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An online train-grid integration energy optimization method for urban rail system

Author

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  • Wei, Wei
  • Zhang, Gang
  • Wang, Renyu
  • Xiong, Wei
  • Yu, Hong

Abstract

The energy consumption of urban rail systems is influenced by the coordination between power supply system and train operation. Currently, these two aspects are not aligned in energy optimization efforts, leading to substantial energy wastage. This paper proposes an energy optimization method that integrates power supply system and train operation. Firstly, the factors influencing system energy optimization are analyzed, and optimization objectives and variables are established. Subsequently, an online train-grid integration energy optimization strategy is outlined, encompassing flexible traction power supply system regulation and train operation regulation. Finally, validation is conducted through simulation encompassing a diverse range of operational scenarios, ensuring a comprehensive verification of its performance and applicability. The results indicate that the implementation of energy-efficient regulation strategies for train-grid integration yields a notable reduction in overall energy consumption, amounting to a reduction of up to 10.75 %. The proposed method effectively optimizes system energy in diverse scenarios, thereby consolidating and maximizing the energy-saving potential within the fields of electrical engineering and transportation. This paper offers novel insights for interdisciplinary operational enhancements within the urban rail transit.

Suggested Citation

  • Wei, Wei & Zhang, Gang & Wang, Renyu & Xiong, Wei & Yu, Hong, 2024. "An online train-grid integration energy optimization method for urban rail system," Energy, Elsevier, vol. 313(C).
    • Handle: RePEc:eee:energy:v:313:y:2024:i:c:s036054422403620x
    DOI: 10.1016/j.energy.2024.133842
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    References listed on IDEAS

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    1. Li, Zhanhe & Li, Xiaoqian & Lu, Chao & Ma, Kechun & Bao, Weihan, 2024. "Carbon emission responsibility accounting in renewable energy-integrated DC traction power systems," Applied Energy, Elsevier, vol. 355(C).
    2. Huang, Yeran & Yang, Lixing & Tang, Tao & Gao, Ziyou & Cao, Fang, 2017. "Joint train scheduling optimization with service quality and energy efficiency in urban rail transit networks," Energy, Elsevier, vol. 138(C), pages 1124-1147.
    3. Wang, Xuekai & Tang, Tao & Su, Shuai & Yin, Jiateng & Gao, Ziyou & Lv, Nan, 2021. "An integrated energy-efficient train operation approach based on the space-time-speed network methodology," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
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