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Integrated pricing strategy for coordinating load levels in coupled power and transportation networks

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  • Zhou, Ze
  • Liu, Zhitao
  • Su, Hongye
  • Zhang, Liyan

Abstract

The increasing popularity of electric vehicles and the development of dynamic wireless charging technology have strengthened the integration between the power system and transportation system. To coordinate the load levels of the coupled power distribution network and transportation network, we propose an integrated pricing strategy including road tolls and charging prices, which depend on the road traffic load rate in the transportation network and the bus load rate in the power distribution network, respectively. To accurately model the interdependency between the power distribution network and the transportation network, a proper interface equation is proposed. Considering data privacy, we adopt a distributed optimization. Furthermore, we present a power allocation strategy based on model predictive control to meet the charging requirements of different EVs. Correspondingly, the above ideas form a two-layer optimization strategy. Based on the integrated pricing strategy, the upper layer aims to minimize the power generation cost and transportation travel cost, while balancing the load levels. The lower layer distributes charging power to different EVs based on the total power demand from the interface equation between the power distribution network and the transportation network. Numerical results demonstrate the effectiveness of the proposed integrated pricing strategy for coordinating load levels in coupled networks.

Suggested Citation

  • Zhou, Ze & Liu, Zhitao & Su, Hongye & Zhang, Liyan, 2022. "Integrated pricing strategy for coordinating load levels in coupled power and transportation networks," Applied Energy, Elsevier, vol. 307(C).
  • Handle: RePEc:eee:appene:v:307:y:2022:i:c:s0306261921013817
    DOI: 10.1016/j.apenergy.2021.118100
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    References listed on IDEAS

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    Cited by:

    1. Liu, Ke & Liu, Yanli, 2023. "Stochastic user equilibrium based spatial-temporal distribution prediction of electric vehicle charging load," Applied Energy, Elsevier, vol. 339(C).
    2. Congyu Zhao & Kangyin Dong & Farhad Taghizadeh-Hesary, 2023. "Can smart transportation enhance green development efficiency?," Economic Change and Restructuring, Springer, vol. 56(2), pages 825-857, April.

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