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Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen Pricing

Author

Listed:
  • Hui Guo

    (School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China)

  • Dandan Gong

    (School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China)

  • Lijun Zhang

    (Instituto Superior Técnico, University of Lisbon, 999022 Lisbon, Portugal)

  • Wenke Mo

    (Shanghai Marine Equipment Research Institute, Shanghai 200031, China)

  • Feng Ding

    (Shanghai Marine Equipment Research Institute, Shanghai 200031, China)

  • Fei Wang

    (School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China)

Abstract

The growing popularity of renewable energy and hydrogen-powered vehicles (HVs) will facilitate the coordinated optimization of energy and transportation systems for economic and environmental benefits. However, little research attention has been paid to dynamic hydrogen pricing and its impact on the optimal performance of energy and transportation systems. To reduce the dependency on centralized controllers and protect information privacy, a time-decoupling layered optimization strategy is put forward to realize the low-carbon and economic operation of energy and transportation systems under dynamic hydrogen pricing. First, a dynamic hydrogen pricing mechanism was formulated on the basis of the share of renewable power in the energy supply and introduced into the optimization of distributed energy stations (DESs), which will promote hydrogen production using renewable power and minimize the DES construction and operation cost. On the basis of the dynamic hydrogen price optimized by DESs and the traffic conditions on roads, the raised user-centric routing optimization method can select a minimum cost route for HVs to purchase fuels from a DES with low-cost and/or low-carbon hydrogen. Finally, the effectiveness of the proposed optimization strategy was verified by simulations.

Suggested Citation

  • Hui Guo & Dandan Gong & Lijun Zhang & Wenke Mo & Feng Ding & Fei Wang, 2022. "Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen Pricing," Energies, MDPI, vol. 15(15), pages 1-18, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5382-:d:871292
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    References listed on IDEAS

    as
    1. Chao Luo & Yih-Fang Huang & Vijay Gupta, 2018. "Stochastic Dynamic Pricing for EV Charging Stations with Renewables Integration and Energy Storage," Papers 1801.02128, arXiv.org.
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