IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v376y2024ipas0306261924013485.html
   My bibliography  Save this article

Peak shaving with hydrogen energy storage: From stochastic control to experiments on a 4 MWh facility

Author

Listed:
  • Fochesato, Marta
  • Peter, Christian
  • Morandi, Lisa
  • Lygeros, John

Abstract

The formation of power peaks caused by the stochastic nature of the electric vehicles (EVs) charging process is raising concerns related to the stability of the power grid. In this work, we consider an EV charging station equipped with a hydrogen-based energy storage system (HESS) and on-site renewable power generation, and we offer an experimental demonstration of its potential in reducing the power peak of the EV charging station, despite uncertainty in the demand. Our contributions are as follows: (1) we derive a complete system description of a real 4 MWh HESS, and (2) we develop a stochastic model-based receding horizon controller that jointly schedules the charging process and the HESS operation to minimize the power peak. The proposed approach is validated both in simulation and via experiments that demonstrate (i) excellent performance, with an average daily peak reduction of 49.2% with respect to the benchmark, and (ii) scalable run times, making it amenable to real-time operations even in the large EV penetration regime.

Suggested Citation

  • Fochesato, Marta & Peter, Christian & Morandi, Lisa & Lygeros, John, 2024. "Peak shaving with hydrogen energy storage: From stochastic control to experiments on a 4 MWh facility," Applied Energy, Elsevier, vol. 376(PA).
    • Handle: RePEc:eee:appene:v:376:y:2024:i:pa:s0306261924013485
    DOI: 10.1016/j.apenergy.2024.123965
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924013485
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.123965?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. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    2. Flamm, Benjamin & Peter, Christian & Büchi, Felix N. & Lygeros, John, 2021. "Electrolyzer modeling and real-time control for optimized production of hydrogen gas," Applied Energy, Elsevier, vol. 281(C).
    3. Soares, João & Ghazvini, Mohammad Ali Fotouhi & Borges, Nuno & Vale, Zita, 2017. "Dynamic electricity pricing for electric vehicles using stochastic programming," Energy, Elsevier, vol. 122(C), pages 111-127.
    4. Reno, Matthew J. & Hansen, Clifford W., 2016. "Identification of periods of clear sky irradiance in time series of GHI measurements," Renewable Energy, Elsevier, vol. 90(C), pages 520-531.
    5. Uddin, Moslem & Romlie, Mohd Fakhizan & Abdullah, Mohd Faris & Abd Halim, Syahirah & Abu Bakar, Ab Halim & Chia Kwang, Tan, 2018. "A review on peak load shaving strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3323-3332.
    6. Rishabh Ghotge & Yitzhak Snow & Samira Farahani & Zofia Lukszo & Ad van Wijk, 2020. "Optimized Scheduling of EV Charging in Solar Parking Lots for Local Peak Reduction under EV Demand Uncertainty," Energies, MDPI, vol. 13(5), pages 1-18, March.
    7. Le, Tay Son & Nguyen, Tuan Ngoc & Bui, Dac-Khuong & Ngo, Tuan Duc, 2023. "Optimal sizing of renewable energy storage: A techno-economic analysis of hydrogen, battery and hybrid systems considering degradation and seasonal storage," Applied Energy, Elsevier, vol. 336(C).
    8. Eriksson, E.L.V. & Gray, E.MacA., 2017. "Optimization and integration of hybrid renewable energy hydrogen fuel cell energy systems – A critical review," Applied Energy, Elsevier, vol. 202(C), pages 348-364.
    9. Philippe Thalmann & Marc Vielle, 2019. "Lowering CO2 emissions in the Swiss transport sector," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 155(1), pages 1-12, December.
    Full references (including those not matched with items on IDEAS)

