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Optimal Sizing of On-Board Energy Storage Systems and Stationary Charging Infrastructures for a Catenary-Free Tram

Author

Listed:
  • Ying Yang

    (CRRC Zhuzhou Locomotive Co., Ltd., Zhuzhou 412001, China)

  • Weige Zhang

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Shaoyuan Wei

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Zhenpo Wang

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

Abstract

This paper introduces an optimal sizing method for a catenary-free tram, in which both on-board energy storage systems and charging infrastructures are considered. To quantitatively analyze the trade-off between available charging time and economic operation, a daily cost function containing a whole life-time cost of energy storage and an expense of energy supplies is formulated for the optimal sizing problem. A mixed particle swarm optimization algorithm is utilized to find optimal solutions for three schemes: (1) ultracapacitors storage systems with fast-charging at each station; (2) battery storage systems with slow-charging at starting and final stations; (3) battery storage systems with fast-swapping at swapping station. A case study on an existing catenary-free tramline in China is applied to verify the effectiveness of the proposed method. Results show that a daily-cost reduction over 30% and a weight reduction over 40% can be achieved by scheme 2, and a cost saving of 34.23% and a weight reduction of 32.46% can be obtained by scheme 3.

Suggested Citation

  • Ying Yang & Weige Zhang & Shaoyuan Wei & Zhenpo Wang, 2020. "Optimal Sizing of On-Board Energy Storage Systems and Stationary Charging Infrastructures for a Catenary-Free Tram," Energies, MDPI, vol. 13(23), pages 1-21, November.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:23:p:6227-:d:451544
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    References listed on IDEAS

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    1. Jiang, Jiuchun & Liu, Sijia & Ma, Zeyu & Wang, Le Yi & Wu, Ke, 2016. "Butler-Volmer equation-based model and its implementation on state of power prediction of high-power lithium titanate batteries considering temperature effects," Energy, Elsevier, vol. 117(P1), pages 58-72.
    2. Ahmadian, Ali & Sedghi, Mahdi & Elkamel, Ali & Fowler, Michael & Aliakbar Golkar, Masoud, 2018. "Plug-in electric vehicle batteries degradation modeling for smart grid studies: Review, assessment and conceptual framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2609-2624.
    3. Yi Yang & Zhihao Shang & Yao Chen & Yanhua Chen, 2020. "Multi-Objective Particle Swarm Optimization Algorithm for Multi-Step Electric Load Forecasting," Energies, MDPI, vol. 13(3), pages 1-19, January.
    4. Zhuang Xiao & Pengfei Sun & Qingyuan Wang & Yuqing Zhu & Xiaoyun Feng, 2018. "Integrated Optimization of Speed Profiles and Power Split for a Tram with Hybrid Energy Storage Systems on a Signalized Route," Energies, MDPI, vol. 11(3), pages 1-21, February.
    5. Long Cheng & Wei Wang & Shaoyuan Wei & Hongtao Lin & Zhidong Jia, 2018. "An Improved Energy Management Strategy for Hybrid Energy Storage System in Light Rail Vehicles," Energies, MDPI, vol. 11(2), pages 1-15, February.
    6. Song, Ziyou & Zhang, Xiaobin & Li, Jianqiu & Hofmann, Heath & Ouyang, Minggao & Du, Jiuyu, 2018. "Component sizing optimization of plug-in hybrid electric vehicles with the hybrid energy storage system," Energy, Elsevier, vol. 144(C), pages 393-403.
    7. Herrera, Victor & Milo, Aitor & Gaztañaga, Haizea & Etxeberria-Otadui, Ion & Villarreal, Igor & Camblong, Haritza, 2016. "Adaptive energy management strategy and optimal sizing applied on a battery-supercapacitor based tramway," Applied Energy, Elsevier, vol. 169(C), pages 831-845.
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