IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v262y2023ipbs0360544222025105.html
   My bibliography  Save this article

Optimal energy management of multiple electricity-hydrogen integrated charging stations

Author

Listed:
  • Fang, Xiaolun
  • Wang, Yubin
  • Dong, Wei
  • Yang, Qiang
  • Sun, Siyang

Abstract

Hydrogen is considered promising for the replacement of fossil fuels in integrated energy systems through hydrogen energy storage (HES). This paper considers multiple electricity-hydrogen integrated charging stations (EHI-CSs) as a unit consisting of photovoltaic systems and HES systems for charging plug-in electric vehicles and refilling hydrogen fuel vehicles. In the multiple EHI-CSs unit, a set of interconnected EHI-CSs can be supplied by other EHI-CSs or power utilities and an EHI-CSs aggregator can manage the individual EHI-CSs through controllable facilities (i.e., HES system) and adjustment methods (i.e., energy transportation between subsystems). Meanwhile, a two-stage energy management system (EMS) strategy is proposed to coordinate the day-ahead scheduling and real-time dispatch. In the day-ahead scheduling stage, the aggregator minimizes the cost of the overall multiple EHI-CSs unit through optimization, and in the real-time dispatching stage, the intraday energy dispatch based model predictive control (MPC) is carried out to minimize the penalty cost. The proposed two-stage EMS strategy is evaluated through simulations and the numerical results confirm that the proposed solution outperforms the baseline solution with additional economic benefit.

