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Improving the Battery Energy Storage System Performance in Peak Load Shaving Applications

Author

Listed:
  • Anderson V. Rocha

    (Centro Federal de Educação Tecnológica de Minas Gerais—CEFET-MG, Belo Horizonte 30421-169, Brazil)

  • Thales A. C. Maia

    (Graduate Program in Electrical Engineering, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Brazil)

  • Braz J. C. Filho

    (Graduate Program in Electrical Engineering, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, Brazil)

Abstract

Peak load shaving using energy storage systems has been the preferred approach to smooth the electricity load curve of consumers from different sectors around the world. These systems store energy during off-peak hours, releasing it for usage during high consumption periods. Most of the current solutions use solar energy as a power source and chemical batteries as energy storage elements. Despite the clear benefits of this strategy, the service life of the battery energy storage system (BESS) is a driving factor for economic feasibility. The present research work proposes the use of storage systems based on actively connected batteries with power electronics support. The proposed scheme allows the individualized control of the power flow, enabling the use of batteries with different ages, technologies or degradation states in a same BESS. The presented results show that overcoming inherent limitations found in passively connected battery banks makes it possible to extend the system’s useful life and the total amount of dispatched energy by more than 50%. Experimental tests on a bench prototype with electronified batteries are carried out to proof the central concept of the proposed solution. Computational simulations using collected data from a photovoltaic plant support the conclusions and discussions on the achieved benefits.

Suggested Citation

  • Anderson V. Rocha & Thales A. C. Maia & Braz J. C. Filho, 2022. "Improving the Battery Energy Storage System Performance in Peak Load Shaving Applications," Energies, MDPI, vol. 16(1), pages 1-19, December.
    • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:382-:d:1018797
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    References listed on IDEAS

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    1. Rodrigo Martins & Holger C. Hesse & Johanna Jungbauer & Thomas Vorbuchner & Petr Musilek, 2018. "Optimal Component Sizing for Peak Shaving in Battery Energy Storage System for Industrial Applications," Energies, MDPI, vol. 11(8), pages 1-22, August.
    2. Nicolas T. D. Fernandes & Anderson Rocha & Danilo Brandao & Braz C. Filho, 2021. "Comparison of Advanced Charge Strategies for Modular Cascaded Battery Chargers," Energies, MDPI, vol. 14(12), pages 1-28, June.
    3. Li, Yi & Liu, Kailong & Foley, Aoife M. & Zülke, Alana & Berecibar, Maitane & Nanini-Maury, Elise & Van Mierlo, Joeri & Hoster, Harry E., 2019. "Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
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    Cited by:

    1. Diego Jose da Silva & Edmarcio Antonio Belati & Jesús M. López-Lezama, 2024. "Enhancing Distribution Networks with Optimal BESS Sitting and Operation: A Weekly Horizon Optimization Approach," Sustainability, MDPI, vol. 16(17), pages 1-15, August.

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