    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. Asaad Mohammad & Ramon Zamora & Tek Tjing Lie, 2020. "Integration of Electric Vehicles in the Distribution Network: A Review of PV Based Electric Vehicle Modelling," Energies, MDPI, vol. 13(17), pages 1-20, September.
    2. Adil Amin & Wajahat Ullah Khan Tareen & Muhammad Usman & Haider Ali & Inam Bari & Ben Horan & Saad Mekhilef & Muhammad Asif & Saeed Ahmed & Anzar Mahmood, 2020. "A Review of Optimal Charging Strategy for Electric Vehicles under Dynamic Pricing Schemes in the Distribution Charging Network," Sustainability, MDPI, vol. 12(23), pages 1-28, December.
    3. Le, Son Tay & Nguyen, Tuan Ngoc & Bui, Dac-Khuong & Teodosio, Birch & Ngo, Tuan Duc, 2024. "Comparative life cycle assessment of renewable energy storage systems for net-zero buildings with varying self-sufficient ratios," Energy, Elsevier, vol. 290(C).
    4. Le, Son Tay & Nguyen, Tuan Ngoc & Bui, Dac-Khuong & Ngo, Tuan Duc, 2024. "Techno-economic and life cycle analysis of renewable energy storage systems in buildings: The effect of uncertainty," Energy, Elsevier, vol. 307(C).
    5. Le, Tay Son & Nguyen, Tuan Ngoc & Bui, Dac-Khuong & Ngo, Tuan Duc, 2023. "Optimal sizing of renewable energy storage: A techno-economic analysis of hydrogen, battery and hybrid systems considering degradation and seasonal storage," Applied Energy, Elsevier, vol. 336(C).
    6. Zanvettor, Giovanni Gino & Fochesato, Marta & Casini, Marco & Lygeros, John & Vicino, Antonio, 2024. "A stochastic approach for EV charging stations in demand response programs," Applied Energy, Elsevier, vol. 373(C).
    7. Bizon, Nicu, 2019. "Real-time optimization strategies of Fuel Cell Hybrid Power Systems based on Load-following control: A new strategy, and a comparative study of topologies and fuel economy obtained," Applied Energy, Elsevier, vol. 241(C), pages 444-460.
    8. Gueymard, Christian A. & Bright, Jamie M. & Lingfors, David & Habte, Aron & Sengupta, Manajit, 2019. "A posteriori clear-sky identification methods in solar irradiance time series: Review and preliminary validation using sky imagers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 412-427.
    9. Heo, SungKu & Byun, Jaewon & Ifaei, Pouya & Ko, Jaerak & Ha, Byeongmin & Hwangbo, Soonho & Yoo, ChangKyoo, 2024. "Towards mega-scale decarbonized industrial park (Mega-DIP): Generative AI-driven techno-economic and environmental assessment of renewable and sustainable energy utilization in petrochemical industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    10. Alqahtani, Mohammed & Hu, Mengqi, 2022. "Dynamic energy scheduling and routing of multiple electric vehicles using deep reinforcement learning," Energy, Elsevier, vol. 244(PA).
    11. Andoni, Merlinda & Robu, Valentin & Flynn, David & Abram, Simone & Geach, Dale & Jenkins, David & McCallum, Peter & Peacock, Andrew, 2019. "Blockchain technology in the energy sector: A systematic review of challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 143-174.
    12. Antoine Boche & Clément Foucher & Luiz Fernando Lavado Villa, 2022. "Understanding Microgrid Sustainability: A Systemic and Comprehensive Review," Energies, MDPI, vol. 15(8), pages 1-29, April.
    13. Silva, Ana R. & Pousinho, H.M.I. & Estanqueiro, Ana, 2022. "A multistage stochastic approach for the optimal bidding of variable renewable energy in the day-ahead, intraday and balancing markets," Energy, Elsevier, vol. 258(C).
    14. Emblemsvåg, Jan, 2022. "Wind energy is not sustainable when balanced by fossil energy," Applied Energy, Elsevier, vol. 305(C).
    15. Gao, Datong & Zhao, Bin & Kwan, Trevor Hocksun & Hao, Yong & Pei, Gang, 2022. "The spatial and temporal mismatch phenomenon in solar space heating applications: status and solutions," Applied Energy, Elsevier, vol. 321(C).
    16. Daxini, Rajiv & Wu, Yupeng, 2024. "Review of methods to account for the solar spectral influence on photovoltaic device performance," Energy, Elsevier, vol. 286(C).
    17. Saima Akhtar & Sulman Shahzad & Asad Zaheer & Hafiz Sami Ullah & Heybet Kilic & Radomir Gono & Michał Jasiński & Zbigniew Leonowicz, 2023. "Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead," Energies, MDPI, vol. 16(10), pages 1-29, May.
    18. Bizon, Nicu, 2019. "Efficient fuel economy strategies for the Fuel Cell Hybrid Power Systems under variable renewable/load power profile," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    19. Khan, Waqas & Walker, Shalika & Zeiler, Wim, 2022. "Improved solar photovoltaic energy generation forecast using deep learning-based ensemble stacking approach," Energy, Elsevier, vol. 240(C).
    20. Vasallo, Manuel Jesús & Cojocaru, Emilian Gelu & Gegúndez, Manuel Emilio & Marín, Diego, 2021. "Application of data-based solar field models to optimal generation scheduling in concentrating solar power plants," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 1130-1149.

    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:appene:v:376:y:2024:i:pa:s0306261924013485. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.