Train-Network-HESS Integrated Optimization for Long-Distance AC Urban Rail Transit to Minimize the Comprehensive Cost

In order to solve the problem of the serious stray current existing in DC urban rail transit, and to improve the utilization rate of the regenerative braking energy (RBE) generated by locomotive, an AC traction power supply system (TPSS) for long-distance urban rail transit is proposed, in which the...

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Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems 2023-01, Vol.24 (1), p.54-67
Main Authors: Chen, Minwu, Lv, Yabo, Lu, Wenjie, Zhang, Diya, Chen, Yinyu
Format: Article
Language:English
Subjects:
AC traction power supply system
Algorithms
Batteries
Configurations
Costs
Electric power distribution
Electric power supplies
Energy consumption
Energy storage
Flow distribution
hybrid energy storage system
Hybrid systems
Indexes
Life cycle costs
Long-distance urban rail transit
Optimization
Power flow
Rail transportation
Railroad transportation
Rails
Stray current
train trajectory
train-network-HESS integrated model
Trajectory
Urban rail
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Summary:In order to solve the problem of the serious stray current existing in DC urban rail transit, and to improve the utilization rate of the regenerative braking energy (RBE) generated by locomotive, an AC traction power supply system (TPSS) for long-distance urban rail transit is proposed, in which the network power flow distribution is affected by the train trajectory, the parameters of network and hybrid energy storage system (HESS) configuration. For achieving the minimum comprehensive cost including the electricity cost and the life cycle cost (LCC) of HESS, this paper aims to develop a Train-Network-HESS integrated model to optimize network power flow distribution. The train trajectory is illustrated based on time-space conversion method and HESS control strategy is discussed to increase the utilization of the RBE. Furthermore, the optimized configuration of the AC TPSS for urban rail transit is obtained by the hybrid GA-PSO algorithm. Finally, the effectiveness of the proposed model is verified by detailed case studies and the comprehensive cost can be reduced up to 39.08% compared with conventional TPSS.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2022.3218639