Suggested Citation

  • Fang, Xiaolun & Wang, Yubin & Dong, Wei & Yang, Qiang & Sun, Siyang, 2023. "Optimal energy management of multiple electricity-hydrogen integrated charging stations," Energy, Elsevier, vol. 262(PB).
    • Handle: RePEc:eee:energy:v:262:y:2023:i:pb:s0360544222025105
    DOI: 10.1016/j.energy.2022.125624
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222025105
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.125624?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Petrollese, Mario & Valverde, Luis & Cocco, Daniele & Cau, Giorgio & Guerra, José, 2016. "Real-time integration of optimal generation scheduling with MPC for the energy management of a renewable hydrogen-based microgrid," Applied Energy, Elsevier, vol. 166(C), pages 96-106.
    2. Wang, Longze & Jiao, Shucen & Xie, Yu & Xia, Shiwei & Zhang, Delong & Zhang, Yan & Li, Meicheng, 2022. "Two-way dynamic pricing mechanism of hydrogen filling stations in electric-hydrogen coupling system enhanced by blockchain," Energy, Elsevier, vol. 239(PC).
    3. Nikmehr, Nima & Najafi-Ravadanegh, Sajad & Khodaei, Amin, 2017. "Probabilistic optimal scheduling of networked microgrids considering time-based demand response programs under uncertainty," Applied Energy, Elsevier, vol. 198(C), pages 267-279.
    4. Ganesh, Akhil Hannegudda & Xu, Bin, 2022. "A review of reinforcement learning based energy management systems for electrified powertrains: Progress, challenge, and potential solution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    5. Panah, Payam Ghaebi & Bornapour, Mosayeb & Hemmati, Reza & Guerrero, Josep M., 2021. "Charging station Stochastic Programming for Hydrogen/Battery Electric Buses using Multi-Criteria Crow Search Algorithm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    6. Wu, Xiong & Qi, Shixiong & Wang, Zhao & Duan, Chao & Wang, Xiuli & Li, Furong, 2019. "Optimal scheduling for microgrids with hydrogen fueling stations considering uncertainty using data-driven approach," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    7. Apostolou, D. & Xydis, G., 2019. "A literature review on hydrogen refuelling stations and infrastructure. Current status and future prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    8. Das, Saborni & Basu, Mousumi, 2020. "Day-ahead optimal bidding strategy of microgrid with demand response program considering uncertainties and outages of renewable energy resources," Energy, Elsevier, vol. 190(C).
    9. Wang, Yubin & Dong, Wei & Yang, Qiang, 2022. "Multi-stage optimal energy management of multi-energy microgrid in deregulated electricity markets," Applied Energy, Elsevier, vol. 310(C).
    10. Zheng, Yanchong & Yu, Hang & Shao, Ziyun & Jian, Linni, 2020. "Day-ahead bidding strategy for electric vehicle aggregator enabling multiple agent modes in uncertain electricity markets," Applied Energy, Elsevier, vol. 280(C).
    11. Zhang, Honghui & Chen, Yuanyuan & Liu, Kuili & Dehan, Sim, 2022. "A novel power system scheduling based on hydrogen-based micro energy hub," Energy, Elsevier, vol. 251(C).
    12. Pelletier, Samuel & Jabali, Ola & Laporte, Gilbert & Veneroni, Marco, 2017. "Battery degradation and behaviour for electric vehicles: Review and numerical analyses of several models," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 158-187.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Zongnan & Fedorovich, Kudashev Sergey, 2024. "Optimal operation of multi-integrated energy system based on multi-level Nash multi-stage robust," Applied Energy, Elsevier, vol. 358(C).
    2. Zhao, Yuehao & Li, Zhiyi & Ju, Ping & Zhou, Yue, 2023. "Two-stage data-driven dispatch for integrated power and natural gas systems by using stochastic model predictive control," Applied Energy, Elsevier, vol. 343(C).
    3. Cai, Pengcheng & Mi, Yang & Ma, Siyuan & Li, Hongzhong & Li, Dongdong & Wang, Peng, 2023. "Hierarchical game for integrated energy system and electricity-hydrogen hybrid charging station under distributionally robust optimization," Energy, Elsevier, vol. 283(C).
    4. Wang, Yubin & Zheng, Yanchong & Yang, Qiang, 2023. "Nash bargaining based collaborative energy management for regional integrated energy systems in uncertain electricity markets," Energy, Elsevier, vol. 269(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fang, Xiaolun & Dong, Wei & Wang, Yubin & Yang, Qiang, 2022. "Multiple time-scale energy management strategy for a hydrogen-based multi-energy microgrid," Applied Energy, Elsevier, vol. 328(C).
    2. Fang, Xiaolun & Dong, Wei & Wang, Yubin & Yang, Qiang, 2024. "Multi-stage and multi-timescale optimal energy management for hydrogen-based integrated energy systems," Energy, Elsevier, vol. 286(C).
    3. Wang, Yubin & Dong, Wei & Yang, Qiang, 2022. "Multi-stage optimal energy management of multi-energy microgrid in deregulated electricity markets," Applied Energy, Elsevier, vol. 310(C).
    4. Wang, Yubin & Zheng, Yanchong & Yang, Qiang, 2023. "Day-ahead bidding strategy of regional integrated energy systems considering multiple uncertainties in electricity markets," Applied Energy, Elsevier, vol. 348(C).
    5. Wang, Yubin & Zheng, Yanchong & Yang, Qiang, 2023. "Optimal energy management of integrated energy systems for strategic participation in competitive electricity markets," Energy, Elsevier, vol. 278(PA).
    6. Àlex Alonso-Travesset & Helena Martín & Sergio Coronas & Jordi de la Hoz, 2022. "Optimization Models under Uncertainty in Distributed Generation Systems: A Review," Energies, MDPI, vol. 15(5), pages 1-40, March.
    7. Wang, Yubin & Zheng, Yanchong & Yang, Qiang, 2023. "Nash bargaining based collaborative energy management for regional integrated energy systems in uncertain electricity markets," Energy, Elsevier, vol. 269(C).
    8. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    9. Zhang, Xinyue & Guo, Xiaopeng & Zhang, Xingping, 2023. "Bidding modes for renewable energy considering electricity-carbon integrated market mechanism based on multi-agent hybrid game," Energy, Elsevier, vol. 263(PA).
    10. Xiao, Tianqi & You, Fengqi, 2024. "Physically consistent deep learning-based day-ahead energy dispatching and thermal comfort control for grid-interactive communities," Applied Energy, Elsevier, vol. 353(PB).
    11. Ghasemi, Ahmad & Jamshidi Monfared, Houman & Loni, Abdolah & Marzband, Mousa, 2021. "CVaR-based retail electricity pricing in day-ahead scheduling of microgrids," Energy, Elsevier, vol. 227(C).
    12. Chang, Weiguang & Dong, Wei & Yang, Qiang, 2023. "Day-ahead bidding strategy of cloud energy storage serving multiple heterogeneous microgrids in the electricity market," Applied Energy, Elsevier, vol. 336(C).
    13. Jiarui Wang & Dexin Li & Xiangyu Lv & Xiangdong Meng & Jiajun Zhang & Tengfei Ma & Wei Pei & Hao Xiao, 2022. "Two-Stage Energy Management Strategies of Sustainable Wind-PV-Hydrogen-Storage Microgrid Based on Receding Horizon Optimization," Energies, MDPI, vol. 15(8), pages 1-18, April.
    14. Morteza Nazari-Heris & Mehdi Abapour & Behnam Mohammadi-Ivatloo, 2022. "An Updated Review and Outlook on Electric Vehicle Aggregators in Electric Energy Networks," Sustainability, MDPI, vol. 14(23), pages 1-24, November.
    15. Mansouri, Seyed Amir & Rezaee Jordehi, Ahmad & Marzband, Mousa & Tostado-Véliz, Marcos & Jurado, Francisco & Aguado, José A., 2023. "An IoT-enabled hierarchical decentralized framework for multi-energy microgrids market management in the presence of smart prosumers using a deep learning-based forecaster," Applied Energy, Elsevier, vol. 333(C).
    16. Chang, Weiguang & Dong, Wei & Wang, Yubin & Yang, Qiang, 2022. "Two-stage coordinated operation framework for virtual power plant with aggregated multi-stakeholder microgrids in a deregulated electricity market," Renewable Energy, Elsevier, vol. 199(C), pages 943-956.
    17. Sharma, Pavitra & Dutt Mathur, Hitesh & Mishra, Puneet & Bansal, Ramesh C., 2022. "A critical and comparative review of energy management strategies for microgrids," Applied Energy, Elsevier, vol. 327(C).
    18. Ajoulabadi, Ata & Ravadanegh, Sajad Najafi & Behnam Mohammadi-Ivatloo,, 2020. "Flexible scheduling of reconfigurable microgrid-based distribution networks considering demand response program," Energy, Elsevier, vol. 196(C).
    19. Zhou, Yu & Meng, Qiang & Ong, Ghim Ping, 2022. "Electric Bus Charging Scheduling for a Single Public Transport Route Considering Nonlinear Charging Profile and Battery Degradation Effect," Transportation Research Part B: Methodological, Elsevier, vol. 159(C), pages 49-75.
    20. Wang, Dongxue & Fan, Ruguo & Yang, Peiwen & Du, Kang & Xu, Xiaoxia & Chen, Rongkai, 2024. "Research on floating real-time pricing strategy for microgrid operator in local energy market considering shared energy storage leasing," Applied Energy, Elsevier, vol. 368(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:262:y:2023:i:pb:s0360544222025105. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.