Energies (Oct 2023)

Hierarchical Operation Optimization for Regenerative Braking Energy Utilizing in Urban Rail Traction Power Supply System

  • Hao Zhang,
  • Jian Zhang,
  • Linjie Zhou,
  • Peng Xiong,
  • Zhuofan Zhao

DOI
https://doi.org/10.3390/en16217268
Journal volume & issue
Vol. 16, no. 21
p. 7268

Abstract

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The energy feedback system (EFS) is widely accepted to utilize the regenerative braking energy (RBE) in an urban rail traction power supply system (TPSS). However, the sharing relationship of RBE between EFS, traction trains and on-board braking resistors is not clear. In addition, the impact of EFS operation on the sharing of RBE has been rarely studied. This paper proposed a hierarchical operation optimization method for improving the utilization of shared RBE in TPSS through the EFS. An optimizing model for the dynamic start-up voltage threshold of EFS is established, with the objective of minimizing TPSS power consumption. A fast prediction model of train operation information is developed to analyze the steady-state power flow in advance. The optimal solution is searched using a salp swarm algorithm (SSA) on a per second basis. A microsystem of three traction stations and two trains is analyzed. Compared to the conventional constant voltage operation scheme, the optimal solution achieves a maximum additional energy-saving efficiency improvement of 2.44%. Efficient sharing of RBE is identified as the key to achieving energy savings. Regarding the local control part, system stability analysis is verified. Real-time simulation results indicate that the dynamic operating mode of EFS efficiently distributes RBE.

Keywords