC) and adaptive power adjustment. The SOC adaptive correction can make the energy storage avoid the "dead zone", and the adaptive adjustment of the energy storage power can make the energy storage power change with the change of the actual source load value. Experimental data show that the proposed control strategy can effectively solve the above two problems, ensure that the system is not affected by the source load prediction error, and improve the economy of system operation.

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Publication Details

Journal
IET conference proceedings.
Published
2026-02-19
DOI
https://doi.org/10.1049/icp.2025.3919
Primary Topic
Railway Systems and Energy Efficiency
Type
article
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article

Real-time control strategy of railway flexible traction power supply system considering source-load prediction error

Yulong Zhao, Pei Luo, L. Q. Li
IET conference proceedings.
Railway Systems and Energy Efficiency
article

Real-time control strategy of railway flexible traction power supply system considering source-load prediction error

Yulong Zhao, Pei Luo, L. Q. Li
article en

Abstract

In the flexible traction power supply system, the source load prediction error will aggravate the "dead time" problem of the energy storage equipment, and also lead to the deviation of the energy storage charge and discharge power from the optimal value. Both of the above problems will have an impact on peak shaving and valley filling and photovoltaic consumption, which will ultimately lead to an increase in the total operating cost of the system. Therefore, this paper first analyses the problem mechanism, and then combines the idea of adaptive correction into the Model Predictive Control (MPC) method from the root cause of the problem, and proposes a Model Predictive Control (DAC-MPC) method based on adaptive correction of energy storage state of charge (SOC) and adaptive power adjustment. The SOC adaptive correction can make the energy storage avoid the "dead zone", and the adaptive adjustment of the energy storage power can make the energy storage power change with the change of the actual source load value. Experimental data show that the proposed control strategy can effectively solve the above two problems, ensure that the system is not affected by the source load prediction error, and improve the economy of system operation.

IET conference proceedings.Vol. 2025(38)
Xiangtan University (CN)
Affordable and clean energy
Openalex Percentile: Top 53%
Railway Systems and Energy Efficiency
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Real-time control strategy of railway flexible traction power supply system considering source-load prediction error — Yulong Zhao, Pei Luo, et al. · IET conference proceedings. (2026) | TGRS Research Map | TGRS