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Economic Analysis on Value Chain of Taxi Fleet with Battery-Swapping Mode Using Multiobjective Genetic Algorithm

Author

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  • Guobao Ning
  • Zijian Zhen
  • Peng Wang
  • Yang Li
  • Huaixian Yin

Abstract

This paper presents an economic analysis model on value chain of taxi fleet with battery-swapping mode in a pilot city. In the model, economic benefits of charging-swapping station group, taxi company, and taxi driver in the region have been taken into consideration. Thus, the model is a multiobjective function and multiobjective genetic algorithm is used to solve this problem. According to the real data collected from the pilot city, the multiobjective genetic algorithm is tested as an effective method to solve this problem. Furthermore, the effects of price of electricity, price of battery package, life cycle of battery package, cost of battery-swapping devices and infrastructure, and driving mileage per day on the benefits of value holders are analyzed, which provide theoretical and practical reference for the deployment of electric vehicles, for the national subsidy criteria adjusment, technological innovation instruction, commercial mode selection, and infrastructure construction.

Suggested Citation

  • Guobao Ning & Zijian Zhen & Peng Wang & Yang Li & Huaixian Yin, 2012. "Economic Analysis on Value Chain of Taxi Fleet with Battery-Swapping Mode Using Multiobjective Genetic Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2012, pages 1-15, December.
  • Handle: RePEc:hin:jnlmpe:175912
    DOI: 10.1155/2012/175912
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    Cited by:

    1. Zhan, Weipeng & Wang, Zhenpo & Zhang, Lei & Liu, Peng & Cui, Dingsong & Dorrell, David G., 2022. "A review of siting, sizing, optimal scheduling, and cost-benefit analysis for battery swapping stations," Energy, Elsevier, vol. 258(C).
    2. Cui, Dingsong & Wang, Zhenpo & Liu, Peng & Wang, Shuo & Dorrell, David G. & Li, Xiaohui & Zhan, Weipeng, 2023. "Operation optimization approaches of electric vehicle battery swapping and charging station: A literature review," Energy, Elsevier, vol. 263(PE).

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