IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i11p3296-d568911.html
   My bibliography  Save this article

Sizing and Management of Energy Storage Systems in Large-Scale Power Plants Using Price Control and Artificial Intelligence

Author

Listed:
  • Carlos García-Santacruz

    (Electronical Engineering Department, University of Seville, 41092 Seville, Spain)

  • Luis Galván

    (Electronical Engineering Department, University of Seville, 41092 Seville, Spain)

  • Juan M. Carrasco

    (Electronical Engineering Department, University of Seville, 41092 Seville, Spain)

  • Eduardo Galván

    (Electronical Engineering Department, University of Seville, 41092 Seville, Spain)

Abstract

Energy storage systems are expected to play a fundamental part in the integration of increasing renewable energy sources into the electric system. They are already used in power plants for different purposes, such as absorbing the effect of intermittent energy sources or providing ancillary services. For this reason, it is imperative to research managing and sizing methods that make power plants with storage viable and profitable projects. In this paper, a managing method is presented, where particle swarm optimisation is used to reach maximum profits. This method is compared to expert systems, proving that the former achieves better results, while respecting similar rules. The paper further presents a sizing method which uses the previous one to make the power plant as profitable as possible. Finally, both methods are tested through simulations to show their potential.

Suggested Citation

  • Carlos García-Santacruz & Luis Galván & Juan M. Carrasco & Eduardo Galván, 2021. "Sizing and Management of Energy Storage Systems in Large-Scale Power Plants Using Price Control and Artificial Intelligence," Energies, MDPI, vol. 14(11), pages 1-17, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:11:p:3296-:d:568911
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/11/3296/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/11/3296/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Holger C. Hesse & Volkan Kumtepeli & Michael Schimpe & Jorn Reniers & David A. Howey & Anshuman Tripathi & Youyi Wang & Andreas Jossen, 2019. "Ageing and Efficiency Aware Battery Dispatch for Arbitrage Markets Using Mixed Integer Linear Programming †," Energies, MDPI, vol. 12(6), pages 1-28, March.
    2. Marija Miletić & Hrvoje Pandžić & Dechang Yang, 2020. "Operating and Investment Models for Energy Storage Systems," Energies, MDPI, vol. 13(18), pages 1-33, September.
    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. Vykhodtsev, Anton V. & Jang, Darren & Wang, Qianpu & Rosehart, William & Zareipour, Hamidreza, 2022. "A review of modelling approaches to characterize lithium-ion battery energy storage systems in techno-economic analyses of power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    2. Collath, Nils & Cornejo, Martin & Engwerth, Veronika & Hesse, Holger & Jossen, Andreas, 2023. "Increasing the lifetime profitability of battery energy storage systems through aging aware operation," Applied Energy, Elsevier, vol. 348(C).
    3. Kristina Pandžić & Ivan Pavić & Ivan Andročec & Hrvoje Pandžić, 2020. "Optimal Battery Storage Participation in European Energy and Reserves Markets," Energies, MDPI, vol. 13(24), pages 1-21, December.
    4. Xu, Jianxi & Zeng, Jiabing & Huang, Jinyong, 2024. "A management system for energy storage," Applied Energy, Elsevier, vol. 368(C).
    5. Harun Or Rashid Howlader & Oludamilare Bode Adewuyi & Ying-Yi Hong & Paras Mandal & Ashraf Mohamed Hemeida & Tomonobu Senjyu, 2019. "Energy Storage System Analysis Review for Optimal Unit Commitment," Energies, MDPI, vol. 13(1), pages 1-21, December.
    6. Murat Ceylan & Abdulkadir Balikci, 2023. "An Intermodular Active Balancing Topology for Efficient Operation of High Voltage Battery Packs in Li-Ion Based Energy Storage Systems: Switched (Flying) DC/DC Converter," Energies, MDPI, vol. 16(15), pages 1-22, July.
    7. Walmsley, Timothy Gordon & Philipp, Matthias & Picón-Núñez, Martín & Meschede, Henning & Taylor, Matthew Thomas & Schlosser, Florian & Atkins, Martin John, 2023. "Hybrid renewable energy utility systems for industrial sites: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    8. Željko Tomšić & Sara Raos & Ivan Rajšl & Perica Ilak, 2020. "Role of Electric Vehicles in Transition to Low Carbon Power System—Case Study Croatia," Energies, MDPI, vol. 13(24), pages 1-22, December.
    9. Robert Małkowski & Marcin Jaskólski & Wojciech Pawlicki, 2020. "Operation of the Hybrid Photovoltaic-Battery System on the Electricity Market—Simulation, Real-Time Tests and Cost Analysis," Energies, MDPI, vol. 13(6), pages 1-21, March.
    10. Iris, Çağatay & Lam, Jasmine Siu Lee, 2021. "Optimal energy management and operations planning in seaports with smart grid while harnessing renewable energy under uncertainty," Omega, Elsevier, vol. 103(C).
    11. Specht, Jan Martin & Madlener, Reinhard, 2023. "Quantifying value pools for distributed flexible energy assets," Energy, Elsevier, vol. 263(PB).
    12. József Magyari & Krisztina Hegedüs & Botond Sinóros-Szabó, 2022. "Integration Opportunities of Power-to-Gas and Internet-of-Things Technical Advancements: A Systematic Literature Review," Energies, MDPI, vol. 15(19), pages 1-19, September.
    13. Gaurav Chaudhary & Jacob J. Lamb & Odne S. Burheim & Bjørn Austbø, 2021. "Review of Energy Storage and Energy Management System Control Strategies in Microgrids," Energies, MDPI, vol. 14(16), pages 1-26, August.
    14. Kanbur, Baris Burak & Kumtepeli, Volkan & Duan, Fei, 2020. "Thermal performance prediction of the battery surface via dynamic mode decomposition," Energy, Elsevier, vol. 201(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:gam:jeners:v:14:y:2021:i:11:p:3296-:d:568911. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.