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GIS-Based Multi-Objective Particle Swarm Optimization of Charging Station of Electric Vehicles – Taking a District in Beijing as an Example

Author

Listed:
  • Zhang Yue

    (China University of Petroleum)

  • Arash Farnoosh

    (IFPEN - IFP Energies nouvelles, IFP School)

  • Qi Zang

    (China University of Petroleum)

  • Siyuan Chen

    (China University of Petroleum)

Abstract

The rapid development of electric vehicles can greatly alleviate the environmental problems and energy tension. However, the lack of public supporting facilities has become the biggest problem hinders its development. How to reasonably plan the construction of charging facilities to meet the needs of electric vehicles has become an urgent situation in China. Different from other charging facilities, charging station could help to break the limitation of driving distance. It also has a special dual attribute of public service and high investment. So, this paper establishes a model with two objective functions of minimizing construction cost and maximizing its coverage and Particle Swarm Optimization was used to solve it. Besides, we take into account the conveniences of stations to charging vehicles and their influences on the loads of the power grid and GIS is used to overlay the traffic system diagram on power system diagram to find the alternative construction points. In this study, a district in Beijing is analyzed using the method and model we proposed. Finally, a planning strategy of charging station for Chinese market is suggested

Suggested Citation

  • Zhang Yue & Arash Farnoosh & Qi Zang & Siyuan Chen, 2018. "GIS-Based Multi-Objective Particle Swarm Optimization of Charging Station of Electric Vehicles – Taking a District in Beijing as an Example," Working Papers hal-03187920, HAL.
    • Handle: RePEc:hal:wpaper:hal-03187920
    Note: View the original document on HAL open archive server: https://ifp.hal.science/hal-03187920
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    References listed on IDEAS

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