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

Hao Zhang (), Jian Zhang, Linjie Zhou, Peng Xiong and Zhuofan Zhao
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Hao Zhang: China Telecom (Anhui Branch) Network Operation Center, Hefei 230031, China
Jian Zhang: School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610097, China
Linjie Zhou: State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Peng Xiong: School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610097, China
Zhuofan Zhao: School of Information and Security Engineering, Zhongnan University of Economics and Law, Wuhan 430073, China

Energies, 2023, vol. 16, issue 21, 1-20

Abstract: 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: urban rail traction power system; energy feedback system; regenerative braking energy; hierarchical operation optimization; real-time simulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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