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Powering the Future: A Comprehensive Review of Battery Energy Storage Systems

Author

Listed:
  • Sergi Obrador Rey

    (Power Systems Group, Catalonia Institute for Energy Research (IREC), 08930 Barcelona, Spain)

  • Juan Alberto Romero

    (Power Systems Group, Catalonia Institute for Energy Research (IREC), 08930 Barcelona, Spain)

  • Lluis Trilla Romero

    (Power Systems Group, Catalonia Institute for Energy Research (IREC), 08930 Barcelona, Spain)

  • Àlber Filbà Martínez

    (Power Systems Group, Catalonia Institute for Energy Research (IREC), 08930 Barcelona, Spain)

  • Xavier Sanchez Roger

    (Power Systems Group, Catalonia Institute for Energy Research (IREC), 08930 Barcelona, Spain)

  • Muhammad Attique Qamar

    (Power Systems Group, Catalonia Institute for Energy Research (IREC), 08930 Barcelona, Spain)

  • José Luis Domínguez-García

    (Power Systems Group, Catalonia Institute for Energy Research (IREC), 08930 Barcelona, Spain)

  • Levon Gevorkov

    (Power Systems Group, Catalonia Institute for Energy Research (IREC), 08930 Barcelona, Spain)

Abstract

Global society is significantly speeding up the adoption of renewable energy sources and their integration into the current existing grid in order to counteract growing environmental problems, particularly the increased carbon dioxide emission of the last century. Renewable energy sources have a tremendous potential to reduce carbon dioxide emissions because they practically never produce any carbon dioxide or other pollutants. On the other hand, these energy sources are usually influenced by geographical location, weather, and other factors that are of stochastic nature. The battery energy storage system can be applied to store the energy produced by RESs and then utilized regularly and within limits as necessary to lessen the impact of the intermittent nature of renewable energy sources. The main purpose of the review paper is to present the current state of the art of battery energy storage systems and identify their advantages and disadvantages. At the same time, this helps researchers and engineers in the field to find out the most appropriate configuration for a particular application. This study offers a thorough analysis of the battery energy storage system with regard to battery chemistries, power electronics, and management approaches. This paper also offers a detailed analysis of battery energy storage system applications and investigates the shortcomings of the current best battery energy storage system architectures to pinpoint areas that require further study.

Suggested Citation

  • Sergi Obrador Rey & Juan Alberto Romero & Lluis Trilla Romero & Àlber Filbà Martínez & Xavier Sanchez Roger & Muhammad Attique Qamar & José Luis Domínguez-García & Levon Gevorkov, 2023. "Powering the Future: A Comprehensive Review of Battery Energy Storage Systems," Energies, MDPI, vol. 16(17), pages 1-21, September.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6344-:d:1231011
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    References listed on IDEAS

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    1. Nickolay I. Shchurov & Sergey I. Dedov & Boris V. Malozyomov & Alexander A. Shtang & Nikita V. Martyushev & Roman V. Klyuev & Sergey N. Andriashin, 2021. "Degradation of Lithium-Ion Batteries in an Electric Transport Complex," Energies, MDPI, vol. 14(23), pages 1-33, December.
    2. Christopher Welch & Abdul Kaleem Mohammad & Narayan S. Hosmane & Lu Zhang & Kyu Taek Cho, 2020. "Effect of Aluminum Oxide on the Performance of Ionic Liquid-Based Aluminum–Air Battery," Energies, MDPI, vol. 13(8), pages 1-27, April.
    3. Zhang, Cheng & Allafi, Walid & Dinh, Quang & Ascencio, Pedro & Marco, James, 2018. "Online estimation of battery equivalent circuit model parameters and state of charge using decoupled least squares technique," Energy, Elsevier, vol. 142(C), pages 678-688.
    4. Shyh-Chin Huang & Kuo-Hsin Tseng & Jin-Wei Liang & Chung-Liang Chang & Michael G. Pecht, 2017. "An Online SOC and SOH Estimation Model for Lithium-Ion Batteries," Energies, MDPI, vol. 10(4), pages 1-18, April.
    5. Kang, Jianqiang & Yan, Fuwu & Zhang, Pei & Du, Changqing, 2014. "Comparison of comprehensive properties of Ni-MH (nickel-metal hydride) and Li-ion (lithium-ion) batteries in terms of energy efficiency," Energy, Elsevier, vol. 70(C), pages 618-625.
    6. Anisha & Anil Kumar, 2023. "Identification and Mitigation of Shortcomings in Direct and Indirect Liquid Cooling-Based Battery Thermal Management System," Energies, MDPI, vol. 16(9), pages 1-21, April.
    7. Moez Krichen & Yasir Basheer & Saeed Mian Qaisar & Asad Waqar, 2023. "A Survey on Energy Storage: Techniques and Challenges," Energies, MDPI, vol. 16(5), pages 1-29, February.
    8. Chan, Lok Shun, 2023. "Transition from fossil fuel propelled transport to electrified mass transit railway system - Experience from Hong Kong," Energy Policy, Elsevier, vol. 173(C).
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    4. Solmaz Nazaralizadeh & Paramarshi Banerjee & Anurag K. Srivastava & Parviz Famouri, 2024. "Battery Energy Storage Systems: A Review of Energy Management Systems and Health Metrics," Energies, MDPI, vol. 17(5), pages 1-21, March.

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